PERFECT PIVOT RANGE DR ABIRAM SIVPRASAD (PPR)PERFECT PIVOT RANGE (PPR) by Dr. Abhiram Sivprasad
The Perfect Pivot Range (PPR) indicator is designed to provide traders with a comprehensive view of key support and resistance levels based on pivot points across different timeframes. This versatile tool allows users to visualize daily, weekly, and monthly pivots along with high and low levels from previous periods, helping traders identify potential areas of price reversals or breakouts.
Features:
Multi-Timeframe Pivots:
Daily, weekly, and monthly pivot levels (Pivot Point, Support 1 & 2, Resistance 1 & 2).
Helps traders understand price levels across various timeframes, from short-term (daily) to long-term (monthly).
Previous High-Low Levels:
Displays the previous week, month, and day high-low levels to highlight key zones of historical support and resistance.
Traders can easily see areas of price action from prior periods, giving context for future price movements.
Customizable Options:
Users can choose which pivot levels and high-lows to display, allowing for flexibility based on trading preferences.
Visual settings can be toggled on and off to suit different trading strategies and timeframes.
Real-Time Data:
All pivot points and levels are dynamically calculated based on real-time price data, ensuring accurate and up-to-date information for decision-making.
How to Use:
Pivot Points: Use daily, weekly, or monthly pivot points to find potential support or resistance levels. Prices above the pivot suggest bullish sentiment, while prices below indicate bearishness.
Previous High-Low: The high-low levels from previous days, weeks, or months can serve as critical zones where price may reverse or break through, indicating potential trade entries or exits.
Confluence: When pivot points or high-low levels overlap across multiple timeframes, they become even stronger levels of support or resistance.
This indicator is suitable for all types of traders (scalpers, swing traders, and long-term investors) looking to enhance their technical analysis and make more informed trading decisions.
Here are three detailed trading strategies for using the Perfect Pivot Range (PPR) indicator for options, stocks, and commodities:
1. Options Buying Strategy with PPR Indicator
Strategy: Buying Call and Put Options Based on Pivot Breakouts
Objective: To capitalize on sharp price movements when key pivot levels are breached, leading to high returns with limited risk in options trading.
Timeframe: 15-minute to 1-hour chart for intraday option trading.
Steps:
Identify the Key Levels:
Use weekly pivots for intraday trading, as they provide more significant levels for options.
Enable the "Previous Week High-Low" to gauge support and resistance from the previous week.
Call Option Setup (Bullish Breakout):
Condition: If the price breaks above the weekly pivot point (PP) with high momentum (indicated by a strong bullish candle), it signifies potential bullishness.
Action: Buy Call Options at the breakout of the weekly pivot.
Confirmation: Check if the price is sustaining above the pivot with a minimum of 1-2 candles (depending on timeframe) and the first resistance (R1) isn’t too far away.
Target: The first resistance (R1) or previous week’s high can be your target for exiting the trade.
Stop-Loss: Set a stop-loss just below the pivot point (PP) to limit risk.
Put Option Setup (Bearish Breakdown):
Condition: If the price breaks below the weekly pivot (PP) with strong bearish momentum, it’s a signal to expect a downward move.
Action: Buy Put Options on a breakdown below the weekly pivot.
Confirmation: Ensure that the price is closing below the pivot, and check for declining volumes or bearish candles.
Target: The first support (S1) or the previous week’s low.
Stop-Loss: Place the stop-loss just above the pivot point (PP).
Example:
Let’s say the weekly pivot point (PP) is at 1500, the price breaks above and sustains at 1510. You buy a Call Option with a strike price near 1500, and the target will be the first resistance (R1) at 1530.
2. Stock Trading Strategy with PPR Indicator
Strategy: Swing Trading Using Pivot Points and Previous High-Low Levels
Objective: To capture mid-term stock price movements using pivot points and historical high-low levels for better trade entries and exits.
Timeframe: 1-day or 4-hour chart for swing trading.
Steps:
Identify the Trend:
Start by determining the overall trend of the stock using the weekly pivots. If the price is consistently above the pivot point (PP), the trend is bullish; if below, the trend is bearish.
Buy Setup (Bullish Trend Reversal):
Condition: When the stock bounces off the weekly pivot point (PP) or previous week’s low, it signals a bullish reversal.
Action: Enter a long position near the pivot or previous week’s low.
Confirmation: Look for a bullish candle pattern or increasing volumes.
Target: Set your first target at the first resistance (R1) or the previous week’s high.
Stop-Loss: Place your stop-loss just below the previous week’s low or support (S1).
Sell Setup (Bearish Trend Reversal):
Condition: When the price hits the weekly resistance (R1) or previous week’s high and starts to reverse downwards, it’s an opportunity to short-sell the stock.
Action: Enter a short position near the resistance.
Confirmation: Watch for bearish candle patterns or decreasing volume at the resistance.
Target: Your first target would be the weekly pivot point (PP), with the second target as the previous week’s low.
Stop-Loss: Set a stop-loss just above the resistance (R1).
Use Previous High-Low Levels:
The previous week’s high and low are key levels where price reversals often occur, so use them as reference points for potential entry and exit.
Example:
Stock XYZ is trading at 200. The previous week’s low is 195, and it bounces off that level. You enter a long position with a target of 210 (previous week’s high) and place a stop-loss at 193.
3. Commodity Trading Strategy with PPR Indicator
Strategy: Trend Continuation and Reversal in Commodities
Objective: To capitalize on the strong trends in commodities by using pivot points as key support and resistance levels for trend continuation and reversal.
Timeframe: 1-hour to 4-hour charts for commodities like Gold, Crude Oil, Silver, etc.
Steps:
Identify the Trend:
Use monthly pivots for long-term commodities trading since commodities often follow macroeconomic trends.
The monthly pivot point (PP) will give an idea of the long-term trend direction.
Trend Continuation Setup (Bullish Commodity):
Condition: If the price is consistently trading above the monthly pivot and pulling back towards the pivot without breaking below it, it indicates a bullish continuation.
Action: Enter a long position when the price tests the monthly pivot (PP) and starts moving up again.
Confirmation: Look for a strong bullish candle or an increase in volume to confirm the continuation.
Target: The first resistance (R1) or previous month’s high.
Stop-Loss: Place the stop-loss below the monthly pivot (PP).
Trend Reversal Setup (Bearish Commodity):
Condition: When the price reverses from the monthly resistance (R1) or previous month’s high, it’s a signal for a bearish reversal.
Action: Enter a short position at the resistance level.
Confirmation: Watch for bearish candle patterns or decreasing volumes at the resistance.
Target: Set your first target as the monthly pivot (PP) or the first support (S1).
Stop-Loss: Stop-loss should be placed just above the resistance level.
Using Previous High-Low for Swing Trades:
The previous month’s high and low are important in commodities. They often act as barriers to price movement, so traders should look for breakouts or reversals near these levels.
Example:
Gold is trading at $1800, with a monthly pivot at $1780 and the previous month’s high at $1830. If the price pulls back to $1780 and starts moving up again, you enter a long trade with a target of $1830, placing your stop-loss below $1770.
Key Points Across All Strategies:
Multiple Timeframes: Always use a combination of timeframes for confirmation. For example, a daily chart may show a bullish setup, but the weekly pivot levels can provide a larger trend context.
Volume: Volume is key in confirming the strength of price movement. Always confirm breakouts or reversals with rising or declining volume.
Risk Management: Set tight stop-loss levels just below support or above resistance to minimize risk and lock in profits at pivot points.
Each of these strategies leverages the powerful pivot and high-low levels provided by the PPR indicator to give traders clear entry, exit, and risk management points across different markets
Cerca negli script per "high low"
ziksfx Structure - LiteInspired by the 'mentfx Structure' indicator created by Anton (mentfx) on TradingView, I have developed my own unique version of the market structure indicator, enhancing it with features that resonate with my personal trading style and offer additional insights into market behaviour.
In the spirit of Anton's original concept, my indicator incorporates the fundamental idea of "sells before buys" for bullish ranges and "buys before sells" for bearish ranges. This methodological approach is designed to mirror the activities of large market participants who typically offload positions before accumulating again in a bullish context, and accumulate before offloading in a bearish context.
The "ranges" displayed on the chart represent historical and updated highs and lows, reflecting the structural delivery of price across any timeframe. This approach assumes that in a bullish range, the market is likely to sustain upward momentum until it reaches a new high or experiences a significant "sell before buy" scenario, and conversely in a bearish range.
Key Enhancements and Features:
Immediate Break of Structure (BOS) Recognition: This feature promptly updates the high/low to the candle that triggers a BOS, providing a more agile response compared to the original mentfx Structure's approach of waiting for a swing high/low to set the range. This adaptation allows me for quicker adaptation to the market's unfolding narrative.
Market Stage Visualization: By seamlessly integrating with the structure tracking, my indicator presents the current 'Market Stage,' offering a clear stage of the current market's phase, which is crucial for informed trading decisions. The core methodology for determining market stages is derived from the foundational concepts established by mentfx.
Moving Average Integration: The inclusion of a Moving Average (MA) within the indicator adds a layer of trend confirmation, reinforcing decisions based on market structure with established trend analysis techniques. You can use EMA or SMA.
Customizable Session Settings: Tailor the indicator to focus on specific market hours, enhancing its utility for session-based trading strategies and backtesting efficiency.
Triple M: The Triple-M feature is also included in this indicator, which provides a visual representation of the market's momentum and potential reverse.
ATR: Utilizes the Average True Range (ATR) to estimate stop loss levels, providing a data-driven method to manage risk in accordance with current market volatility.
Watermark: Displays the name of the ticker and the current timeframe directly on the chart for easy reference, ensuring clarity and orientation when analyzing multiple instruments or timeframes.
How It Works:
When a range is assigned as being bullish, it will continue updating the high until a new high is created after the bos (= the new high of the range) and will not update or change until a candle's body, open's or close's above it - which will re-update the high and update the low. The low will be updated based on the last time price had a candle (open or closure) below a previous candle low, and then will find the lowest low after the rule was met to assign a low (the idea here is to locate the last major "sell before buy" and showcase that range. And this will occur vice versa, where: when a range is assigned as bearish, it will continue updating the low until a true low is created (=low of the range) and will not update or change until a candle's body, open's or close's below it - which will reupdate the low and update the high. The high will be updated based on the last time price had a candle (open or closure) above a previous candle high, and then will find the highest high after the rule was met to assign a high (once again, the idea being to locate the last major "buy before sell" and showcase price as existing in that range.)
A high is considered as a high that has a lower high to its left and to its right. And a low is considered as a low that has a higher low to its left and to its right. These high and low are used to determine the final high or low of a Bullish or Bearish range (respectively).
Range Determination: The indicator assesses the market momentum and assigns a Bullish or Bearish state based on the most recent directional break.
High/Low Rules Adaptation: In a Bullish range, indicator updates the high if a candle's body, not just the wick, exceeds the current high. This subtle yet significant change allows for a more conservative and potentially more accurate portrayal of bullish sentiment.
Dynamic Updating: As the market evolves, the indicator recalibrates the high and low lines based on the latest price movements, ensuring that you always have the most current and relevant data.
The indicator is not merely a trend-following or scalping tool. It leverages a distinct interpretation of market behavior, focusing on the last major "sell before buy" in Bullish ranges and "buy before sell" in Bearish ranges. By doing so, it aims to pinpoint the true sentiment behind price movements, offering traders a more grounded basis for anticipating market trends.
Of course, a special acknowledgment is due to Anton for his foundational work and the insightful knowledge he's giving day-by-day. The principles of his structure tracking method and market approach have significantly influenced the creation of this indicator, which now carries those insights forward, adapted through the lens of my personal trading philosophy.
GKD-M Baseline Optimizer [Loxx]Giga Kaleidoscope GKD-M Baseline Optimizer is a Metamorphosis module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
The Baseline Optimizer enables traders to backtest over 60 moving averages using variable period inputs. It then exports the baseline with the highest cumulative win rate per candle to any baseline-enabled GKD backtest. To perform the backtesting, the trader selects an initial period input (default is 60) and a skip value that increments the initial period input up to seven times. For instance, if a skip value of 5 is chosen, the Baseline Optimizer will run the backtest for the selected moving average on periods such as 60, 65, 70, 75, and so on, up to 90. If the user selects an initial period input of 45 and a skip value of 2, the Baseline Optimizer will conduct backtests for the chosen moving average on periods like 45, 47, 49, 51, and so forth, up to 57.
The Baseline Optimizer provides a table displaying the output of the backtests for a specified date range. The table output represents the cumulative win rate for the given date range.
On the Metamorphosis side of the Baseline Optimizer, a cumulative backtest is calculated for each candle within the date range. This means that each candle may exhibit a different distribution of period inputs with the highest win rate for a particular moving average. The Baseline Optimizer identifies the period input combination with the highest win rates for long and short positions and creates a win-rate adaptive long and short moving average chart. The moving average used for shorts differs from the moving average used for longs, and the moving average for each candle may vary from any other candle. This customized baseline can then be exported to all baseline-enabled GKD backtests.
The backtest employed in the Baseline Optimizer is a Solo Confirmation Simple, allowing only one take profit and one stop loss to be set.
Lastly, the Baseline Optimizer incorporates Goldie Locks Zone filtering, which can be utilized for signal generation in advanced GKD backtests.
█ Moving Averages included in the Baseline Optimizer
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Kaufman Adaptive Moving Average - KAMA
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
█ Volatility Goldie Locks Zone
The Goldie Locks Zone volatility filter is the standard first-pass filter used in all advanced GKD backtests (Complex, Super Complex, and Full GKd). This filter requires the price to fall within a range determined by multiples of volatility. The Goldie Locks Zone is separate from the core Baseline and utilizes its own moving average with Loxx's Exotic Source Types you can read about below.
On the chart, you will find green and red dots positioned at the top, indicating whether a candle qualifies for a long or short trade respectively. Additionally, green and red triangles are located at the bottom of the chart, signifying whether the trigger has crossed up or down and qualifies within the Goldie Locks zone. The Goldie Locks zone is represented by a white color on the mean line, indicating low volatility levels that are not suitable for trading.
█ Volatility Types Included in the Baseline Optimizer
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user.
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
█ Loxx's Expanded Source Types Included in Baseline Optimizer
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
-Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
-Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
-Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
-Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
-Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full GKD Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Kase Peak Oscillator
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer as shown on the chart above
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest:
GKD-BT Giga Stacks Backtest:
GKD-BT Full Giga Kaleidoscope Backtest:
GKD-BT Solo Confirmation Super Complex Backtest:
GKD-BT Solo Confirmation Complex Backtest:
GKD-BT Solo Confirmation Simple Backtest:
GKD-C Adaptive-Lookback Phase Change Index [Loxx]Giga Kaleidoscope GKD-C Adaptive-Lookback Phase Change Index is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Adaptive-Lookback Phase Change Index
What is the Phase Change Index?
The Phase Change Index (PCI) is a technical indicator that has gained popularity among traders in recent years. It is used to identify market phases and make profitable trades based on momentum and price data. The PCI was developed by M.H. Pee and first introduced in the Stocks & Commodities magazine in 2004.
The PCI is calculated using the 35-day momentum and the 35-day price channel index (PCI). The momentum is the difference between the current day's close and the close 35 days ago, while the PCI measures the distance between the highest high and lowest low over a period of 35 days. By combining these two indicators, traders can identify six possible market phases, each with its own trading strategy.
The formula for calculating the Phase Change Index (PCI) is as follows:
PCI = 100 * (C - L) / (H - L)
Where:
- C is the closing price of the current day
- L is the lowest low over a period of 35 days
- H is the highest high over a period of 35 days
The formula for calculating momentum is as follows:
Momentum = C - Cn
Where:
- C is the closing price of the current day
- Cn is the closing price n days ago, where n = 35 in this case.
The first two phases are characterized by negative momentum, with phase one having a low PCI value (less than 20) and phase two having a high PCI value (greater than 80). In these phases, traders should enter short positions. The next two phases have positive momentum, with phase three having a low PCI value and phase four having a high PCI value. In these phases, traders should enter long positions.
The final two phases are characterized by neutral momentum, with phase five having a low PCI value and phase six having a high PCI value. In these phases, traders should maintain their previous positions until there is a clear signal to enter or exit.
Traders can also use other technical indicators in conjunction with the PCI to confirm signals or filter out false signals. For example, some traders use moving averages or trendlines to confirm trend direction before entering a trade based on the PCI.
In conclusion, the Phase Change Index is a powerful technical indicator that can help traders identify market phases and make profitable trades. By combining momentum and price data, traders can enter long or short positions based on the six possible market phases. Backtesting results have shown that the PCI is robust across parameters, markets, and years. However, it is important to use proper risk management and not rely solely on past profitability when making trading decisions.
What is the Jurik Filter?
The Jurik Filter is a technical analysis tool that is used to filter out market noise and identify trends in financial markets. It was developed by Mark Jurik in the 1990s and is based on a non-linear smoothing algorithm that provides a more accurate representation of price movements.
Traditional moving averages, such as the Simple Moving Average ( SMA ) or Exponential Moving Average ( EMA ), are linear filters that produce a lag between price and the moving average line. This can cause false signals during periods of market volatility , which can result in losses for traders and investors.
The Jurik Filter is designed to address this issue by incorporating a damping factor into the smoothing algorithm. This damping factor adjusts the filter's responsiveness to the changes in price, allowing it to filter out market noise without overshooting price peaks and valleys.
The Jurik Filter is calculated using a mathematical formula that takes into account the current and past prices of an asset, as well as the volatility of the market. This formula incorporates the damping factor and produces a smoother price curve than traditional moving average filters.
One of the advantages of the Jurik Filter is its ability to adjust to changing market conditions. The damping factor can be adjusted to suit different securities and time frames, making it a versatile tool for traders and investors.
Traders and investors often use the Jurik Filter in conjunction with other technical analysis tools, such as the MACD or RSI , to confirm or complement their trading strategies. By filtering out market noise and identifying trends in the financial markets, the Jurik Filter can help improve the accuracy of trading signals and reduce the risks of false signals during periods of market volatility .
Overall, the Jurik Filter is a powerful technical analysis tool that can help traders and investors make more informed decisions about buying and selling securities. By providing a smoother price curve and reducing false signals, it can help improve trading performance and reduce risk in volatile markets.
What is the Adaptive Lookback Period?
The adaptive lookback period is a technique used in technical analysis to adjust the period of an indicator based on changes in market conditions. This technique is particularly useful in volatile or rapidly changing markets where a fixed period may not be optimal for detecting trends or signals.
The concept of the adaptive lookback period is relatively simple. By adjusting the lookback period based on changes in market conditions, traders can more accurately identify trends and signals. This can help traders to enter and exit trades at the right time and improve the profitability of their trading strategies.
The adaptive lookback period works by identifying potential swing points in the market. Once these points are identified, the lookback period is calculated based on the number of swings and a speed parameter. The swing count parameter determines the number of swings that must occur before the lookback period is adjusted. The speed parameter controls the rate at which the lookback period is adjusted, with higher values indicating a more rapid adjustment.
The adaptive lookback period can be applied to a wide range of technical indicators, including moving averages, oscillators, and trendlines. By adjusting the period of these indicators based on changes in market conditions, traders can reduce the impact of noise and false signals, leading to more profitable trades.
In summary, the adaptive lookback period is a powerful technique for traders and analysts looking to optimize their technical indicators. By adjusting the period based on changes in market conditions, traders can more accurately identify trends and signals, leading to more profitable trades. While there are various ways to implement the adaptive lookback period, the basic concept remains the same, and traders can adapt and customize the technique to suit their individual needs and trading styles.
What is the Adaptive-Lookback Phase Change Index?
The combination of adaptive lookback and Jurik filtering is an effective technique used in technical analysis to filter out market noise and improve the accuracy of trading signals. When applied to the Phase Change Index (PCI) indicator, the adaptive lookback period can be used to adjust the period of the indicator based on changes in market conditions. Jurik filtering can then be used to filter out market noise and improve the accuracy of the signals produced by the PCI indicator.
The adaptive lookback period is particularly useful in volatile or rapidly changing markets where a fixed period may not be optimal for detecting trends or signals. By adjusting the lookback period based on changes in market conditions, traders can more accurately identify trends and signals, leading to more profitable trades.
Jurik filtering is a more advanced filtering technique that uses a combination of smoothing and phase shift to produce a more accurate signal. This technique is particularly useful in filtering out market noise and improving the accuracy of trading signals. Jurik filtering can be applied to various indicators, including moving averages, oscillators, and trendlines.
Overall, the combination of adaptive lookback and Jurik filtering is a powerful technique used in technical analysis to filter out market noise and improve the accuracy of trading signals. When applied to the Phase Change Index (PCI) indicator, this technique is particularly effective in identifying trend changes and producing more accurate signals for entry and exit points in trading strategies.
Keep in mind, this is an inverse indicator meaning that above the middle-line/signal is short, below is long.
Additional Features
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
It's important to note that, like any other technical analysis tool, Heiken Ashi "better" candles are not foolproof and should be used in conjunction with other indicators and analysis techniques to make well-informed trading decisions.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Adaptive-Lookback Phase Change Index as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
Market Structure & Liquidity: CHoCHs+Nested Pivots+FVGs+Sweeps//Purpose:
This indicator combines several tools to help traders track and interpret price action/market structure; It can be divided into 4 parts;
1. CHoCHs, 2. Nested Pivot highs & lows, 3. Grade sweeps, 4. FVGs.
This gives the trader a toolkit for determining market structure and shifts in market structure to help determine a bull or bear bias, whether it be short-term, med-term or long-term.
This indicator also helps traders in determining liquidity targets: wether they be voids/gaps (FVGS) or old highs/lows+ typical sweep distances.
Finally, the incorporation of HTF CHoCH levels printing on your LTF chart helps keep the bigger picture in mind and tells traders at a glance if they're above of below Custom HTF CHoCH up or CHoCH down (these HTF CHoCHs can be anything from Hourly up to Monthly).
//Nomenclature:
CHoCH = Change of Character
STH/STL = short-term high or low
MTH/MTL = medium-term high or low
LTH/LTL = long-term high or low
FVG = Fair value gap
CE = consequent encroachement (the midline of a FVG)
~~~ The Four components of this indicator ~~~
1. CHoCHs:
•Best demonstrated in the below charts. This was a method taught to me by @Icecold_crypto. Once a 3 bar fractal pivot gets broken, we count backwards the consecutive higher lows or lower highs, then identify the CHoCH as the opposite end of the candle which ended the consecutive backwards count. This CHoCH (UP or DOWN) then becomes a level to watch, if price passes through it in earnest a trader would consider shifting their bias as market structure is deemed to have shifted.
•HTF CHoCHs: Option to print Higher time frame chochs (default on) of user input HTF. This prints only the last UP choch and only the last DOWN choch from the input HTF. Solid line by default so as to distinguish from local/chart-time CHoCHs. Can be any Higher timeframe you like.
•Show on table: toggle on show table(above/below) option to show in table cells (top right): is price above the latest HTF UP choch, or is price below HTF DOWN choch (or is it sat between the two, in a state of 'uncertainty').
•Most recent CHoCHs which have not been met by price will extend 10 bars into the future.
• USER INPUTS: overall setting: SHOW CHOCHS | Set bars lookback number to limit historical Chochs. Set Live CHoCHs number to control the number of active recent chochs unmet by price. Toggle shrink chochs once hit to declutter chart and minimize old chochs to their origin bars. Set Multi-timeframe color override : to make Color choices auto-set to your preference color for each of 1m, 5m, 15m, H, 4H, D, W, M (where up and down are same color, but 'up' icon for up chochs and down icon for down chochs remain printing as normal)
2. Nested Pivot Highs & Lows; aka 'Pivot Highs & Lows (ST/MT/LT)'
•Based on a seperate, longer lookback/lookforward pivot calculation. Identifies Pivot highs and lows with a 'spikeyness' filter (filtering out weak/rounded/unimpressive Pivot highs/lows)
•by 'nested' I mean that the pivot highs are graded based on whether a pivot high sits between two lower pivot highs or vice versa.
--for example: STH = normal pivot. MTH is pivot high with a lower STH on either side. LTH is a pivot high with a lower MTH on either side. Same applies to pivot lows (STL/MTL/LTL)
•This is a useful way to measure the significance of a high or low. Both in terms of how much it might be typically swept by (see later) and what it would imply for HTF bias were we to break through it in earnest (more than just a sweep).
• USER INPUTS: overall setting: show pivot highs & lows | Bars lookback (historical pivots to show) | Pivots: lookback/lookforward length (determines the scale of your pivot highs/lows) | toggle on/off Apply 'Spikeyness' filter (filters out smooth/unimpressive pivot highs/lows). Set Spikeyness index (determines the strength of this filter if turned on) | Individually toggle on each of STH, MTH, LTH, STL, MTL, LTL along with their label text type , and size . Toggle on/off line for each of these Pivot highs/lows. | Set label spacer (atr multiples above / below) | set line style and line width
3. Grade Sweeps:
•These are directly related to the nested pivots described above. Most assets will have a typical sweep distance. I've added some of my expected sweeps for various assets in the indicator tooltips.
--i.e. Eur/Usd 10-20-30 pips is a typical 'grade' sweep. S&P HKEX:5 - HKEX:10 is a typical grade sweep.
•Each of the ST/MT/LT pivot highs and lows have optional user defined grade sweep boxes which paint above until filled (or user option for historical filled boxes to remain).
•Numbers entered into sweep input boxes are auto converted into appropriate units (i.e. pips for FX, $ or 'handles' for indices, $ for Crypto. Very low $ units can be input for low unit value crypto altcoins.
• USER INPUTS: overall setting: Show sweep boxes | individually select colors of each of STH, MTH, LTH, STL, MTL, LTL sweep boxes. | Set Grade sweep ($/pips) number for each of ST, MT, LT. This auto converts between pips and $ (i.e. FX vs Indices/Crypto). Can be a float as small or large as you like ($0.000001 to HKEX:1000 ). | Set box text position (horizontal & vertical) and size , and color . | Set Box width (bars) (for non extended/ non-auto-terminating at price boxes). | toggle on/off Extend boxes/lines right . | Toggle on/off Shrink Grade sweeps on fill (they will disappear in realtime when filled/passed through)
4. FVGs:
•Fair Value gaps. Represent 'naked' candle bodies where the wicks to either side do not meet, forming a 'gap' of sorts which has a tendency to fill, or at least to fill to midline (CE).
•These are ICT concepts. 'UP' FVGS are known as BISIs (Buyside imbalance, sellside inefficiency); 'DOWN' FVGs are known as SIBIs (Sellside imbalance, buyside inefficiency).
• USER INPUTS: overall setting: show FVGs | Bars lookback (history). | Choose to display: 'UP' FVGs (BISI) and/or 'DOWN FVGs (SIBI) . Choose to display the midline: CE , the color and the line style . Choose threshold: use CE (as opposed to Full Fill) |toggle on/off Shrink FVG on fill (CE hit or Full fill) (declutter chart/see backtesting history)
////••Alerts (general notes & cautionary notes)::
•Alerts are optional for most of the levels printed by this indicator. Set them via the three dots on indicator status line.
•Due to dynamic repainting of levels, alerts should be used with caution. Best use these alerts either for Higher time frame levels, or when closely monitoring price.
--E.g. You may set an alert for down-fill of the latest FVG below; but price will keep marching up; form a newer/higher FVG, and the alert will trigger on THAT FVG being down-filled (not the original)
•Available Alerts:
-FVG(BISI) cross above threshold(CE or full-fill; user choice). Same with FVG(SIBI).
-HTF last CHoCH down, cross below | HTF last CHoCH up, cross above.
-last CHoCH down, cross below | last CHoCH up, cross above.
-LTH cross above, MTH cross above, STH cross above | LTL cross below, MTL cross below, STL cross below.
////••Formatting (general)::
•all table text color is set from the 'Pivot highs & Lows (ST, MT, LT)' section (for those of you who prefer black backgrounds).
•User choice of Line-style, line color, line width. Same with Boxes. Icon choice for chochs. Char or label text choices for ST/MT/LT pivot highs & lows.
////••User Inputs (general):
•Each of the 4 components of this indicator can be easily toggled on/off independently.
•Quite a lot of options and toggle boxes, as described in full above. Please take your time and read through all the tooltips (hover over '!' icon) to get an idea of formatting options.
•Several Lookback periods defined in bars to control how much history is shown for each of the 4 components of this indicator.
•'Shrink on fill' settings on FVGs and CHoCHs: Basically a way to declutter chart; toggle on/off depending on if you're backtesting or reading live price action.
•Table Display: applies to ST/MT/LT pivot highs and to HTF CHoCHs; Toggle table on or off (in part or in full)
////••Credits:
•Credit to ICT (Inner Circle Trader) for some of the concepts used in this indicator (FVGS & CEs; Grade sweeps).
•Credit to @Icecold_crypto for the specific and novel concept of identifying CHoCHs in a simple, objective and effective manner (as demonstrated in the 1st chart below).
CHoCH demo page 1: shifting tweak; arrow diagrams to demonstrate how CHoCHs are defined:
CHoCH demo page 2: Simplified view; short lookback history; few CHoCHs, demo of 'latest' choch being extended into the future by 10 bars:
USAGE: Bitcoin Hourly using HTF daily CHoCHs:
USAGE-2: Cotton Futures (CT1!) 2hr. Painting a rather bullish picture. Above HTF UP CHoCH, Local CHoCHs show bullish order flow, Nice targets above (MTH/LTH + grade sweeps):
Full Demo; 5min chart; CHoCHs, Short term pivot highs/lows, grade sweeps, FVGs:
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias (part A):
Full Demo, Eur/Usd 15m: STH, MTH, LTH grade sweeps, CHoCHs, Usage for finding bias, 3hrs later (part B):
Realtime Vs Backtesting(A): btc/usd 15m; FVGs and CHoCHs: shrink on fill, once filled they repaint discreetly on their origin bar only. Realtime (Shrink on fill, declutter chart):
Realtime Vs Backtesting(B): btc/usd 15m; FVGs and CHoCHs: DON'T shrink on fill; they extend to the point where price crosses them, and fix/paint there. Backtesting (seeing historical behaviour):
GKD-C Super 6x [Loxx]Giga Kaleidoscope GKD-C Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ GKD-C Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity
What is MACD?
MACD stands for Moving Average Convergence Divergence. It is a technical indicator used in financial analysis to track the trend and momentum of a security or market index. The MACD indicator consists of two lines, a faster-moving average called the MACD line, and a slower-moving average called the signal line.
The MACD line is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA. The signal line is a 9-period EMA of the MACD line. The MACD line oscillates above and below the zero line, which represents the equilibrium point between the bullish and bearish forces.
Traders use the MACD indicator to identify changes in trend and momentum. When the MACD line crosses above the signal line, it is considered a bullish signal, indicating that the momentum is shifting towards the upside. Conversely, when the MACD line crosses below the signal line, it is considered a bearish signal, indicating that the momentum is shifting towards the downside.
The MACD indicator can also be used to identify divergences between the MACD line and the price action. A bullish divergence occurs when the price is making lower lows, but the MACD line is making higher lows. This could indicate that the downward momentum is weakening, and a potential trend reversal could be imminent. A bearish divergence occurs when the price is making higher highs, but the MACD line is making lower highs, indicating that the upward momentum is weakening, and a potential trend reversal could be imminent.
Overall, the MACD indicator is a versatile tool that can be used in conjunction with other technical indicators and chart patterns to make informed trading decisions.
What is CCI?
The Commodity Channel Index ( CCI ) is a technical analysis indicator that was developed by Donald Lambert in 1980. It's primarily used to identify overbought and oversold conditions in the market, as well as trend direction and potential price reversals.
The CCI is calculated by taking the difference between the typical price (the average of the high, low, and close prices) and a moving average of the typical price over a certain period of time. This difference is then divided by a factor based on the average deviation of the typical price from the moving average.
The formula for the CCI is:
CCI = (Typical Price - 20-period SMA of Typical Price) / (0.015 x Mean Deviation)
Where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average
Mean Deviation = Average of the absolute value of the difference between the Typical Price and the SMA over the last 20 periods.
The CCI is usually displayed as a line chart that oscillates around a centerline of zero. Readings above zero indicate that the typical price is above the moving average, while readings below zero indicate that the typical price is below the moving average.
Traders typically use the CCI to identify overbought and oversold conditions in the market. When the CCI rises above a certain level (e.g., +100), it's considered overbought, indicating that the price may be due for a correction or reversal. When the CCI falls below a certain level (e.g., -100), it's considered oversold, indicating that the price may be due for a bounce or reversal.
The CCI can also be used to identify potential trend reversals. When the CCI crosses above or below the zero line, it can signal a potential change in trend. For example, if the CCI crosses above the zero line, it could indicate that a bullish trend is emerging, while a cross below the zero line could indicate that a bearish trend is emerging.
Overall, the Commodity Channel Index is a useful technical analysis tool for identifying overbought and oversold conditions, as well as potential trend reversals in the market. However, like all technical indicators, it should be used in conjunction with other forms of analysis and risk management techniques to make informed trading decisions.
What is RSI?
The RSI, or Relative Strength Index, is a popular technical analysis tool used to measure the strength of a security's price action and identify potential trend reversals. It was developed by J. Welles Wilder and is based on the concept that price action tends to follow a momentum pattern.
The RSI is calculated based on the average gain and loss of a security's price over a specified period, usually 14 periods. It oscillates between 0 and 100 and is represented as a single line on a chart.
The RSI is calculated as follows:
RS = Average Gain / Average Loss
RSI = 100 - (100 / (1 + RS))
Where the Average Gain is the sum of all gains divided by the number of periods, and the Average Loss is the sum of all losses divided by the number of periods.
The RSI is used to identify overbought and oversold conditions in a security or market index. When the RSI rises above 70, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the RSI falls below 30, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the RSI to identify potential trend reversals. When the RSI forms a divergent pattern with the price action, it could indicate that the security is losing momentum and may be reversing to the upside or downside.
Overall, the RSI is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Stochastic?
The stochastic oscillator is a momentum indicator used in technical analysis to measure the current closing price of a security or market index relative to its price range over a specified period. The indicator consists of two lines, the %K line and the %D line, which oscillate between 0 and 100.
The %K line is calculated as follows:
%K = 100 x (Closing Price - Lowest Low) / (Highest High - Lowest Low)
Where:
Closing Price is the most recent closing price of the security.
Lowest Low is the lowest low of the security over a specified period (usually 14 periods).
Highest High is the highest high of the security over the same specified period.
The %D line is a 3-period simple moving average of the %K line. The %D line is slower than the %K line and is used to smooth out the volatility of the %K line.
The stochastic oscillator is used to identify overbought and oversold conditions in a security or market index. When the %K line rises above 80, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the %K line falls below 20, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the stochastic oscillator to identify bullish and bearish divergences between the %K line and the price action. A bullish divergence occurs when the %K line is making higher lows while the price action is making lower lows, indicating that the momentum is shifting towards the upside. A bearish divergence occurs when the %K line is making lower highs while the price action is making higher highs, indicating that the momentum is shifting towards the downside.
Overall, the stochastic oscillator is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Loxxer?
The Loxxer Index is a technical indicator used in financial analysis to identify potential trend reversals and overbought/oversold conditions in a security or market index. It was developed by Loxx and is also known as the Loxx Indicator.
The Loxxer Index is calculated based on the high, low, and closing prices of a security over a specified period. It measures the demand for the security by comparing the current high and low prices with the previous high and low prices. The indicator oscillates between 0 and 1 and is represented as a single line on a chart.
The Loxxer Index is calculated as follows:
LoxxMax = Current High - Previous High
LoxxMin = Previous Low - Current Low
If LoxxMax is greater than LoxxMin, then the Loxxer Index is calculated as follows:
Loxxer = LoxxMax / (LoxxMax + Current Close - Previous Close)
If LoxxMax is less than or equal to LoxxMin, then the Loxxer Index is calculated as follows:
Loxxer = 0
The Loxxer Index is used to identify overbought and oversold conditions in a security or market index. When the Loxxer Index rises above 0.7, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the Loxxer Index falls below 0.3, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the Loxxer Index to identify potential trend reversals. When the Loxxer Index forms a higher low while the price action forms a lower low, it could indicate that the security is losing momentum and may be reversing to the upside. Conversely, when the Loxxer Index forms a lower high while the price action forms a higher high, it could indicate that the security is losing momentum and may be reversing to the downside.
Overall, the Loxxer Index is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Velocity?
The Velocity Indicator is a technical analysis tool used to measure the speed and momentum of price movements in a security or market index. It is a type of oscillator that is used to identify potential trend reversals and overbought/oversold conditions.
The Velocity Indicator is calculated based on the difference between the current price and the price from a specified number of periods ago. It measures the rate of change of the price movement over time and is represented as a single line on a chart.
The Velocity Indicator is calculated as follows:
Velocity = (Current Price - Price from N periods ago) / Price from N periods ago x 100
Where N is the number of periods used in the calculation.
The Velocity Indicator is used to identify overbought and oversold conditions in a security or market index. When the Velocity Indicator rises above 1, it is considered overbought, indicating that the security may be overvalued and due for a price correction. Conversely, when the Velocity Indicator falls below -1, it is considered oversold, indicating that the security may be undervalued and due for a price rebound.
Traders can also use the Velocity Indicator to identify potential trend reversals. When the Velocity Indicator crosses above its moving average, it could indicate that the security is gaining momentum and may be reversing to the upside. Conversely, when the Velocity Indicator crosses below its moving average, it could indicate that the security is losing momentum and may be reversing to the downside.
Overall, the Velocity Indicator is a useful tool for traders to identify potential buy and sell signals, as well as to confirm trends and reversals. However, it should not be used in isolation, and traders should consider using other technical indicators and fundamental analysis to make informed trading decisions.
What is Super 6x: RSI, MACD, Stochastic, Loxxer, CCI, & Velocity?
Super 6x combines all 6 indicators into one signal, long or short
Requirements
Inputs
Confirmation 1 and Solo Confirmation: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Outputs
Confirmation 2 and Solo Confirmation Complex: GKD-E Exit indicator
Confirmation 1: GKD-C Confirmation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest strategy
Additional features will be added in future releases.
Double Candle Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed double candle trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
Double Candle Trends
• A double uptrend candle trend is formed when a candle closes with both a higher high and a higher low.
• A double downtrend candle trend is formed when a candle closes with both a lower high and a lower low.
Multi-Part Double Candle Trends
• A multi-part double uptrend candle trend begins with the formation of a new double uptrend candle trend and continues until a new lower high or lower low ends the trend.
• A multi-part double downtrend candle trend begins with the formation of a new double downtrend candle trend and continues until a new higher high or higher low ends the trend.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
• Show Plots
Table
The table is colour coded, consists of seven columns and, as many as, thirty-two rows. Blue cells denote the multi-part trend scenarios, green cells denote the corresponding double uptrend candle trend scenarios and red cells denote the corresponding double downtrend candle trend scenarios.
The multi-part double candle trend scenarios are listed in the first column with their corresponding total counts to the right, in the second and fifth columns. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third and sixth columns display the double candle trend scenarios as percentages of total 1-part double candle trends. And columns four and seven display the total double candle trend scenarios as percentages of the last, or preceding double candle trend part. For example 4-part double uptrend candle trends as percentages of 3-part double uptrend candle trends.
Plots
I have added plots as a visual aid to the double candle trend scenarios. Green up-arrows, with the number of the trend part, denote double uptrend candle trends. Red down-arrows, with the number of the trend part, denote double downtrend candle trends.
█ HOW TO USE
This indicator is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the current double candle trend will continue or fail, based on the current trend scenario and what has happened in the past under similar circumstances. Such information can be useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Upper and Lower Candle Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed upper and lower candle trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
Table
The table is colour coded, consists of seven columns and, as many as, sixty-two rows. Blue cells denote the multi-part trend scenarios, green cells denote the corresponding upper candle trend scenarios and red cells denote the corresponding lower candle trend scenarios.
The multi-part candle trend scenarios are listed in the first column with their corresponding total counts to the right, in the second and fifth columns. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third and sixth columns display the candle trend scenarios as percentages of total 1-part candle trends. And columns four and seven display the total candle trend scenarios as percentages of the last, or preceding candle trend part. For example 4-part higher high trends as a percentages of 3-part higher high trends. This offers more insight into what might happen next at any given point in time.
Plots
For a visual aid to this indicator please use in conjunction with my Upper Candle Trends and Lower Candle Trends indicators which can both be found on my profile page under scripts, or in community scripts under the same names.
Green up-arrows, with the number of the trend part, denote higher high trends when above bar and higher low trends when below bar. Red down-arrows, with the number of the trend part, denote lower high trends when above bar and lower low trends when below bar.
█ HOW TO USE
This is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the current upper or lower candle trend will continue or fail, based on the current trend scenario and what has happened in the past under similar circumstances. Such information can be useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Parallel Projections [theEccentricTrader]█ OVERVIEW
This indicator automatically projects parallel trendlines or channels, from a single point of origin. In the example above I have applied the indicator twice to the 1D SPXUSD. The five upper lines (green) are projected at an angle of -5 from the 1-month swing high anchor point with a projection ratio of -72. And the seven lower lines (blue) are projected at an angle of 10 with a projection ratio of 36 from the 1-week swing low anchor point.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Trendlines
Trendlines are straight lines that are drawn between two or more points on a price chart. These lines are used as dynamic support and resistance levels for making strategic decisions and predictions about future price movements. For example traders will look for price movements along, and reactions to, trendlines in the form of rejections or breakouts/downs.
█ FEATURES
Inputs
• Anchor Point Type
• Swing High/Low Occurrence
• HTF Resolution
• Highest High/Lowest Low Lookback
• Angle Degree
• Projection Ratio
• Number Lines
• Line Color
Anchor Point Types
• Swing High
• Swing Low
• Swing High (HTF)
• Swing Low (HTF)
• Highest High
• Lowest Low
• Intraday Highest High (intraday charts only)
• Intraday Lowest Low (intraday charts only)
Swing High/Swing Low Occurrence
This input is used to determine which historic peak or trough to reference for swing high or swing low anchor point types.
HTF Resolution
This input is used to determine which higher timeframe to reference for swing high (HTF) or swing low (HTF) anchor point types.
Highest High/Lowest Low Lookback
This input is used to determine the lookback length for highest high or lowest low anchor point types.
Intraday Highest High/Lowest Low Lookback
When using intraday highest high or lowest low anchor point types, the lookback length is calculated automatically based on number of bars since the daily candle opened.
Angle Degree
This input is used to determine the angle of the trendlines. The output is expressed in terms of point or pips, depending on the symbol type, which is then passed through the built in math.todegrees() function. Positive numbers will project the lines upwards while negative numbers will project the lines downwards. Depending on the market and timeframe, the impact input values will have on the visible gaps between the lines will vary greatly. For example, an input of 10 will have a far greater impact on the gaps between the lines when viewed from the 1-minute timeframe than it would on the 1-day timeframe. The input is a float and as such the value passed through can go into as many decimal places as the user requires.
It is also worth mentioning that as more lines are added the gaps between the lines, that are closest to the anchor point, will get tighter as they make their way up the y-axis. Although the gaps between the lines will stay constant at the x2 plot, i.e. a distance of 10 points between them, they will gradually get tighter and tighter at the point of origin as the slope of the lines get steeper.
Projection Ratio
This input is used to determine the distance between the parallels, expressed in terms of point or pips. Positive numbers will project the lines upwards while negative numbers will project the lines downwards. Depending on the market and timeframe, the impact input values will have on the visible gaps between the lines will vary greatly. For example, an input of 10 will have a far greater impact on the gaps between the lines when viewed from the 1-minute timeframe than it would on the 1-day timeframe. The input is a float and as such the value passed through can go into as many decimal places as the user requires.
Number Lines
This input is used to determine the number of lines to be drawn on the chart, maximum is 500.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
If the lines do not draw or you see a study error saying that the script references too many candles in history, this is most likely because the higher timeframe anchor point is not present on the current timeframe. This problem usually occurs when referencing a higher timeframe, such as the 1-month, from a much lower timeframe, such as the 1-minute. How far you can lookback for higher timeframe anchor points on the current timeframe will also be limited by your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000.
█ RAMBLINGS
It is my current thesis that the indicator will work best when used in conjunction with my Wavemeter indicator, which can be used to set the angle and projection ratio. For example, the average wave height or amplitude could be used as the value for the angle and projection ratio inputs. Or some factor or multiple of such an average. I think this makes sense as it allows for objectivity when applying the indicator across different markets and timeframes with different energies and vibrations.
“If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.”
― Nikola Tesla
Fan Projections [theEccentricTrader]█ OVERVIEW
This indicator automatically projects trendlines in the shape of a fan, from a single point of origin. In the example above I have applied the indicator twice to the 1D SPXUSD. The seven upper lines (green) are projected at an angle of -5 from the 1-month swing high anchor point. And the five lower lines (blue) are projected at an angle of 10 from the 1-week swing low anchor point.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Trendlines
Trendlines are straight lines that are drawn between two or more points on a price chart. These lines are used as dynamic support and resistance levels for making strategic decisions and predictions about future price movements. For example traders will look for price movements along, and reactions to, trendlines in the form of rejections or breakouts/downs.
█ FEATURES
Inputs
• Anchor Point Type
• Swing High/Low Occurrence
• HTF Resolution
• Highest High/Lowest Low Lookback
• Angle Degree
• Number Lines
• Line Color
Anchor Point Types
• Swing High
• Swing Low
• Swing High (HTF)
• Swing Low (HTF)
• Highest High
• Lowest Low
• Intraday Highest High (intraday charts only)
• Intraday Lowest Low (intraday charts only)
Swing High/Swing Low Occurrence
This input is used to determine which historic peak or trough to reference for swing high or swing low anchor point types.
HTF Resolution
This input is used to determine which higher timeframe to reference for swing high (HTF) or swing low (HTF) anchor point types.
Highest High/Lowest Low Lookback
This input is used to determine the lookback length for highest high or lowest low anchor point types.
Intraday Highest High/Lowest Low Lookback
When using intraday highest high or lowest low anchor point types, the lookback length is calculated automatically based on number of bars since the daily candle opened.
Angle Degree
This input is used to determine the angle of the trendlines. The output is expressed in terms of point or pips, depending on the symbol type, which is then passed through the built in math.todegrees() function. Positive numbers will project the lines upwards while negative numbers will project the lines downwards. Depending on the market and timeframe, the impact input values will have on the visible gaps between the lines will vary greatly. For example, an input of 10 will have a far greater impact on the gaps between the lines when viewed from the 1-minute timeframe than it would on the 1-day timeframe. The input is a float and as such the value passed through can go into as many decimal places as the user requires.
It is also worth mentioning that as more lines are added the gaps between the lines, that are closest to the anchor point, will get tighter as they make their way up the y-axis. Although the gaps between the lines will stay constant at the x2 plot, i.e. a distance of 10 points between them, they will gradually get tighter and tighter at the point of origin as the slope of the lines get steeper.
Number Lines
This input is used to determine the number of lines to be drawn on the chart, maximum is 500.
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
If the lines do not draw or you see a study error saying that the script references too many candles in history, this is most likely because the higher timeframe anchor point is not present on the current timeframe. This problem usually occurs when referencing a higher timeframe, such as the 1-month, from a much lower timeframe, such as the 1-minute. How far you can lookback for higher timeframe anchor points on the current timeframe will also be limited by your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000.
█ RAMBLINGS
It is my current thesis that the indicator will work best when used in conjunction with my Wavemeter indicator, which can be used to set the angle. For example, the average wave height or amplitude could be used as the value for the angle input. Or some factor or multiple of such an average. I think this makes sense as it allows for objectivity when applying the indicator across different markets and timeframes with different energies and vibrations.
“If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.”
― Nikola Tesla
Swing Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed swing high and swing low scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Peak and Trough Prices (Advanced)
• The advanced peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the highest preceding green candle high price, depending on which is higher.
• The advanced trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the lowest preceding red candle low price, depending on which is lower.
Green and Red Peaks and Troughs
• A green peak is one that derives its price from the green candle/s that constitute the swing high.
• A red peak is one that derives its price from the red candle that completes the swing high.
• A green trough is one that derives its price from the green candle that completes the swing low.
• A red trough is one that derives its price from the red candle/s that constitute the swing low.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
• Show Sample Period
• Show Plots
• Show Lines
Table
The table is colour coded, consists of three columns and nine rows. Blue cells denote neutral scenarios, green cells denote return line uptrend and uptrend scenarios, and red cells denote downtrend and return line downtrend scenarios.
The swing scenarios are listed in the first column with their corresponding total counts to the right, in the second column. The last row in column one, row nine, displays the sample period which can be adjusted or hidden via indicator settings.
Rows three and four in the third column of the table display the total higher peaks and higher troughs as percentages of total peaks and troughs, respectively. Rows five and six in the third column display the total lower peaks and lower troughs as percentages of total peaks and troughs, respectively. And rows seven and eight display the total double-top peaks and double-bottom troughs as percentages of total peaks and troughs, respectively.
Plots
I have added plots as a visual aid to the swing scenarios listed in the table. Green up-arrows with ‘HP’ denote higher peaks, while green up-arrows with ‘HT’ denote higher troughs. Red down-arrows with ‘LP’ denote higher peaks, while red down-arrows with ‘LT’ denote lower troughs. Similarly, blue diamonds with ‘DT’ denote double-top peaks and blue diamonds with ‘DB’ denote double-bottom troughs. These plots can be hidden via indicator settings.
Lines
I have also added green and red trendlines as a further visual aid to the swing scenarios listed in the table. Green lines denote return line uptrends (higher peaks) and uptrends (higher troughs), while red lines denote downtrends (lower peaks) and return line downtrends (lower troughs). These lines can be hidden via indicator settings.
█ HOW TO USE
This indicator is intended for research purposes and strategy development. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe. It can, for example, give you an idea of any inherent biases such as a greater proportion of higher peaks to lower peaks. Or a greater proportion of higher troughs to lower troughs. Such information can be very useful when conducting top down analysis across multiple timeframes, or considering entry and exit methods.
What I find most fascinating about this logic, is that the number of swing highs and swing lows will always find equilibrium on each new complete wave cycle. If for example the chart begins with a swing high and ends with a swing low there will be an equal number of swing highs to swing lows. If the chart starts with a swing high and ends with a swing high there will be a difference of one between the two total values until another swing low is formed to complete the wave cycle sequence that began at start of the chart. Almost as if it was a fundamental truth of price action, although quite common sensical in many respects. As they say, what goes up must come down.
The objective logic for swing highs and swing lows I hope will form somewhat of a foundational building block for traders, researchers and developers alike. Not only does it facilitate the objective study of swing highs and swing lows it also facilitates that of ranges, trends, double trends, multi-part trends and patterns. The logic can also be used for objective anchor points. Concepts I will introduce and develop further in future publications.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
The sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
█ NOTES
I feel it important to address the mention of advanced peak and trough price logic. While I have introduced the concept, I have not included the logic in my script for a number of reasons. The most pertinent of which being the amount of extra work I would have to do to include it in a public release versus the actual difference it would make to the statistics. Based on my experience, there are actually only a small number of cases where the advanced peak and trough prices are different from the basic peak and trough prices. And with adequate multi-timeframe analysis any high or low prices that are not captured using basic peak and trough price logic on any given time frame, will no doubt be captured on a higher timeframe. See the example below on the 1H FOREXCOM:USDJPY chart (Figure 1), where the basic peak price logic denoted by the indicator plot does not capture what would be the advanced peak price, but on the 2H FOREXCOM:USDJPY chart (Figure 2), the basic peak logic does capture the advanced peak price from the 1H timeframe.
Figure 1.
Figure 2.
█ RAMBLINGS
“Never was there an age that placed economic interests higher than does our own. Never was the need of a scientific foundation for economic affairs felt more generally or more acutely. And never was the ability of practical men to utilize the achievements of science, in all fields of human activity, greater than in our day. If practical men, therefore, rely wholly on their own experience, and disregard our science in its present state of development, it cannot be due to a lack of serious interest or ability on their part. Nor can their disregard be the result of a haughty rejection of the deeper insight a true science would give into the circumstances and relationships determining the outcome of their activity. The cause of such remarkable indifference must not be sought elsewhere than in the present state of our science itself, in the sterility of all past endeavours to find its empirical foundations.” (Menger, 1871, p.45).
█ BIBLIOGRAPHY
Menger, C. (1871) Principles of Economics. Reprint, Auburn, Alabama: Ludwig Von Mises Institute: 2007.
Black RSI (Pro Suite)Black RSI (Pro Suite) is combination of RSI (Relative Strength Index), Volume RSI, Heikin Ashi RSI & other multi Oscillators with multi features into one indicator, features like (Quad Divergences, Multi Time Frame RSI, MTF RSI Panel, Oscillator Support/Resistance/Wedges/Trendlines, Oscillator Moving Average/BBs, Smooth RSI, RSI Price Estimator, Oscillator Over bought/sold Bars, Osc OB/OS Zones, Osc OB/OS Highlights, additionally Black RSI indicator is flexible & completely customizable).
Indicator goal: I have tried my best to organized RSI & other suitable oscillators and oscillator useful tools into one simple and free indicator for Tradingview users (specifically for Tradingview 'basic' subscription users). suggestions are always welcome. please give feedback & appreciate if you like my work.
Black RSI Indicator Features Summary:
Black RSI indicator includes many features mainly relevant to RSI and other Oscillators, these are briefly highlighted below:
Black RSI Dashboard
Multi Oscillators: Choose between multiple oscillators. All oscillators settings are customizable.
Multi Symbol: Multi Symbol Support, applicable on all oscillators
RSI (Relative Strength Index)
VRSI (Volume Relative Strength Index)
HA RSI (Heikin Ashi Relative Strength Index)
OBV (On Balance Volume)
CVD (Comulative Volume Delta)
MFI (Money Flow Index)
UO (Ultimate Oscillator)
MOM (Momentum Oscillator)
ATR (Average True Range)
Stoch (Stochastic Oscillator)
Stoch RSI (Stochastic RSI)
Oscillator Primary Tools ◢
Oscillator Moving Average/Bollinger Bands
Smooth RSI
Multi Timeframe RSI
Multi Timeframe RSI Panel
RSI Price Estimator
Oscillator Support/Resistance/Wedges/Trendlines
Oscillator Moving Average/BBs: Shows Moving Average for selected oscillator.
Smooth Smooth: Smooths out RSI
Multi Timeframe RSI: Displays Multiple Time Frame/Multiple Symbol RSI and converts it and shows it as it is in current time frame without effecting Primary RSI
Multi Timeframe RSI Panel: Displays Multiple Time Frame/Multiple Symbol RSI values of user input specific timeframes in compact panel (max 8 Time frames)
RSI Price Estimator: Calculates RSI estimate price values of 3 different user specific RSI input levels, RSI x MA cross price and RSI future value of user specific price input level.
Oscillator Support/Resistance/Wedges/Trendlines: Draws Trendlines, Wedges and Support & Resistance lines on selected oscillator
Oscillator Quad Divergence ◢
1st Oscillator Divergence: Traditional divergence indicator with enhancements & customization
2nd Oscillator Divergence: Traditional divergence indicator with enhancements & customization
3rd Oscillator Divergence: Advanced Divergence indicator with source selection, RSI/Price threshold, potential divergences & customization
4th Oscillator Divergence: Pivots divergence indicator with flexible pivots selection & customization
Regular bullish divergences are indicated when price is forming lower lows while an oscillator shows higher lows.
Regular bearish divergences are indicated when price is forming higher highs while an oscillator shows lower highs.
While regular divergences indicate trend reversals, hidden divergences indicate a trend continuation.
When the price is making higher lows and the oscillator is showing lower lows, we speak of a bullish hidden divergence.
When the price is making lower highs and the oscillator shows higher highs, it's a bearish hidden divergence.
Oscillator Secondary Tools ◢
Oscillator HH/LL pivots
Osc OB/OS Color Bars
Osc OB/OS Zones
Osc OB/OS Highlights
Background
Oscillator HH/LL pivots: Shows HH/LL pivot points on selected oscillator
Osc OB/OS Color Bars: Plots color chart bars based on RSI, MFI, Stochastic, Stochastic RSI or combine overbought/oversold conditions
Osc OB/OS Zones: Plots Osc OB/OS Zones with user input levels
Osc OB/OS Highlights: Highlight oscillator OB/OS background area
Background: background color customization
+ Primary RSI Settings ▾
- Primary RSI Length: User input RSI Length value
- Primary RSI Source: User RSI Source selection
- RSI Overbought Threshold: Allows the user to set the RSI overbought threshold value. This Overbought Threshold value will also be applied on "RSI Divergence overbought condition", "RSI OB Color Bars" and "Primary RSI Color Schemes
- RSI Oversold Threshold: Allows the user to set the RSI oversold threshold value. The lower band (oversold line) of RSI. This Oversold Threshold value will also be applied on "RSI Divergence oversold condition", "RSI OS Color Bars" and "Primary RSI Color Schemes
- RSI Middle Band: Allows the user to set the RSI middle band value. This value will also applied to "Center Line" color scheme from "Primary RSI Color Schemes" drop menu
- Primary RSI Colors:
Range color specifies a gradient of colors from the overbought to the oversold threshold user inputs from "Primary RSI" section. Color interpolation also a gradient but smoother than Range color. Center Line is similar but is not a gradient, linked to Middle Band ("Primary RSI" section) and changes color with RSI Middle Band. Traditional is simple with Overbought and Oversold colors change.
- RSI Bullish Band: Allows the user to plot extra/optional RSI band on RSI Oscillator (Note: it will not be plotted if "OB/OS Zone only" enabled from "OB/OS Zone Settings" section)
- RSI Bearish Band: Allows the user to plot extra/optional RSI band on RSI Oscillator (Note: it will not be plotted if "OB/OS Zone only" enabled from "OB/OS Zone Settings" section)
+ Primary RSI Smooth Settings ▾
- Smooth Moving Average Type: User selected Smooth MA type. With RSI Smooth enabled, will also effect all RSI Divergences detection (all divergences will be plot according to "Smoothed RSI line")
- Smooth Moving Average Length: User input Smooth MA length value
+ Oscillator Moving Average Settings ▾
- Osc Moving Average Colors: Allows user to select Bullish/Bearish colors of Oscillator Moving Average
- Osc Moving Average Type: Allows user to select Oscillator MA Type
- Osc Moving Average Length: User input Oscillator MA length value
- Osc Moving Average Thickness: User input Oscillator MA thickness
- BB StdDev: user input Bollinger Bands standard deviation value
+ Stochastic Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Stochastic RSI Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Money Index Flow Settings ▾
- Same as Traditional/Default indicator
+ Ultimate Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Momentum Oscillator Settings ▾
- Same as Traditional/Default indicator
+ Average True Range Settings ▾
- Same as Traditional/Default indicator
+ Multi Timeframe RSI Settings ▾
- MTF RSI Time Frame: Allows user to select MTF RSI Time Frame
- MTF RSI Symbol: Allows user to select MTF RSI Time Symbol
- MTF RSI Length: User input MTF RSI length value
- MTF RSI Source: User selected MTF RSI source
- MTF RSI Line Width: User input MTF RSI line thickness value
- Number of Bars for MTF RSI plot
- MTF RSI Color > OB color > OS color : Allows user to select MTF RSI color with additionally Overbought/Oversold colors
+ MTF RSI Panel Settings ▾
- Select MTF RSI Type: If "Primary RSI" or "Volume RSI" selected MTF RSI Panel will show output values based on "Primary RSI" or "Volume RSI" parameters e.g. source, length, but without smooth.
- MTF RSI Panel Symbol: Allows user to select MTF RSI Panel symbol, leave symbol blank or uncheck "checkbox" for current chart symbol
- Show Symbol in Panel: Shows symbol ticker(current or user selected) in MTF RSI Panel
- Panel Background: Allows user to select MTF RSI Panel Background (enable/disable) and Background color selection
- TF1: MTF RSI Timeframe 1 user selection
- TF2: MTF RSI Timeframe 2 user selection
- TF3: MTF RSI Timeframe 3 user selection
- TF4: MTF RSI Timeframe 4 user selection
- TF5: MTF RSI Timeframe 5 user selection
- TF6: MTF RSI Timeframe 6 user selection
- TF7: MTF RSI Timeframe 7 user selection
- TF8: MTF RSI Timeframe 8 user selection
- Panel Top Offset: MTF RSI Panel offset input value
- Position: MTF RSI Panel position selection
- Text Size: MTF RSI Panel text size selection
- Bullish Colors: MTF RSI Panel bullish color selection. (Bullish colors range RSI >75, <75 to >65, <65 to >55)
- Bearish Colors: MTF RSI Panel bearish color selection. (Bearish colors range RSI <45 to >35, <35 to >25, <25)
+ RSI Price Estimator Settings ▾
- Price 1: User input value for RSI future price
- Price 2: User input value for RSI future price
- Price 3: User input value for RSI future price
- Panel Position Offset: User input value for panel position offset
- Price Decimals: User input value for output price decimals in panel
- Show RSI/OscMA cross Price: Enable/Disable RSIxOscillator MA cross future price
- Show RSI Level for Input Price: User input price for future RSI level
- Invisible Background: Enable/Disable Background
Auto Text Color > Auto color change of Panel text according to Dark/Light chart theme
+ Oscillator Support/Resistance Settings ▾
- Show Support line: Allows user to Enable/Disable Oscillator support line
Color > Auto Color: Auto color change of support line according to Dark/Light chart theme
- Show Resistance line: Allows user to Enable/Disable Oscillator resistance line
Color > Auto Color: Auto color display of resistance line according to Dark/Light chart theme
- Lookback lows/highs: User input of Lookback lows/highs value
- Distance threshold: Distance from the line to the low
- Line touch points: Number of points that have to be around the line
- Low/High left bars: User input of Low/High left bars value
- Low/High right bars: User input of Low/High right bars value
- Line style: User selection of line style
- Line thickness: User input of line thickness value
+ Oscillator 1st Divergence Settings ▾
- Divergence Source: User selection of divergence source. "High/Low" (high/low of oscillator/price divergence detection), "Close" (close of oscillator/price divergence detection) and "Both" (Both Close + High/Low of oscillator/price divergence detection). (Note: Traditional Divergence indicator default source is "High/Low")
- Pivot Lookback Right: How many candle to compare on the right side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Pivot Lookback Left: How many candle to compare on the left side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Divergence Max Length (Bars): The maximum length of a divergence (number of bars). If a detected divergence is longer than this, it will be discarded
- Divergence Min Length (Bars): The minimum length of a divergence (number of bars). If a detected divergence is shorter than this, it will be discarded
- Show Divergence as:
- Line Thickness: User input divergence line thickness value
- Label Transparency: it could reduce labels mess on oscillator line, input "100" for label text only without label background
- Labels Text Color: User label text color selection
Auto Text Color > Auto color change of label text according to Dark/Light chart theme
- Bull Divergences: Enable/Disable of Bull divergences
> Color: User selection of Bull divergence color
> Oversold only: It will show Regular Bullish RSI divergences in oversold zone only, RSI oversold threshold can be configure in "Primary RSI Settings" section.
- Bear Divergences: Enable/Disable of Bear divergences
> Color: User selection of Bear divergence color
> Overbought only: It will show Regular Bearish RSI divergences in overbought zone only, RSI overbought threshold can be configure in "Primary RSI Settings" section.
- Hidden Bull Div: Enable/Disable of Hidden Bull divergences
> Color: User selection of Hidden Bull divergence color
- Hidden Bear Div: Enable/Disable of Hidden Bear divergences
> Color: User selection of Hidden Bear divergence color
+ Oscillator 2nd Divergence Settings ▾
- Same as Oscillator 1st Divergence Settings
+ Oscillator 3rd Divergence Settings ▾
- Divergence source: User selection of divergence source . "oscillator" (divergence detection with high/low or close of selected oscillator), "price" (divergence detection with high/low or close of price)
- Bull price source: User selection of Bull price source. Bull price source: "Low" (low of price divergence detection), "Close" (close of price divergence detection) (linked to "price" in "Divergence source")
- Bear price source: User selection of Bear price source. Bear price source: "High" (high of price divergence detection), "Close" (close of price divergence detection) (linked to "price" in "Divergence source")
- Low/High left bars: How many candle to compare on the left side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Low/High right bars: How many candle to compare on the right side of a candle when deciding whether it is a pivot. The lower the number is, the earlier pivots (and therefore divergences) will be signaled, but the quality of those detections could be lower.
- Maximum lookback bars: The maximum length of a divergence (number of bars). If a detected divergence is longer than this, it will be discarded.
- Price threshold: User selection of Price threshold, higher values more lines
- RSI threshold: User selection of RSI threshold, higher values more lines
- Show Lows: Displays lows of RSI
- Show Highs: Displays highs of RSI
- Show Divergence as:
- Line Style:
- Line thickness: User input divergence line thickness value
- Label Transparency: it could reduce labels mess on oscillator line, input "100" for label text only without label background
- Labels Text Color: User label text color selection
Auto Text Color > Auto color change of label text according to Dark/Light chart theme
- Bull Divergences: Enable/Disable of Bull divergences
> Color: User selection of Bull divergence color
> Potential Bull: It will plot potential regular bull divergence with dotted line.
- Bear Divergences: Enable/Disable of Bear divergences
> Color: User selection of Bear divergence color
> Potential Bear: It will plot potential regular bear divergence with dotted line.
- Hidden Bull Div: Enable/Disable of Hidden Bull divergences
> Color: User selection of Hidden Bull divergence color
> Potential H.Bull: It will plot potential hidden bull divergence with dotted line.
- Hidden Bear Div: Enable/Disable of Hidden Bear divergences
> Color: User selection of Hidden Bear divergence color
> Hidden Bear divergence: It will plot potential hidden bear divergence with dotted line.
> Regular Bull oversold only: It will show Regular Bullish RSI divergences in oversold zone only, RSI oversold threshold can be configure in "Primary RSI Settings" section.
> Regular Bear overbought only: It will show Regular Bearish RSI divergences in overbought zone only, RSI overbought threshold can be configure in "Primary RSI Settings" section.
+ Oscillator 4th Divergences Settings ▾
- Upper Length: User pivot input value of draw upper divergence line From
- To Pivot:
- Lower Length: User pivot input value of draw lower divergence line From
- To Pivot:
- Show Divergence as:
- Line Style:
- Line thickness: User input divergence line thickness value
- Label Transparency: it could reduce labels mess on oscillator line, input "100" for label text only without label background
- Labels Text Color: User label text color selection
Auto Text Color > Auto color change of label text according to Dark/Light chart theme
- Bull Divergences: Enable/Disable of Bull divergences
> Color: User selection of Bull divergence color
- Bear Divergences: Enable/Disable of Bear divergences
> Color: User selection of Bear divergence color
- Regular Bull oversold only: It will show Regular Bullish RSI divergences in oversold zone only, RSI oversold threshold can be configure in "Primary RSI Settings" section.
- Regular Bear overbought only: It will show Regular Bearish RSI divergences in overbought zone only, RSI overbought threshold can be configure in "Primary RSI Settings" section.
+ Oscillator HHLL Pivots Settings ▾
- Pivot Length: User input value of HH/LL pivot length
> L.Text Color: User label text color selection
- HH color: User HH Label color selection
- HL color: User HL Label color selection
- LH color: User LH Label color selection
- LL color: User LL Label color selection
+ Oscillator OB/OS Colored Bars Settings▾
- Overbought/Oversold Bars Oscillator: Plots Overbought/Oversold color bars based on RSI, MFI, Stoch, Stoch RSI overbought/oversold threshold conditions separately or combined(when every oscillator reach its OB or OS threshold condition at same time).
- Overbought Bar Color: User RSI OB Bars color selection
- Oversold Bar Color: User RSI OS Bars color selection
+ Primary RSI Range Color ▾
- OB: Overbought Color
- OS: Oversold Color
- Bullish: Bullish Color
- Bearish: Bearish Color
+ Primary RSI Color interpolation ▾
- RSI Color: RSI Color
- OB: Overbought Color
- OS: Oversold Color
+ Primary RSI Center Line Color ▾
- OB: Overbought Color
- Bullish: Bullish Color
- Bearish: Bearish Color
- OS: Oversold Color
+ Primary RSI Traditional Color ▾
- RSI Color: RSI Color
- OB: Overbought Color
- OS: Oversold Color
Osc Overbought/Oversold Zones Settings ▾
- OB/OS Zone Band Lines: Enable/Disable OB/OS Zone Band Lines
- OB/OS Zones only: Only shows OB/OS Zones and disable all RSI band lines except Middle Band. Background will not be effected by this setting.
- Overbought Zone: User input value of Overbought Zone from
> To:
- Oversold Zone: User input value of Oversold Zone from
> To:
Osc Overbought/Oversold Highlights ▾
- Overbought Highlights : Enable/Disable Overbought Highlights
- Oversold Highlights : Enable/Disable Oversold Highlights
- Transparency: Gradient transparency of highlighted area
+ 'Oscillators Color Settings ▾
- Show Osc Symbol label : Enable/Disable of oscillator symbol label. Displays current oscillator symbol, but with "Override Oscillator Symbol" enabled from "Black RSI Dashboard" it will Auto/forcefully displays Override Oscillator Symbol on Oscillator
- Fade out Oscillator line: Fade out the oscillator line color, focusing only the most recent periods prominent for a clearer chart
- Fill Stoch/StochRSI lines: Fills Stoch/Stoch RSI lines
- Oscillator line thickness: user input value of oscillator line thickness
- Oscillator line offset: Shifts the oscillator to the left or to the right on the given number of bars, Default is 0
- OBV Color
- MFI Color
- ATR Color
- UO Color
- MOM Color
- CVD Bullish Color
- CVD Bearish Color
+ Background Setting ▾
- Custom Background Color: User selection of Background color
Authors & Credits: I'd like to THANK to Nabeel Black(myself), LonesomeTheBlue, iFuSiiOnzZ, jmosullivan, zdmre, creengrack, and TradingView for the locally sourced ingredients.
Disclaimer: DYOR. Not financial advice. Not a trading system. I am not affiliated with TradingView or any authors mentioned here; You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely. Always trade with confluence and Risk Management.
Feedback & Bug report
if you found any bug in this indicator or any suggestion, please let me know. Please give feedback & appreciate if you like to see more future updates and indicators. Thank you
[astropark] price levelsDear Followers,
today another awesome Analysis Tool, that you can use in your trading journey: Price Levels !
Are you a range trading player? a scalper? or maybe a day-trader or a swing-trader? This is for you then. Indeed it's for everyone.
This indicator works on every timeframe, market and pair.
It keeps track of recent important levels generated by price action:
Monday high, low and middle range level
Tuesday high and low
Wednesday high and low
Thursday high and low
Friday high and low
Weekly open, high and low
Monthly open, high and low
Yearly open, high and low
Previous weekly open, high and low
Previous monthly open, high and low
Previous yearly open, high and low
You can:
choose price levels to hide and show
change each level color / thickness / display style (solid or dotted)
choose to show or hide price labels and change their size
Why such indicator should be helpful? How can I use it to do profit?
In multiple ways! Let's talk about Monday Range :
when Monday range is formed, price acceptance below Monday low is a bearish signal, so will more likely want to short / sell
equally price acceptance above Monday high is a bullish signal, so will more likely want to long / buy
it can happen that Monday high is simply retested, with price not being able to stay above it: this is called a retest (in case of a simple wick) or a deviation (in case of price staying above the level just for some candles) and what usually happens is price falling back to Monday middle range level and even back to Monday low.
the opposite can happen of course: you will become bullish if Monday low is tested or a deviation appears below Monday low: price tends to bounce on such occasions back to Monday middle range or even Monday high
Tuesday is usually a marker day within a trading week:
if Monday was pretty bullish, Tuesday high may mark the weekly top, following some red days
if Monday was pretty bearish, Tuesday low may mark the weekly bottom, following some green days
Thursday is the day when big players start to take profits, as the trading week is going to end the next day, so in an all-green week Thursday may be a red one, while in an all-red week it may be a bullish day
Thursday is the day when big players start to take profits, as the trading week is going to end the next day:
in an all-green week, Thursday may be a red one and it's low tends to mark the weekly low
while in an all-red week, it tends to be a bullish day, so here you will refill your shorts for the next blooding day
Let's talk now about the Weekly, Monthly and Yearly price levels : here it is the interesting part for Swing Traders
Weekly open is usually a defining level: on retest, if price keeps staying below then more downside is expected, if price keeps staying above then more upside is expected (similarly to what we said about Monday high and low)
Monthly and Yearly open price levels are usually a "no-brainer" buy level in a bullish trend or equally a sell level in a bearish trend: in this scenarios, a deviation structure is even more powerful in term of price reaction and efficiency
We trade Weekly, Monthly and Yearly high and low price levels as explained for the Monday high and low, but with a swing traders perspective (so a medium-long term trade)
Previous Weekly/Monthly/Yearly price levels are usually very useful as targets in your trades
Here below some screenshots that resumes what said above.
Weekly Open as support (bullish) and Monday High deviation (bearish)
Tuesday High, Weekly Open failing as support: bearish
Monday Low deviation (bullish)
Price Acceptance above Monday High and Weekly Open (bullish)
Yearly Open retests as buy opportunities
Deviation below Monthly Open (bullish), Price Acceptance below Monthly and Yearly Open (bearish)
This is a premium indicator , so send me a private message in order to get access to this script.
Kawabunga Swing Failure Points Candles (SFP) by RRBKawabunga Swing Failure Points Candles (SFP) by RagingRocketBull 2019
Version 1.0
This indicator shows Swing Failure Points (SFP) and Swing Confirmation Points (SCP) as candles on a chart.
SFP/SCP candles are used by traders as signals for trend confirmation/possible reversal.
The signal is stronger on a higher volume/larger candle size.
A Swing Failure Point (SFP) candle is used to spot a reversal:
- up trend SFP is a failure to close above prev high after making a new higher high => implies reversal down
- down trend SFP is a failure to close below prev low after making a new lower low => implies reversal up
A Swing Confirmation Point (SCP) candle is just the opposite and is used to confirm the current trend:
- up trend SCP is a successful close above prev high after making a new higher high => confirms the trend and implies continuation up
- down trend SCP is a successful close below prev low after making a new lower low => confirms the trend and implies continuation down
Features:
- uses fractal pivots with optional filter
- show/hide SFP/SCP candles, pivots, zigzag, last min/max pivot bands
- dim lag zones/hide false signals introduced by lagging fractals or
- use unconfirmed pivots to eliminate fractal lag/false signals. 2 modes: fractals 1,1 and highest/lowest
- filter only SFP/SCP candles confirmed with volume/candle size
- SFP/SCP candles color highlighting, dim non-important bars
Usage:
- adjust fractal settings to get pivots that best match your data (lower values => more frequent pivots. 0,0 - each candle is a pivot)
- use one of the unconfirmed pivot modes to eliminate false signals or just ignore all signals in the gray lag zones
- optionally filter only SFP/SCP candles with large volume/candle size (volume % change relative to prev bar, abs candle body size value)
- up/down trend SCP (lime/fuchsia) => continuation up/down; up/down trend SFP (orange/aqua) => possible reversal down/up. lime/aqua => up; fuchsia/orange => down.
- when in doubt use show/hide pivots/unconfirmed pivots, min/max pivot bands to see which prev pivot and min/max value were used in comparisons to generate a signal on the following candle.
- disable offset to check on which bar the signal was generated
Notes:
Fractal Pivots:
- SFP/SCP candles depend on fractal pivots, you will get different signals with different pivot settings. Usually 4,4 or 2,2 settings are used to produce fractal pivots, but you can try custom values that fit your data best.
- fractal pivots are a mixed series of highs and lows in no particular order. Pivots must be filtered to produce a proper zigzag where ideally a high is followed by a low and another high in orderly fashion.
Fractal Lag/False Signals:
- only past fractal pivots can be processed on the current bar introducing a lag, therefore, pivots and min/max pivot bands are shown with offset=-rightBars to match their target bars. For unconfirmed pivots an offset=-1 is used with a lag of just 1 bar.
- new pivot is not a confirmed fractal and "does not exist yet" while the distance between it and the current bar is < rightBars => prev old fractal pivot in the same dir is used for comparisons => gives a false signal for that dir
- to show false signals enable lag zones. SFP/SCP candles in lag zones are false. New pivots will be eventually confirmed, but meanwhile you get a false signal because prev pivot in the same dir was used instead.
- to solve this problem you can either temporary hide false signals or completely eliminate them by using unconfirmed pivots of a smaller degree/lag.
- hiding false signals only works for history and should be used only temporary (left disabled). In realtime/replay mode it disables all signals altogether due to TradingView's bug (barcolor doesn't support negative offsets)
Unconfirmed Pivots:
- you have 2 methods to check for unconfirmed pivots: highest/lowest(rightBars) or fractals(1,1) with a min possible step. The first is essentially fractals(0,0) where each candle is a pivot. Both produce more frequent pivots (weaker signals).
- an unconfirmed pivot is used in comparisons to generate a valid signal only when it is a higher high (> max high) or a lower low (< min low) in the dir of a trend. Confirmed pivots of a higher degree are not affected. Zigzag is not affected.
- you can also manually disable the offset to check on which bar the pivot was confirmed. If the pivot just before an SCP/SFP suddenly jumps ahead of it - prev pivot was used, generating a false signal.
- last max high/min low bands can be used to check which value was used in candle comparison to generate a signal: min(pivot min_low, upivot min_low) and max(pivot max_high, upivot max_high) are used
- in the unconfirmed pivots mode the max high/min low pivot bands partially break because you can't have a variable offset to match the random pos of an unconfirmed pivot (anywhere in 0..rightBars from the current bar) to its target bar.
- in the unconfirmed pivots mode h (green) and l (red) pivots become H and L, and h (lime) and l (fuchsia) are used to show unconfirmed pivots of a smaller degree. Some of them will be confirmed later as H and L pivots of a higher degree.
Pivot Filter:
- pivot filter is used to produce a better looking zigzag. Essentially it keeps only higher highs/lower lows in the trend direction until it changes, skipping:
- after a new high: all subsequent lower highs until a new low
- after a new low: all subsequent higher lows until a new high
- you can't filter out all prev highs/lows to keep just the last min/max pivots of the current swing because they were already confirmed as pivots and you can't delete/change history
- alternatively you could just pick the first high following a low and the first low following a high in a sequence and ignore the rest of the pivots in the same dir, producing a crude looking zigzag where obvious max high/min lows are ignored.
- pivot filter affects SCP/SFP signals because it skips some pivots
- pivot filter is not applied to/not affected by the unconfirmed pivots
- zigzag is affected by pivot filter, but not by the unconfirmed pivots. You can't have both high/low on the same bar in a zigzag. High has priority over Low.
- keep same bar pivots option lets you choose which pivots to keep when there are both high/low pivots on the same bar (both kept by default)
SCP/SFP Filters:
- you can confirm/filter only SCP/SFP signals with volume % change/candle size larger than delta. Higher volume/larger candle means stronger signal.
- technically SCP/SFP is always the first matching candle, but it can be invalidated by the following signal in the opposite dir which in turn can be negated by the next signal.
- show first matching SCP/SFP = true - shows only the first signal candle (and any invalidations that follow) and hides further duplicate signals in the same dir, does not highlight the trend.
- show first matching SCP/SFP = false - produces a sequence of candles with duplicate signals, highlights the whole trend until its dir changes (new pivot).
Good Luck! Feel free to learn from/reuse the code to build your own indicators!
3 Period EMA Cloud [deepakks444]3 Period EMA Cloud Indicator
The 3EMA Cloud Indicator uses three key EMAs to capture trends and display the market's direction through a color-coded cloud. The EMAs used in this indicator are:
High EMA: The EMA of the high prices over a specified period.
Low EMA: The EMA of the low prices over a specified period.
Additional EMA: An extra EMA, typically based on the close prices, that serves as an independent confirmation tool for trend direction.
Indicator Logic and Cloud Visualization:
The cloud is drawn between the high EMA and the low EMA, and its color changes based on the price's relationship to the high EMA, low EMA, and additional EMA.
Cloud Color:
Green Cloud: When the price is above both the high EMA and the low EMA, it signals a bullish trend, and the cloud turns green.
Additionally, if the close price is above the Additional EMA, this further confirms the bullish trend.
Red Cloud: When the price is below both the high EMA and the low EMA, it signals a bearish trend, and the cloud turns red.
Additionally, if the close price is below the Additional EMA, this further confirms the bearish trend.
How the Indicator Captures Trends:
Bullish Market:
Price above both high EMA and low EMA: This indicates that the market is in an uptrend, and the cloud will turn green.
Confirmation with Additional EMA: When the close price is above the Additional EMA, this reinforces the bullish market sentiment.
The green cloud is the visual confirmation of a bullish trend, guiding traders to consider long positions.
Bearish Market:
Price below both high EMA and low EMA: This indicates that the market is in a downtrend, and the cloud will turn red.
Confirmation with Additional EMA: When the close price is below the Additional EMA, this confirms the bearish trend.
The red cloud is the visual confirmation of a bearish trend, guiding traders to consider short positions.
Key Components:
High EMA: Calculates the EMA based on high prices, which helps to determine the upper boundary of the cloud.
Low EMA: Calculates the EMA based on low prices, which helps to determine the lower boundary of the cloud.
Additional EMA: An extra EMA (often of the close prices) that acts as an independent trend confirmation. This is used to validate the market direction and filter out potential false signals.
Use Cases for the 3EMA Cloud:
Trend Identification:
The cloud helps to visually identify the prevailing trend. A green cloud suggests a bullish trend, while a red cloud indicates a bearish trend.
Confirmation Tool:
The Additional EMA serves as an additional confirmation tool. A close price above the Additional EMA signals a strong bullish trend, while a close below it signals a strong bearish trend.
Market Reversals:
When the price moves from above both the high EMA and low EMA to below them (or vice versa), this could indicate a trend reversal. Pay attention to cloud color changes and the movement of the close price relative to the Additional EMA for potential reversal signals.
Entry and Exit Signals:
Long Entry (Buy Signal):
Price is above both the high EMA and low EMA, confirming a bullish trend.
Close price is above the Additional EMA, confirming the bullish trend.
Enter a long position when the cloud turns green and the confirmation by the Additional EMA is in place.
Short Entry (Sell Signal):
Price is below both the high EMA and low EMA, confirming a bearish trend.
Close price is below the Additional EMA, confirming the bearish trend.
Enter a short position when the cloud turns red and the confirmation by the Additional EMA is in place.
Exit Signal:
Exit Long Position when the price moves below both the high EMA and low EMA (signaling a potential trend reversal), or if the close price falls below the Additional EMA.
Exit Short Position when the price moves above both the high EMA and low EMA (signaling a potential trend reversal), or if the close price rises above the Additional EMA.
How This Indicator Improves Trend Following:
The 3EMA Cloud indicator enhances trend-following strategies by:
Visual Clarity: The color-coded cloud provides immediate visual feedback on whether the market is in a bullish or bearish phase.
Price Confirmation: The indicator uses the relationship of price to three EMAs (high, low, and additional) to confirm trend strength, which can help reduce false signals.
Flexibility: The Additional EMA adds flexibility by serving as an independent confirmation tool for trend direction, ensuring that you don’t enter trades based on weak or choppy market conditions.
This 3EMA Cloud indicator is designed to help traders follow and confirm trends with precision, improving their ability to identify strong market movements and avoid getting caught in sideways or choppy conditions. It provides a clear visual cue for potential buy and sell opportunities based on price relative to multiple EMAs, ensuring that trend-following strategies are robust and effective.
Disclaimer:
This script and its associated indicators are for educational purposes only. The information provided does not constitute financial advice or a recommendation to buy or sell any financial instruments. Users are advised to conduct their own research and consult with a professional financial advisor before making any trading decisions. Trading and investing involve risk, and users should be aware of the risks involved in financial markets.
Time Based StatisticsThis indicator is a complex time-based statistics tool for analyzing intraday trading patterns. Here's a comprehensive breakdown:
1. **Session Management**
- Tracks trading sessions from 18:00 to 16:59 next day (using New York time)
- Separates analysis by weekdays (Monday through Friday)
- Resets statistics at week's end
2. **High/Low Time Tracking**
- Records when daily highs and lows occur for each day
- Maintains historical arrays of high/low times for pattern analysis
- Tracks high/low patterns in three main time periods:
- Evening/Overnight (18:00-23:59)
- Early Morning (00:00-09:59)
- Market Hours (10:00-16:59)
3. **Probability Calculations**
The indicator calculates several probabilities:
a) **Hold Probability**
- Calculates likelihood current high/low will remain day's high/low
- Counts how many historical highs/lows occurred in remaining hours
- Returns percentage based on historical patterns
b) **Most Frequent Times**
- Identifies which times most frequently produce highs/lows
- Tracks both primary and secondary (next highest) probable times
- Maintains historical counts of highs/lows by hour
4. **Pattern Analysis**
- Filters historical times based on current time
- Helps predict potential future high/low times
- Adjusts analysis based on time of day
5. **Data Display**
Shows statistics in a table including:
- Days of data analyzed
- Current day's high/low times
- Most frequent times for today's highs/lows
- Probability of current high/low holding
- Historical patterns for current hour
6. **Historical Data Management**
- Stores daily high/low data at week's end
- Maintains separate arrays for each day of the week
- Uses this historical data for pattern analysis
The indicator helps traders by:
- Understanding when highs/lows typically occur
- Assessing probability of new highs/lows
- Identifying historically significant time periods
- Providing statistical basis for timing decisions
Daily Weekly Monthly Highs & Lows - Alerts !
1. Purpose
The script helps traders:
• Visualize the high and low levels for the previous daily, weekly, and monthly periods.
• Receive alerts when the current price crosses these levels.
• Identify key support and resistance zones based on historical highs and lows.
2. Key Features
User Inputs
The script offers customization options through input parameters:
• Daily Levels:
• Enable/disable displaying daily levels (Show Daily Levels).
• Customize the color for daily level lines (Daily Line Color).
• Weekly Levels:
• Enable/disable displaying weekly levels (Show Weekly Levels).
• Customize the color for weekly level lines (Weekly Line Color).
• Monthly Levels:
• Enable/disable displaying monthly levels (Show Monthly Levels).
• Customize the color for monthly level lines (Monthly Line Color).
3. Core Functionality
Level Calculations
The script retrieves the previous daily, weekly, and monthly highs and lows using the request.security() function:
• Daily High/Low: Taken from the previous day’s high and low.
• Weekly High/Low: Taken from the previous week’s high and low.
• Monthly High/Low: Taken from the previous month’s high and low.
Price Crossing Detection
For each level (daily, weekly, monthly), the script checks if the current high or low price has crossed:
• The previous high (triggering a “High Reached” alert).
• The previous low (triggering a “Low Reached” alert).
4. Visual Features
The script plots lines to represent the previous highs and lows:
• Daily Levels:
• Dashed lines for the previous daily high and low.
• Configurable color (Daily Line Color).
• Weekly Levels:
• Dashed lines for the previous weekly high and low.
• Configurable color (Weekly Line Color).
• Monthly Levels:
• Dashed lines for the previous monthly high and low.
• Configurable color (Monthly Line Color).
These lines extend forward by one bar for better visibility on the chart.
5. Alert Features
The script provides alerts for when the price crosses these levels:
• Daily Alerts:
• “Daily High Reached” when the current price crosses the previous daily high.
• “Daily Low Reached” when the current price crosses the previous daily low.
• Weekly Alerts:
• “Weekly High Reached” when the current price crosses the previous weekly high.
• “Weekly Low Reached” when the current price crosses the previous weekly low.
• Monthly Alerts:
• “Monthly High Reached” when the current price crosses the previous monthly high.
• “Monthly Low Reached” when the current price crosses the previous monthly low.
6. Practical Use Case
This script is ideal for traders who:
• Use support and resistance levels from daily, weekly, and monthly timeframes as part of their strategy.
• Want to monitor price interactions with these levels in real-time.
• Need automatic alerts for key price movements without continuously monitoring the chart.
7. Limitations
• Max Line Count: TradingView limits the number of lines that can be drawn on the chart to max_lines_count = 500.
• No Historical Levels: The script only tracks the most recent daily, weekly, and monthly levels and does not display historical levels.
Top-Down Trend and Key Levels with Swing Points//by antaryaami0
Overview
The “Top-Down Trend and Key Levels with Swing Points” indicator is a comprehensive tool designed to enhance your technical analysis by integrating multiple trading concepts into a single, easy-to-use script. It combines higher timeframe trend analysis, key price levels, swing point detection, and ranging market identification to provide a holistic view of market conditions. This indicator is particularly useful for traders who employ multi-timeframe analysis, support and resistance levels, and price action strategies.
Key Features
1. Higher Timeframe Trend Background Shading:
• Purpose: Identifies the prevailing trend on a higher timeframe to align lower timeframe trading decisions with the broader market direction.
• How it Works: The indicator compares the current higher timeframe close with the previous one to determine if the trend is up, down, or ranging.
• Customization:
• Trend Timeframe: Set your preferred higher timeframe (e.g., Daily, Weekly).
• Up Trend Color & Down Trend Color: Customize the background colors for uptrends and downtrends.
• Ranging Market Color: A separate color to indicate when the market is moving sideways.
2. Key Price Levels:
• Previous Day High (PDH) and Low (PDL):
• Purpose: Identifies key support and resistance levels from the previous trading day.
• Visualization: Plots horizontal lines at PDH and PDL with labels.
• Customization: Option to show or hide these levels and customize their colors.
• Pre-Market High (PMH) and Low (PML):
• Purpose: Highlights the price range during the pre-market session, which can indicate potential breakout levels.
• Visualization: Plots horizontal lines at PMH and PML with labels.
• Customization: Option to show or hide these levels and customize their colors.
3. First 5-Minute Marker (F5H/F5L):
• Purpose: Marks the high or low of the first 5 minutes after the market opens, which is significant for intraday momentum.
• How it Works:
• If the first 5-minute high is above the Pre-Market High (PMH), an “F5H” label is placed at the first 5-minute high.
• If the first 5-minute high is below the PMH, an “F5L” label is placed at the first 5-minute low.
• Visualization: Labels are placed at the 9:35 AM candle (closing of the first 5 minutes), colored in purple by default.
• Customization: Option to show or hide the marker and adjust the marker color.
4. Swing Points Detection:
• Purpose: Identifies significant pivot points in price action to help recognize trends and reversals.
• How it Works: Uses left and right bars to detect pivot highs and lows, then determines if they are Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), or Lower Lows (LL).
• Visualization: Plots small markers (circles) with labels (HH, LH, HL, LL) at the corresponding swing points.
• Customization: Adjust the number of left and right bars for pivot detection and the size of the markers.
5. Ranging Market Detection:
• Purpose: Identifies periods when the market is consolidating (moving sideways) within a defined price range.
• How it Works: Calculates the highest high and lowest low over a specified period and determines if the price range is within a set percentage threshold.
• Visualization: Draws a gray box around the price action during the ranging period and labels the high and low prices at the end of the range.
• Customization: Adjust the range detection period and threshold, as well as the box color.
6. Trend Coloring on Chart:
• Purpose: Provides a visual cue for the short-term trend based on a moving average.
• How it Works: Colors the candles green if the price is above the moving average and red if below.
• Customization: Set the moving average length and customize the uptrend and downtrend colors.
How to Use the Indicator
1. Adding the Indicator to Your Chart:
• Copy the Pine Script code provided and paste it into the Pine Script Editor on TradingView.
• Click “Add to Chart” to apply the indicator.
2. Configuring Inputs and Settings:
• Access Inputs:
• Click on the gear icon next to the indicator’s name on your chart to open the settings.
• Customize Key Levels:
• Show Pre-Market High/Low: Toggle on/off.
• Show Previous Day High/Low: Toggle on/off.
• Show First 5-Minute Marker: Toggle on/off.
• Set Trend Parameters:
• Trend Timeframe for Background: Choose the higher timeframe for trend analysis.
• Moving Average Length for Bar Color: Set the period for the moving average used in bar coloring.
• Adjust Ranging Market Detection:
• Range Detection Period: Specify the number of bars to consider for range detection.
• Range Threshold (%): Set the maximum percentage range for the market to be considered ranging.
• Customize Visuals:
• Colors: Adjust colors for trends, levels, markers, and ranging market boxes.
• Label Font Size: Choose the size of labels displayed on the chart.
• Level Line Width: Set the thickness of the lines for key levels.
3. Interpreting the Indicator:
• Background Shading:
• Green Shade: Higher timeframe is in an uptrend.
• Red Shade: Higher timeframe is in a downtrend.
• Gray Box: Market is ranging (sideways movement).
• Key Levels and Markers:
• PDH and PDL Lines: Represent resistance and support from the previous day.
• PMH and PML Lines: Indicate potential breakout levels based on pre-market activity.
• F5H/F5L Labels: Early indication of intraday momentum after market open.
• Swing Point Markers:
• HH (Higher High): Suggests bullish momentum.
• LH (Lower High): May indicate a potential bearish reversal.
• HL (Higher Low): Supports bullish continuation.
• LL (Lower Low): Indicates bearish momentum.
• Ranging Market Box:
• Gray Box Around Price Action: Highlights consolidation periods where breakouts may occur.
• Range High and Low Labels: Provide the upper and lower bounds of the consolidation zone.
4. Applying the Indicator to Your Trading Strategy:
• Trend Alignment:
• Use the higher timeframe trend shading to align your trades with the broader market direction.
• Key Levels Trading:
• Watch for price reactions at PDH, PDL, PMH, and PML for potential entry and exit points.
• Swing Points Analysis:
• Identify trend continuations or reversals by observing the sequence of HH, HL, LH, and LL.
• Ranging Market Strategies:
• During ranging periods, consider range-bound trading strategies or prepare for breakout trades when the price exits the range.
• Intraday Momentum:
• Use the F5H/F5L marker to gauge early market sentiment and potential intraday trends.
Practical Tips
• Adjust Settings to Your Trading Style:
• Tailor the indicator’s inputs to match your preferred timeframes and trading instruments.
• Combine with Other Indicators:
• Use in conjunction with volume indicators, oscillators, or other technical tools for additional confirmation.
• Backtesting:
• Apply the indicator to historical data to observe how it performs and refine your settings accordingly.
• Stay Updated on Market Conditions:
• Be aware of news events or economic releases that may impact market behavior and the effectiveness of technical levels.
Customization Options
• Time Zone Adjustment:
• The script uses “America/New_York” time zone by default. Adjust the timezone variable in the script if your chart operates in a different time zone.
var timezone = "Your/Timezone"
• Session Times:
• Modify the Regular Trading Session and Pre-Market Session times in the indicator settings to align with the trading hours of different markets or exchanges.
• Visual Preferences:
• Colors: Personalize the indicator’s colors to suit your visual preferences or to enhance visibility.
• Label Sizes: Adjust label sizes if you find them too intrusive or not prominent enough.
• Marker Sizes: Further reduce or enlarge the swing point markers by modifying the swing_marker_size variable.
Understanding the Indicator’s Logic
1. Higher Timeframe Trend Analysis:
• The indicator retrieves the closing prices of a higher timeframe using the request.security() function.
• It compares the current higher timeframe close with the previous one to determine the trend direction.
2. Key Level Calculation:
• Previous Day High/Low: Calculated by tracking the highest and lowest prices of the previous trading day.
• Pre-Market High/Low: Calculated by monitoring price action during the pre-market session.
3. First 5-Minute Marker Logic:
• At 9:35 AM (end of the first 5 minutes after market open), the indicator evaluates whether the first 5-minute high is above or below the PMH.
• It then places the appropriate label (F5H or F5L) on the chart.
4. Swing Points Detection:
• The script uses ta.pivothigh() and ta.pivotlow() functions to detect pivot points.
• It then determines the type of swing point based on comparisons with previous swings.
5. Ranging Market Detection:
• The indicator looks back over a specified number of bars to find the highest high and lowest low.
• It calculates the percentage difference between these two points.
• If the difference is below the set threshold, the market is considered to be ranging, and a box is drawn around the price action.
Limitations and Considerations
• Indicator Limitations:
• Maximum Boxes and Labels: Due to Pine Script limitations, there is a maximum number of boxes and labels that can be displayed simultaneously.
• Performance Impact: Adding multiple visual elements (boxes, labels, markers) can affect the performance of the script on lower-end devices or with large amounts of data.
• Market Conditions:
• False Signals: Like any technical tool, the indicator may produce false signals, especially during volatile or erratic market conditions.
• Not a Standalone Solution: This indicator should be used as part of a comprehensive trading strategy, including risk management and other forms of analysis.
Conclusion
The “Top-Down Trend and Key Levels with Swing Points” indicator is a versatile tool that integrates essential aspects of technical analysis into one script. By providing insights into higher timeframe trends, highlighting key price levels, detecting swing points, and identifying ranging markets, it equips traders with valuable information to make more informed trading decisions. Whether you are a day trader looking for intraday opportunities or a swing trader aiming to align with the broader trend, this indicator can enhance your chart analysis and trading strategy.
Disclaimer
Trading involves significant risk, and it’s important to understand that past performance is not indicative of future results. This indicator is a tool to assist in analysis and should not be solely relied upon for making trading decisions. Always conduct thorough research and consider seeking advice from financial professionals before engaging in trading activities.
Weekly H/L DOTWThe Weekly High/Low Day Breakdown indicator provides a detailed statistical analysis of the days of the week (Monday to Sunday) on which weekly highs and lows occur for a given timeframe. It helps traders identify recurring patterns, correlations, and tendencies in price behavior across different days of the week. This can assist in planning trading strategies by leveraging day-specific patterns.
The indicator visually displays the statistical distribution of weekly highs and lows in an easy-to-read tabular format on your chart. Users can customize how the data is displayed, including whether the table is horizontal or vertical, the size of the text, and the position of the table on the chart.
Key Features:
Weekly Highs and Lows Identification:
Tracks the highest and lowest price of each trading week.
Records the day of the week on which these events occur.
Customizable Table Layout:
Option to display the table horizontally or vertically.
Text size can be adjusted (Small, Normal, or Large).
Table position is customizable (top-right, top-left, bottom-right, or bottom-left of the chart).
Flexible Value Representation:
Allows the display of values as percentages or as occurrences.
Default setting is occurrences, but users can toggle to percentages as needed.
Day-Specific Display:
Option to hide Saturday or Sunday if these days are not relevant to your trading strategy.
Visible Date Range:
Users can define a start and end date for the analysis, focusing the results on a specific period of interest.
User-Friendly Interface:
The table dynamically updates based on the selected timeframe and visibility of the chart, ensuring the displayed data is always relevant to the current context.
Adaptable to Custom Needs:
Includes all-day names from Monday to Sunday, but allows for specific days to be excluded based on the user’s preferences.
Indicator Logic:
Data Collection:
The indicator collects daily high, low, day of the week, and time data from the selected ticker using the request.security() function with a daily timeframe ('D').
Weekly Tracking:
Tracks the start and end times of each week.
During each week, it monitors the highest and lowest prices and the days they occurred.
Weekly Closure:
When a week ends (detected by Sunday’s daily candle), the indicator:
Updates the statistics for the respective days of the week where the weekly high and low occurred.
Resets tracking variables for the next week.
Visible Range Filter:
Only processes data for weeks that fall within the visible range of the chart, ensuring the table reflects only the visible portion of the chart.
Statistical Calculations:
Counts the number of weekly highs and lows for each day.
Calculates percentages relative to the total number of weeks in the visible range.
Dynamic Table Display:
Depending on user preferences, displays the data either horizontally or vertically.
Formats the table with proper alignment, colors, and text sizes for easy readability.
Custom Value Representation:
If set to "percentages," displays the percentage of weeks a high/low occurred on each day.
If set to "occurrences," displays the raw count of weekly highs/lows for each day.
Input Parameters:
High Text Color:
Color for the text in the "Weekly High" row or column.
Low Text Color:
Color for the text in the "Weekly Low" row or column.
High Background Color:
Background color for the "Weekly High" row or column.
Low Background Color:
Background color for the "Weekly Low" row or column.
Table Background Color:
General background color for the table.
Hide Saturday:
Option to exclude Saturday from the analysis and table.
Hide Sunday:
Option to exclude Sunday from the analysis and table.
Values Format:
Dropdown menu to select "percentages" or "occurrences."
Default value: "occurrences."
Table Position:
Dropdown menu to select the table position on the chart: "top_right," "top_left," "bottom_right," "bottom_left."
Default value: "top_right."
Text Size:
Dropdown menu to select text size: "Small," "Normal," "Large."
Default value: "Normal."
Vertical Table Format:
Checkbox to toggle the table layout:
Checked: Table displays days vertically, with Monday at the top.
Unchecked: Table displays days horizontally.
Start Date:
Allows users to specify the starting date for the analysis.
End Date:
Allows users to specify the ending date for the analysis.
Use Cases:
Day-Specific Pattern Recognition:
Identify if specific days, such as Monday or Friday, are more likely to form weekly highs or lows.
Seasonal Analysis:
Use the start and end date filters to analyze patterns during specific trading seasons.
Strategy Development:
Plan day-based entry and exit strategies by identifying recurring patterns in weekly highs/lows.
Historical Review:
Study historical data to understand how market behavior has changed over time.
TradingView TOS Compliance Notes:
Originality:
This script is uniquely designed to provide day-based statistics for weekly highs and lows, which is not a common feature in other publicly available indicators.
Usefulness:
Offers practical insights for traders interested in understanding day-specific price behavior.
Detailed Description:
Fully explains the purpose, features, logic, input settings, and use cases of the indicator.
Includes clear and concise details on how each input works.
Clear Input Descriptions:
All input parameters are clearly named and explained in the script and this description.
No Redundant Functionality:
Focused specifically on tracking weekly highs and lows, ensuring the indicator serves a distinct purpose without unnecessary features.
Exposure Oscillator (Cumulative 0 to ±100%)
Exposure Oscillator (Cumulative 0 to ±100%)
This Pine Script indicator plots an "Exposure Oscillator" on the chart, which tracks the cumulative market exposure from a range of technical buy and sell signals. The exposure is measured on a scale from -100% (maximum short exposure) to +100% (maximum long exposure), helping traders assess the strength of their position in the market. It provides an intuitive visual cue to aid decision-making for trend-following strategies.
Buy Signals (Increase Exposure Score by +10%)
Buy Signal 1 (Cross Above 21 EMA):
This signal is triggered when the price crosses above the 21-period Exponential Moving Average (EMA), where the current bar closes above the EMA21, and the previous bar closed below the EMA21. This indicates a potential upward price movement as the market shifts into a bullish trend.
buySignal1 = ta.crossover(close, ema21)
Buy Signal 2 (Trending Above 21 EMA):
This signal is triggered when the price closes above the 21-period EMA for each of the last 5 bars, indicating a sustained bullish trend. It confirms that the price is consistently above the EMA21 for a significant period.
buySignal2 = ta.barssince(close <= ema21) > 5
Buy Signal 3 (Living Above 21 EMA):
This signal is triggered when the price has closed above the 21-period EMA for each of the last 15 bars, demonstrating a strong, prolonged uptrend.
buySignal3 = ta.barssince(close <= ema21) > 15
Buy Signal 4 (Cross Above 50 SMA):
This signal is triggered when the price crosses above the 50-period Simple Moving Average (SMA), where the current bar closes above the 50 SMA, and the previous bar closed below it. It indicates a shift toward bullish momentum.
buySignal4 = ta.crossover(close, sma50)
Buy Signal 5 (Cross Above 200 SMA):
This signal is triggered when the price crosses above the 200-period Simple Moving Average (SMA), where the current bar closes above the 200 SMA, and the previous bar closed below it. This suggests a long-term bullish trend.
buySignal5 = ta.crossover(close, sma200)
Buy Signal 6 (Low Above 50 SMA):
This signal is true when the lowest price of the current bar is above the 50-period SMA, indicating strong bullish pressure as the price maintains itself above the moving average.
buySignal6 = low > sma50
Buy Signal 7 (Accumulation Day):
An accumulation day occurs when the closing price is in the upper half of the daily range (greater than 50%) and the volume is larger than the previous bar's volume, suggesting buying pressure and accumulation.
buySignal7 = (close - low) / (high - low) > 0.5 and volume > volume
Buy Signal 8 (Higher High):
This signal occurs when the current bar’s high exceeds the highest high of the previous 14 bars, indicating a breakout or strong upward momentum.
buySignal8 = high > ta.highest(high, 14)
Buy Signal 9 (Key Reversal Bar):
This signal is generated when the stock opens below the low of the previous bar but rallies to close above the previous bar’s high, signaling a potential reversal from bearish to bullish.
buySignal9 = open < low and close > high
Buy Signal 10 (Distribution Day Fall Off):
This signal is triggered when a distribution day (a day with high volume and a close near the low of the range) "falls off" the rolling 25-bar period, indicating the end of a bearish trend or selling pressure.
buySignal10 = ta.barssince(close < sma50 and close < sma50) > 25
Sell Signals (Decrease Exposure Score by -10%)
Sell Signal 1 (Cross Below 21 EMA):
This signal is triggered when the price crosses below the 21-period Exponential Moving Average (EMA), where the current bar closes below the EMA21, and the previous bar closed above it. It suggests that the market may be shifting from a bullish trend to a bearish trend.
sellSignal1 = ta.crossunder(close, ema21)
Sell Signal 2 (Trending Below 21 EMA):
This signal is triggered when the price closes below the 21-period EMA for each of the last 5 bars, indicating a sustained bearish trend.
sellSignal2 = ta.barssince(close >= ema21) > 5
Sell Signal 3 (Living Below 21 EMA):
This signal is triggered when the price has closed below the 21-period EMA for each of the last 15 bars, suggesting a strong downtrend.
sellSignal3 = ta.barssince(close >= ema21) > 15
Sell Signal 4 (Cross Below 50 SMA):
This signal is triggered when the price crosses below the 50-period Simple Moving Average (SMA), where the current bar closes below the 50 SMA, and the previous bar closed above it. It indicates the start of a bearish trend.
sellSignal4 = ta.crossunder(close, sma50)
Sell Signal 5 (Cross Below 200 SMA):
This signal is triggered when the price crosses below the 200-period Simple Moving Average (SMA), where the current bar closes below the 200 SMA, and the previous bar closed above it. It indicates a long-term bearish trend.
sellSignal5 = ta.crossunder(close, sma200)
Sell Signal 6 (High Below 50 SMA):
This signal is true when the highest price of the current bar is below the 50-period SMA, indicating weak bullishness or a potential bearish reversal.
sellSignal6 = high < sma50
Sell Signal 7 (Distribution Day):
A distribution day is identified when the closing range of a bar is less than 50% and the volume is larger than the previous bar's volume, suggesting that selling pressure is increasing.
sellSignal7 = (close - low) / (high - low) < 0.5 and volume > volume
Sell Signal 8 (Lower Low):
This signal occurs when the current bar's low is less than the lowest low of the previous 14 bars, indicating a breakdown or strong downward momentum.
sellSignal8 = low < ta.lowest(low, 14)
Sell Signal 9 (Downside Reversal Bar):
A downside reversal bar occurs when the stock opens above the previous bar's high but falls to close below the previous bar’s low, signaling a reversal from bullish to bearish.
sellSignal9 = open > high and close < low
Sell Signal 10 (Distribution Cluster):
This signal is triggered when a distribution day occurs three times in the rolling 7-bar period, indicating significant selling pressure.
sellSignal10 = ta.valuewhen((close < low) and volume > volume , 1, 7) >= 3
Theme Mode:
Users can select the theme mode (Auto, Dark, or Light) to match the chart's background or to manually choose a light or dark theme for the oscillator's appearance.
Exposure Score Calculation: The script calculates a cumulative exposure score based on a series of buy and sell signals.
Buy signals increase the exposure score, while sell signals decrease it. Each signal impacts the score by ±10%.
Signal Conditions: The buy and sell signals are derived from multiple conditions, including crossovers with moving averages (EMA21, SMA50, SMA200), trend behavior, and price/volume analysis.
Oscillator Visualization: The exposure score is visualized as a line on the chart, changing color based on whether the exposure is positive (long position) or negative (short position). It is limited to the range of -100% to +100%.
Position Type: The indicator also indicates the position type based on the exposure score, labeling it as "Long," "Short," or "Neutral."
Horizontal Lines: Reference lines at 0%, 100%, and -100% visually mark neutral, increasing long, and increasing short exposure levels.
Exposure Table: A table displays the current exposure level (in percentage) and position type ("Long," "Short," or "Neutral"), updated dynamically based on the oscillator’s value.
Inputs:
Theme Mode: Choose "Auto" to use the default chart theme, or manually select "Dark" or "Light."
Usage:
This oscillator is designed to help traders track market sentiment, gauge exposure levels, and manage risk. It can be used for long-term trend-following strategies or short-term trades based on moving average crossovers and volume analysis.
The oscillator operates in conjunction with the chart’s price action and provides a visual representation of the market’s current trend strength and exposure.
Important Considerations:
Risk Management: While the exposure score provides valuable insight, it should be combined with other risk management tools and analysis for optimal trading decisions.
Signal Sensitivity: The accuracy and effectiveness of the signals depend on market conditions and may require adjustments based on the user’s trading strategy or timeframe.
Disclaimer:
This script is for educational purposes only. Trading involves significant risk, and users should carefully evaluate all market conditions and apply appropriate risk management strategies before using this tool in live trading environments.
HTF TriangleHTF Triangle by ZeroHeroTrading aims at detecting ascending and descending triangles using higher time frame data, without repainting nor misalignment issues.
It addresses user requests for combining Ascending Triangle and Descending Triangle into one indicator.
Ascending triangles are defined by an horizontal upper trend line and a rising lower trend line. It is a chart pattern used in technical analysis to predict the continuation of an uptrend.
Descending triangles are defined by a falling upper trend line and an horizontal lower trend line. It is a chart pattern used in technical analysis to predict the continuation of a downtrend.
This indicator can be useful if you, like me, believe that higher time frames can offer a broader perspective and provide clearer signals, smoothing out market noise and showing longer-term trends.
You can change the indicator settings as you see fit to tighten or loosen the detection, and achieve the best results for your use case.
Features
It draws the detected ascending and descending triangles on the chart.
It supports alerting when a detection occurs.
It allows for selecting ascending and/or descending triangle detection.
It allows for setting the higher time frame to run the detection on.
It allows for setting the minimum number of consecutive valid higher time frame bars to fit the pattern criteria.
It allows for setting a high/low factor detection criteria to apply on higher time frame bars high/low as a proportion of the distance between the reference bar high/low and open/close.
It allows for turning on an adjustment of the triangle using highest/lowest values within valid higher time frame bars.
Settings
Ascending checkbox: Turns on/off ascending triangle detection. Default is on.
Descending checkbox: Turns on/off descending triangle detection. Default is on.
Higher Time Frame dropdown: Selects higher time frame to run the detection on. It must be higher than, and a multiple of, the chart's timeframe. Default is 5 minutes.
Valid Bars Minimum field: Sets minimum number of consecutive valid higher time frame bars to fit the pattern criteria. Default is 3. Minimum is 1.
High/Low Factor checkbox: Turns on/off high/low factor detection criteria. Default is on.
High/Low Factor field: Sets high/low factor to apply on higher time frame bars high/low as a proportion of the distance between the reference bar high/low and open/close. Default is 0. Minimum is 0. Maximum is 1.
Adjust Triangle checkbox: Turns on/off triangle adjustment using highest/lowest values within valid higher time frame bars. Default is on.
Detection Algorithm Notes
The detection algorithm recursively selects a higher time frame bar as reference. Then it looks at the consecutive higher time frame bars (as per the requested number of minimum valid bars) as follows:
Ascending Triangle
Low must be higher than previous bar.
Open/close max value must be lower than (or equal to) reference bar high.
When high/low factor criteria is turned on, high must be higher than (or equal to) reference bar open/close max value plus high/low factor proportion of the distance between reference bar high and open/close max value.
Descending Triangle
High must be lower than previous bar.
Open/close min value must be higher than (or equal to) reference bar low.
When high/low factor criteria is turned on, low must be lower than (or equal to) reference bar open/close min value minus high/low factor proportion of the distance between reference bar low and open/close min value.
RunRox - Advanced SMC⭐️ Introducing Our Advanced SMC Indicator: Elevate Your Smart Money Concept Trading
We are excited to present our innovative indicator, specifically designed for the Smart Money Concept (SMC). Our approach goes beyond the traditional SMC strategy by offering significant enhancements that can help you achieve stronger trading performance.
We employ a more sophisticated SMC structure, incorporating improved IDM (Inducement) logic, both internal and external structures, and four types of order blocks. This allows for deeper insights into market trends and a clearer understanding of how major market participants may be manipulating price action.
🟠 Indicator Features:
Structure
HTF Structure – Choose any timeframe and display its structure on your current chart.
CHoCH | BOS | IDM – Display any components from this structure.
Market Minor Structure – Swing and Minor structure.
BOS/CHoCH Breaking by (Body | Wick) – Choose the principle for building the structure, either by the candle body or by their wicks.
BOS/CHoCH Move if Swept – When liquidity is taken, decide whether to move the structure line higher or consider it a structural break.
Move CHoCH/BOS – Relocate key points on the chart if the structure becomes too large.
FVG Concept
HTF FVG – Choose any timeframe from which you want to display FVG on your current chart
Three Types of FVG – Classic FVG, Double FVG, Implied Imbalance
Reaction to FVG – Show the market’s reaction to FVG on the chart
Mitigation Method – Select the fill method that suits your approach (Touch/Midline/Complete)
Remove Filled FVG – Remove FVGs from the chart once they have been filled
Combine FVG – Merge several consecutive FVGs into one
Length FVG – Adjust the number of candles that define the FVG
OrderBlock Concept
HTF OrderBlock – Choose any timeframe from which you want to display orderblocks on your current chart
Swing and Minor Orderblocks – Display only the orderblocks you need, whether from the Swing or Minor structure
Four Types of Order Blocks – Advanced OB, Classic OB, BTS/STB zones, Extremum Candle
Block Based on – Decide whether to base the orderblock on candle highs/lows or candle open/close
Mitigation Method – Define when an orderblock is considered filled (Touch/Midline/Complete)
Remove Blocks Older – Remove older orderblocks from the chart
Hide Overlap – Disable overlapping orderblocks when they appear in the same area
Eat Young Blocks – Reduce the size of an orderblock until it fully forms
Hide Distant Blocks – Remove orderblocks that are too far from the current price
Previous Highs & Lows
Four Level Types – Day, Week, Month, Quarter
Style Customization – Choose line color, line style, and transparency
Fibonacci Retracements
10 Template Options – Ten different bases on which you can build your Fibonacci grid
Up to 7 Levels – Add up to seven Fibonacci levels for your convenience
Fibo Inversion – Option to invert the Fibonacci grid
Style Customization – Choose line colors, line styles, and transparency
Additional Functions
Premium & Discount Zones – A popular concept we’ve incorporated to help identify potential trading areas within premium or discount prices
Equal Highs & Lows – High-liquidity levels where market makers may seek liquidity
Color Candles – Automatically colors candles based on the current trend
Market Structure ZigZag – Offers a clear visual of the zigzag pattern on which the structure is built
Key Point Labels – Displays important swing high/low points directly on the chart
General Styling – Customize any chart element, including size, style, color, and transparency
Alert Customization – Over 16 types of alerts, easily configured in a few clicks. Receive only the notifications you need. Custom alerts are also available for developers.
Next, we will provide a detailed overview of all the indicator’s features, accompanied by chart examples.
📈 Structure
What Is IDM?
IDM, or the Institutional Distribution Model, is an advanced concept within SMC that focuses on how institutional players distribute their positions in the market. By analyzing IDM, traders can better anticipate price movements and potential turning points, thereby gaining a meaningful edge in their trading.
In our structure concept, IDM can form under specific conditions. The market does not always provide a high-liquidity point to work with, so we’ve adopted a flexible approach. We generate IDM when a certain type of liquidity appears during the impulse and BOS break, allowing for a potential future liquidity sweep.
Below, I will provide an example that illustrates when IDM forms as a liquidity magnet within the structure - and when it does not.
As shown in the example above, we focus on the initial impulse after the BOS. If liquidity forms during this impulse - liquidity that needs to be taken out during the structural move - we mark an IDM level as a price magnet. However, if this liquidity does not appear, we do not create an IDM. In that case, the same point might serve as an FVG or play a different role, depending on your trading approach.
This concept makes the structure more flexible and better able to respond immediately to market movements and key structural points.
Above is an example on the chart illustrating what the structure looks like both with and without IDM. As you can see, when the structural move includes pullbacks and consolidation, there is an opportunity to form an IDM as a price magnet. However, if the impulses are strong and lack pullbacks, FVG becomes the only magnet in that move. Depending on the chart, our indicator adapts to the current market conditions and highlights potential liquidity collection points.
📊 Swing and Minor Structure
In the new version of the indicator, the minor structure and the swing structure differ from each other.
Swing structure - In this structure, as mentioned earlier, the IDM concept remains a price magnet and is formed at certain points on the chart if the conditions allow. If these points do not appear, IDM might not form at all.
Minor structure - Here, we have completely removed IDM and only kept BOS and CHoCH for structure formation. We found that for a minor structure, this approach allows faster reactions to trend changes, depending on market movements.
By making these adjustments, we have resolved the main issue of the advanced structure, which was the large distance between BOS and CHoCH that sometimes resulted in a month-long consolidation between these levels. In this version, those problems no longer occur.
If, for some reason, your settings result in a larger swing structure, you can still work with the minor structure using the same POI as in the swing structure. OrderBlock and FVG remain the primary drivers of order flow.
Shown above is a screenshot of the main structure settings you can adjust. These settings are highly flexible and can be tailored to fit a wide range of trading preferences.
⚖️ FVG Concept
A new feature of our indicator is the FVG concept. We automatically detect three types of FVG at the moment, which will be explained below.
FVG - the standard Fair Value Gap
Double FVG - a double FVG, also referred to as BPR (Balanced Price Range)
Implied Imbalance - a type of imbalance that arises from buyer or seller demand
Below, we will look at examples of the FVG types we currently identify.
All price inefficiencies work in real time, immediately appearing on the chart and allowing traders to quickly respond to FVG reactions.
We have also enhanced this concept by displaying FVG reactions on the chart. If an FVG triggers a reaction and the price responds to that range, we highlight it on the chart, so you can recognize the reaction and make timely trading decisions. A screenshot below shows how this looks in practice.
Below is a screenshot illustrating the main settings of this concept, along with detailed descriptions.
📦 OrderBlock Concept
OrderBlocks provide an effective way to identify areas of interest and make informed decisions. We have dedicated significant effort to refining this section’s functionality and have achieved strong results in doing so.
Order Block Types
Advanced OrderBlock – A specialized type of order block generated by our internal algorithm. This can help traders aim for tighter entries and potentially more favorable risk-reward ratios within a narrow price range.
OrderBlock – The classic type, formed at the highs or lows of a structure when a BOS or CHoCH occurs. It can still be an effective entry method but typically spans a wider price range.
Extremum Candle – Based on liquidity grabs. The candle creating this order block must collect liquidity before making an impulsive move that breaks the BOS or CHoCH.
BTS / STB (Buy To Sell / Sell To Buy) – This concept may appear when market makers manipulate price to buy or sell an asset. It often covers a larger price range because it relies on a brief impulsive move to form.
Each type of order block has its own strengths and weaknesses. We provide traders with the flexibility to choose which types suit their trading style and preferences.
Above is an example of how you can apply OrderFlow alongside our structure and orderblocks, which can produce solid results when combined with the Smart Money concept.
In this demonstration, we have highlighted the Advanced Orderblock as an illustration.
Above is a screenshot of all the settings related to this section. They can be customized to suit your specific needs, ensuring you only see what is genuinely relevant on your chart.
📏 Previous Highs and Lows
You can select four levels to display on the chart as some of the most liquid zones:
Daily Highs and Lows
Weekly Highs and Lows
Monthly Highs and Lows
Quarterly Highs and Lows
This feature helps you identify important levels on lower timeframes and focus on these zones for potential trading opportunities. Below is an example of how it appears on the chart.
Below, you can see the settings available in this section.
📐 Fibonacci Levels
Likewise, a new section in our indicator is Fibonacci Levels, a well-known tool recognized as a reliable source of important levels on the chart. We have added this functionality with the option to choose how you want to generate these levels and which specific levels you want to display.
You can plot Fibonacci levels based on the Swing structure, Minor structure, previous or current day, month, and more. In total, there are 10 different options for constructing the Fibonacci grid.
Above, you can see an example of how it appears on the chart, and below you will find the settings available in this section.
🈹 Premium and Discount
Another useful feature for all traders is the Premium and Discount zones based on structure. This makes it easy to identify areas of interest—whether in a discount or premium zone, or in an equilibrium area.
Below, you can also see the settings available in this section.
✅ Additional Function
We have also separated a few functions into their own section:
Color Candles – Colors the candles according to the current trend.
Market Structure ZigZag – Visually highlights the zigzag used to form the structure.
Key Point Labels – Displays the points on the chart from which the structure is built.
Equal Highs & Lows – Identifies equal highs and lows as areas of potential liquidity for larger market players, as price often aims to sweep these zones.
Below are a few screenshots showing how these features appear on the chart.
Color Candles
Market Structure ZigZag and Key Point Labels
Equal Highs & Lows
Below, you can see a screenshot displaying all the settings available in this section.
🎨 General Styling
We have devoted considerable effort to providing flexible customization for each element on the chart, so you can design the exact look you want. That’s why we created an additional section where you can adjust any element’s size, style, and more.
Combined with extensive color and transparency options, this feature provides a flexible appearance for the indicator on any chart.
Below, you can see the settings available in this section
🔔 Alert Customization
You can configure over 16 types of reactions to various events on the chart. Additionally, you can set up alerts to trigger at specific fill levels and explore numerous other alert options, as shown in the screenshot below.
🟠 Usage Examples
We have also prepared several examples of how to use the indicator. These are standard entry models taken from the classic Smart Money concept.
First Example
In the screenshot above, the market displays a downward structure until a manipulation occurs, followed by a CHoCH break. This is a standard entry model featuring an entry at the nearest FVG, a stop-loss placed beyond the manipulation, and a target at the nearest liquidity zone—whether session-based or, as in our case, a gap (one of the FVG types) that price commonly revisits.
This is considered a more aggressive entry because we only waited for a single confirmation of the trend change—the CHoCH break—and then entered immediately afterward. While the WinRate might be lower in such trades, the Risk-Reward ratio is typically very high if you correctly identify the manipulation.
Second Example
This approach is more conservative and less risky, typically offering a higher WinRate but with a lower Risk-Reward ratio.
Here, we use the 4H FVG as our decision point (POI). With the indicator, we plot the 4-hour FVG on our current chart without needing to switch back and forth between timeframes.
Once price reaches our POI, we look for an entry model that includes three confirmations:
First Confirmation – A CHoCH break.
Second Confirmation – A manipulation.
Third Confirmation – A second BOS break.
We wait for all these confirmations before entering the trade, ensuring our stop-loss is well-protected since the remaining liquidity has been swept and the 4-hour FVG has been fully filled.
Our target is the full fill of a higher timeframe FVG or other high-liquidity levels below.
In a conservative setup, it is crucial to allow a complete OrderFlow to develop, including manipulations and clear breaks of lower levels. This approach helps protect the trade and often results in a higher WinRate.
🟠 Disclaimer
Past performance is not indicative of future results. To trade successfully, it is crucial to have a thorough understanding of the market context and the specific situation at hand. Always conduct your own research and analysis before making any trading decisions.
To gain access to the indicator, please review the author's instructions below this post
LevelUp^ Trend Follower All-In-OneLevelUp is an all-in-one collection of the most popular trend following tools merged into one indicator. LevelUp automates many aspects of technical analysis to find and highlight chart patterns and signals based on the principles of William O'Neil, Stan Weinstein, Jesse Livermore and other well-known trend followers.
The 10-EMA, 21-EMA and 50-SMA are foundational in LevelUp. LevelUp uses the term moving average alignment to refer to patterns that meet your specific requirements as it relates to moving averages and their relationship to price and one another. For example, you can request the start of MA alignment begin when the low is > 21-EMA, the 21-EMA is > 50-SMA and the 50-SMA is trending up.
LevelUp includes indicators for intraday, daily and weekly timeframes.
Key Features:
Daily Timeframe:
▪ Configure moving average alignment and preferred price action.
▪ Custom RS Line:
▪ Symbol overlays showing new RS highs.
▪ Custom moving average with optional cloud.
▪ View 10-week SMA on daily chart.
▪ Set exit criteria based on moving averages and % below entry.
▪ Stats table to simplify calculating entry/exit points.
▪ Signals table to quickly view if stock is trending up.
▪ Power trend tools and analysis.
Daily & Weekly Timeframe:
▪ Flat base detection with custom configuration.
▪ Consolidation detection with custom configuration.
▪ Highlight lower lows and lower closes (pullbacks).
▪ Highlight 52-week highs.
Weekly Timeframe:
▪ Customizable tight closes.
▪ Customizable up weeks.
Intraday Timeframe:
▪ View daily 10-EMA, 21-EMA and 50-SMA.
▪ 1-day and 2-day AVWAP.
▪ 5-day moving average.
All Timeframes:
▪ Marked highs/lows with lines showing support/resistance.
▪ Custom moving averages.
Daily Chart Examples
The following charts show a range of examples on customization and features in LevelUp when viewing a daily chart.
Weekly Chart Examples
Weekly charts are helpful for identifying longer-term trends and patterns. Trend followers often limit the number of indicators and signals on a weekly timeframe, making for a cleaner chart with less noise.
Intraday Chart Examples
Daily 10-EMA, 21-EMA and 50-SMA on an intraday chart.
AVWAP and marked highs/lows.
RS Line ~ Relative Strength
The RS Line compares a stock's performance to the S&P 500 index. A rising RS Line means the stock is outperforming the overall market. Another important signal is when the RS Line reaches a new high before price. When this occurs, it indicates strong demand for the stock and may precede a significant price increase as buyers accumulate shares. Both signals are customizable within LevelUp providing multiple visual cues when the required conditions are met.
LevelUp also adds a few unique visuals as it relates to the typical RS Line. Included are options to show symbols on the RS line that represent RS Line new high and RS Line new high before price. This provides an at-a-glance view of the trend. Additionally, LevelUp allows for custom moving averages to be applied to the RS Line as well as an optional cloud to help identify support/resistance levels.
Power Trends
When a power trend is active, there is a stronger than usual uptrend underway. The concept of a power trend was created by Investor's Business Daily (IBD) based on extensive backtesting and historical analysis.
A power trend by definition uses a major index, such as the Nasdaq Composite (IXIC), as the data source for determining a power trend's state, either off or on. The LevelUp indicator builds upon this concept by allowing the current active chart symbol to be the data source for the power trend.
What Starts A Power Trend:
▪ Low is above the 21-day EMA for at least 10 days.
▪ 21-day EMA is above the 50-day SMA for at least five days.
▪ 50-day SMA is in an uptrend.
▪ Close up for the day.
What Ends A Power Trend:
▪ 21-day EMA crosses under 50-day SMA and the close is below prior day close.
▪ Close below the 50-day SMA and low is 10% below recent high.
Important Note: The power trend as created by IBD uses the daily 21-EMA and 50-SMA. Hence, the power trend is only shown when on the daily timeframe.
AVWAP - Anchored VWAP
The Anchored Volume Weighted Average Price (AVWAP) , created by Brian Shannon, is used to assess the average price at which an asset has traded since a specific time, event or milestone. This could be the beginning of a trading day, the release of important news, or any other event deemed significant. By anchoring the VWAP to a specific point in time, it helps market participants analyze how prices have evolved relative to that anchor.
If a stock is above a rising AVWAP, buyers are in control, while a declining AVWAP indicates sellers are in control. By analyzing AVWAP, traders can make informed decisions on timing entries, managing losses and profits, or deciding to stay on the sidelines during periods of market indecision.
Tight Weeks And Up Weeks
William O'Neil primarily focused on weekly charts. Two common patterns he looked for were tight weeks and up weeks.
Tight weeks occur when there are small variations in price from one week to the next. This indicates a lack of supply and accumulation by institutions. You can configure the minimum number of weeks and the maximum % change in price from week to week.
Up weeks are defined as multiple weeks where each close is higher than the previous week. This pattern is often a signal of institutional buying. At a minimum, O'Neil looked for three weeks of upward price action. You can configure the minimum number of up weeks required.
Flat Base
A flat based is relatively tight price action within a range. A flat base takes 5+ weeks (25+ days) to form. Although flat bases are often found after a more significant advance in price, this isn't always the case. With that in mind, LevelUp does not currently have requirements for a prior uptrend while scanning for flat bases.
In a flat base, price declines should be no more than 15% from intraday peak to trough. This is an important distinction, as with a consolidation (see below) the maximum depth is based on the high of first bar that started the base.
Default Requirements:
▪ Daily minimum length: 25 days.
▪ Weekly minimum length: 5 weeks.
▪ Depth maximum: 15% (daily or weekly).
Consolidation
A consolidation differs from a flat base in that the former can be much deeper and last longer. In addition, the fluctuations in price of a flat base are often tighter than a consolidation.
Unlike a flat base, the maximum depth is calculated from the high at the start of the consolidation. The minimum length and maximum depth can be customized for all flat base and consolidation patterns.
Default Requirements:
▪ Daily minimum length: 30 days.
▪ Weekly minimum length: 6 weeks.
▪ Depth maximum: 35% (daily or weekly).
Pullback In Price And Potential Bounce
A pullback occurs when the price declines after an initial advance. This is normal price action as prior support levels are tested. Pullbacks also act as a way to shakeout weak holders before the primary trend resumes.
With LevelUp you specify the type of pullback to track: lower lows, lower closes or both. You also set the minimum number of bars required. Different values can be set for daily and weekly charts. Once your requirements are met, LevelUp will highlight the bar after the pullback is complete. This is often a potential entry/add point.
52-Week Highs
A 52-week high refers to the highest closing price within the past 52 weeks. Trend followers often use the 52-week high as a signal to identify assets with upward momentum, considering it as an indication of a potential trend continuation. This approach assumes that assets that have reached a 52-week high are more likely to experience further price appreciation.
52-week highs can be shown on both weekly and daily charts. You can set the location where the 52-week high symbol is shown: above the bar, below the bar, at the top of the chart or at the bottom of the chart.
Marked Highs And Lows
Marked highs/lows, often referred to as pivot highs/lows, can be helpful to find areas of potential support and resistance. As defined by William O'Neil, on a daily chart, a marked high is the highest high going back nine bars and forward nine bars. The number of days forward/backward is referred to as the period. The same concept applies to finding marked lows.
One benefit of LevelUp marked highs/lows is that you can customize the high and low periods on all timeframes.
There is an additional option when viewing marked highs/lows to see where a breakout occurs. The highlight is shown if the current bar high is above the most recent pivot high.
Comparing Stock Performance
With two or more copies of LevelUp installed, you can configure different settings and compare and contrast how indicators and signals perform relative to one another.
This is a great way to come up with your own custom layout for each timeframe, tailored to your preferences and trading style.
Stats And The Signals Table
The stats and signal tables can be very helpful to see price information and patterns at a glance. For example, you can quickly determine potential stoploss placement based on the distance to/from a moving average. The signals tables show the status of several key trend indicators, including 52-week highs, RS Line new high and RS Line new high before price.
Managing Long Term Trends
Depending on your trading style, there are many ways to take advantage of long term trends. For example, the chart that follows show how an uptrend can be a profitable trade whether holding for the duration or taking shorter term trades along the way.
