TradeDots - Buy Sell SignalsThe TradeDots Buy Sell Indicator is a sophisticated multi-strategy analytics tool designed to discern market direction and identify potential trading opportunities.
The TradeDots indicator utilizes a trend-following strategy that initially identifies the long-term market trend, whether bullish or bearish, at a macro level. It then zooms in on pullback and reversal price action patterns within this broader trend. These patterns are confirmed by a micro-level candlestick analysis, which leads to the issuance of a "buy" alert. This process ensures both macro and micro elements of the market are considered before entering a trade.
How Does It Work?
In more detail, the procedure begins at the macro level where the advanced indicator applies an Exponential Moving Average (EMA) within the current timeframe. This EMA is then cross-verified with another EMA of the same length from a higher timeframe, ensuring a reliable assessment of long-term market trends. This approach helps establish whether the market situation favors long or short positions.
Following this, a complex mathematical model uses a designated window of candlesticks to calculate price action changes, storing all significant reversal patterns for subsequent comparison. The algorithm then identifies similar repeated reversal patterns in the chart, pinpointing potential market turning points.
For precision and reliability, the confirmation of these reversal patterns involves further refinement and filtering at a micro level. By calculating market momentum in tandem with an exhaustive analysis, e.g. Average True Value (ATR), candlestick body and wick data, the algorithm can affirm the reversal. Finally, the buy or sell signals are plotted on the chart in real-time.
The indicator includes 4 distinct entry strategies for both "Long" and "Short" orders. Each strategy represents different levels of rigorousness in their analysis rules. For instance, a "Weak Buy" signal represents a lighter pullback strength compared to a "Strong Buy" signal, with "Reversal Buy" exhibiting the robust pullback strength based on the change in price action value.
Each type of order comes with its minimum threshold and conditions for profit-taking to prevent excessive trading activity that could lead to high commission costs. Once these conditions are met and coupled with a reversal signal — generated with the same concepts as mentioned earlier but in the opposite direction — a sell signal is then triggered in real time. It's a systematic process that ensures an optimal balance between timely entries and exits in the market.
Generating Trading Ideas Catering To Traders Of All Kinds
TradeDots Buy Sell Indicator includes multiple strategies and many features:
4+ Types of Trading Alerts: Strong, Weak, Reversal, and Breakout for different market conditions (Should not be followed blindly).
2+ Trading Styles: Buy and Hold, Swing Trading (Should not be followed blindly).
Facilitates both "Long" and "Short" trades.
+ more. (Check the changelog below for current features)
HOW TO USE
⭐️ TRADING STRATEGY
Buy and Hold: An approach suitable for long-term investments or as an alternative to a dollar-cost averaging strategy by identifying only the undervalued positions in markets with long-term growth potential like stocks and indices.
Note: This strategy does not provide an exit strategy.
Swing Trading: This method targets buying low and selling high, adapted for traders looking to make the most of short to mid-term market volatility.
⭐️ ORDER DIRECTION
Order direction is for “Swing trading” strategy and other strategies that comes with an exit strategy. It is to choose the direction of the market that you wish to place your order on.
Long: Primarily targeting markets that exhibit a left-skewed trend (more often it rises than falls), this strategy focuses on "long" trading opportunities, avoiding "short" market actions.
Short: Apt for markets displaying a right-skewed trend (more often it falls than rises), this approach targets "short" opportunities exclusively, refraining from "long" market actions.
Long and Short: This comprehensive strategy identifies trading opportunities for both "long" and "short" market actions, facilitating increased opportunities for volatile assets.
⭐️ ALERT TYPES
Strong: These alerts designate high risk/reward return opportunities with a reasonable win rate. They tend to appear near previous support pivots where a Change in Character (CoCh) may often occur, typically coupled with a tight stop-loss strategy.
Weak: Indicative of opportunities balancing risk/reward return and win-rate, these alerts often appear during strong momentum markets.
Reversal: These signals identify potential reversals by highlighting extreme oversold or overbought states, thus revealing markets that are underpriced or overpriced for swift trading actions.
Breakout: They are to identify a change in trend and market breakout by gaps created post earnings or significant economic events, purposed for "Buy high, sell higher" strategies.
⭐️ STOP LOSS
The stop-loss feature offers customization options, enabling users to close a position upon reaching a predefined percentage drawdown. As volatility varies across different timeframes and markets, tuning this feature in accordance with the market allows optimal usage of this indicator.
CONCLUSION
While technical indicators are certainly vital in trading analysis, they are just one part of the equation. The individual trader's style and mindset significantly influence their trading outcomes, making them equally crucial in the process. Therefore, relying solely on indicators for a successful trading outcome may not be the most effective strategy.
Understanding and leveraging these indicators requires substantial time and significant effort from traders. They need to deeply engage with these tools to truly grasp their behavior and functionality. Taking this into consideration, our aim is to create highly advanced, customizable, and user-friendly technical indicators. This tool is designed to illuminate the fundamental role that technical indicators play as a supportive decision-making apparatus, aiding traders to more swiftly embark on their journey towards successful trading.
See Author's instructions below to get instant access to this indicator.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Cerca negli script per "swing trading"
Alpha Time Zones {DCAquant}
Alpha Time Zones {DCAquant}
The Alpha Time Zones {DCAquant} is a versatile TradingView indicator designed to help traders navigate the markets by highlighting key trading sessions. This tool provides visual cues by color-coding periods of the London, New York, and Tokyo trading sessions, along with customizable 'Golden' zones, enabling traders to capitalize on market overlaps and increased volatility.
Key Features:
Global Trading Sessions: Automatically shades the periods of the major trading sessions, which can be critical for traders looking to trade during peak liquidity times.
Customizable 'Golden' Zone: Set up your own 'Golden' trading hours for personalized time frames where you observe increased market activity.
Clarity and Focus: By color-coding each session, the indicator allows for a clean and organized view of the market, enabling traders to focus on their strategies without distraction.
BTC Halving Dates and Countdown: For cryptocurrency traders, this indicator includes a feature to show Bitcoin halving dates and a countdown to the next event, assisting in speculation around these significant occurrences.
How to Use the Indicator:
Optimized for Shorter Timeframes: Alpha Time Zones {DCAquant} is fine-tuned for high timeframe charts up to 12 hours. It's designed to provide the most value for intraday to half-day chart intervals, which aligns well with the duration of trading sessions around the globe.
Session Overlaps: Identify times when key sessions overlap, such as the London-New York overlap, to exploit potential periods of increased liquidity and volatility—prime times for trading on lower timeframes.
Custom 'Golden' Zone Trading: Define your own 'Golden' trading hours to correspond with specific economic releases or your peak trading times, perfect for strategies that target times of intensified market action.
Strategic Halving Date Analysis: Utilize the indicator’s Bitcoin halving dates and countdown feature to make informed decisions around these pivotal events, particularly relevant to cryptocurrency traders focusing on macro timeframes.
Adaptability and Customization: While the indicator is not intended for use on timeframes longer than 12 hours, its flexible settings allow for toggling session displays and customizing the 'Golden' zone, making it a versatile companion to your trading system.
Trading Strategy Integration:
The Alpha Time Zones {DCAquant} indicator is designed to be an auxiliary tool, easily integrated into any trading strategy that emphasizes trading session dynamics. Whether you're day trading, swing trading, or taking a position based on economic announcements, this indicator adapts to your approach, providing clear visual markers of key trading hours.
Disclaimer:
This indicator does not predict market movements but instead serves as a guide to understand the timing of market activities. Traders should use this tool in conjunction with a comprehensive analysis and a robust risk management strategy.
Adaptive Moving Average (AMA) Signals (Zeiierman)█ Overview
The Adaptive Moving Average (AMA) Signals indicator, enhances the classic concept of moving averages by making them adaptive to the market's volatility. This adaptability makes the AMA particularly useful in identifying market trends with varying degrees of volatility.
The core of the AMA's adaptability lies in its Efficiency Ratio (ER), which measures the directionality of the market over a given period. The ER is calculated by dividing the absolute change in price over a period by the sum of the absolute differences in daily prices over the same period.
⚪ Why It's Useful
The AMA Signals indicator is particularly useful because of its adaptability to changing market conditions. Unlike static moving averages, it dynamically adjusts, providing more relevant signals that can help traders capture trends earlier or identify reversals with greater accuracy. Its configurability makes it suitable for various trading strategies and timeframes, from day trading to swing trading.
█ How It Works
The AMA Signals indicator operates on the principle of adapting to market efficiency through the calculation of the Efficiency Ratio (ER), which measures the directionality of the market over a specified period. By comparing the net price change to total price movements, the AMA adjusts its sensitivity, becoming faster during trending markets and slower during sideways markets. This adaptability is enhanced by a gamma parameter that filters signals for either trend continuation or reversal, making it versatile across different market conditions.
change = math.abs(close - close )
volatility = math.sum(math.abs(close - close ), n)
ER = change / volatility
Efficiency Ratio (ER) Calculation: The AMA begins with the computation of the Efficiency Ratio (ER), which measures the market's directionality over a specified period. The ER is a ratio of the net price change to the total price movements, serving as a measure of the efficiency of price movements.
Adaptive Smoothing: Based on the ER, the indicator calculates the smoothing constants for the fastest and slowest Exponential Moving Averages (EMAs). These constants are then used to compute a Scaled Smoothing Coefficient (SC) that adapts the moving average to the market's efficiency, making it faster during trending periods and slower in sideways markets.
Signal Generation: The AMA applies a filter, adjusted by a "gamma" parameter, to identify trading signals. This gamma influences the sensitivity towards trend or reversal signals, with options to adjust for focusing on either trend-following or counter-trend signals.
█ How to Use
Trend Identification: Use the AMA to identify the direction of the trend. An upward moving AMA indicates a bullish trend, while a downward moving AMA suggests a bearish trend.
Trend Trading: Look for buy signals when the AMA is trending upwards and sell signals during a downward trend. Adjust the fast and slow EMA lengths to match the desired sensitivity and timeframe.
Reversal Trading: Set the gamma to a positive value to focus on reversal signals, identifying potential market turnarounds.
█ Settings
Period for ER calculation: Defines the lookback period for calculating the Efficiency Ratio, affecting how quickly the AMA responds to changes in market efficiency.
Fast EMA Length and Slow EMA Length: Determine the responsiveness of the AMA to recent price changes, allowing traders to fine-tune the indicator to their trading style.
Signal Gamma: Adjusts the sensitivity of the filter applied to the AMA, with the ability to focus on trend signals or reversal signals based on its value.
AMA Candles: An innovative feature that plots candles based on the AMA calculation, providing visual cues about the market trend and potential reversals.
█ Alerts
The AMA Signals indicator includes configurable alerts for buy and sell signals, as well as positive and negative trend changes.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Candlestick Bias OscillatorCandlestick Bias Oscillator (CBO)
The Candlestick Bias Oscillator (CBO) with Signal Line is a pioneering indicator developed for the TradingView platform, designed to offer traders a nuanced analysis of market sentiment through the unique lens of candlestick patterns. This indicator stands out by merging traditional concepts of price action analysis with innovative mathematical computations, providing a fresh perspective on trend detection and potential market reversals.
Originality and Utility
At the core of the CBO's originality is its method of calculating the bias of candlesticks. Unlike conventional oscillators that may rely solely on closing prices or high-low ranges, the CBO incorporates both the body and wick of candlesticks into its analysis. This dual consideration allows for a more rounded understanding of market sentiment, capturing both the directional momentum and the strength of price rejections within a single oscillator.
Mathematical Foundations
1. Body Bias: The CBO calculates the body bias by assessing the relative position of the close to the open within the day's range, scaled to a -100 to 100 range. This calculation reflects the bullish or bearish sentiment of the market, based on the day's closing momentum.
Body Bias = (Close−Open)/(High−Low) x 100
Wick Bias: Similarly, the wick bias calculation takes into account the lengths of the upper and lower wicks, indicating rejection levels beyond the body's close. The balance between these wicks is scaled similarly to the body bias, offering insight into the market's indecision or rejection of certain price levels.
Wick Bias=(Lower Wick−Upper Wick)/(Total Wick Length) × 100
3. Overall Bias and Oscillator: By averaging the body and wick biases, the CBO yields an overall bias score, which is then smoothed over a user-defined period to create the oscillator. This oscillator provides a clear visual representation of the market's underlying sentiment, smoothed to filter out the noise.
4. Signal Line: A secondary smoothing of the oscillator creates the signal line, offering a trigger for potential trading signals when the oscillator crosses this line, indicative of a change in market momentum.
How to Use the CBO:
The CBO is versatile, suitable for various trading strategies, including scalping, swing trading, and long-term trend following. Traders can use the oscillator and signal line crossovers as indications for entry or exit points. The relative position of the oscillator to the zero line further provides insight into the prevailing market bias, enabling traders to align their strategies with the broader market sentiment.
Why It Adds Value:
The CBO's innovative approach to analyzing candlestick patterns fills a gap in the existing array of TradingView indicators. By providing a detailed analysis of both candle bodies and wicks, the CBO offers a more comprehensive view of market sentiment than traditional oscillators. This can be particularly useful for traders looking to gauge the strength of price movements and potential reversal points with greater precision.
Conclusion:
The Candle Bias Oscillator with Signal Line is not just another addition to the plethora of indicators on TradingView. It represents a significant advancement in the analysis of market sentiment, combining traditional concepts with a novel mathematical approach. By offering a deeper insight into the dynamics of candlestick patterns, the CBO equips traders with a powerful tool to navigate the complexities of the market with increased confidence.
Explore the unique insights provided by the CBO and integrate it into your trading strategy for a more informed and nuanced market analysis.
RMB - High and LowDescription:
Introducing the "RMB - High and Low" indicator, a versatile and powerful tool designed for traders who seek a comprehensive view of the market across multiple time frames. This indicator is tailored to identify and display key support and resistance levels, adapting to your chosen time frame - from as short as 15 minutes to as long as a week.
Key Features:
Multi-Time Frame Flexibility : Easily switch between 15 minutes, 30 minutes, 1 hour, 2 hours, 4 hours, daily, and weekly time frames to align with your trading strategy and market analysis.
Dynamic Support and Resistance Levels : The indicator plots the highest high (resistance) and the lowest low (support) for the selected time frame, providing real-time insights into market behavior and potential pivot points.
Time Frame-Specific Labels : Each resistance and support line is labeled with the corresponding time frame, offering a clear and immediate reference, enhancing your chart analysis and decision-making process.
User-Friendly Interface : A simple and intuitive input interface allows for quick adjustments, making it easy to toggle between different time frames based on your trading needs.
Visual Clarity : Designed with distinct color coding - green for resistance and red for support - ensuring that key levels are easily identifiable at a glance.
Ideal Use Cases:
Day Trading: Utilize shorter time frames to capture quick market movements and identify intraday pivot points.
Swing Trading: Leverage longer time frames to understand broader market trends and establish entry and exit points.
Diverse Strategies: Whether you're scalping, trend following, or employing mean reversion tactics, adapt the indicator to fit your unique approach.
Conclusion:
The "RMB - High and Low" indicator is a must-have tool for traders who demand flexibility and precision in their technical analysis. By offering insights across various time frames, this indicator empowers you to make well-informed decisions, adapt to market changes swiftly, and enhance your trading performance.
VIPER DOPING - A Volume Profile to estimate trend probabilityDESCRIPTION :
VIPER DOPING uses volume analysis to help trader to understand trading keys below:
Support and Resistance
Profit and Loss
Estimate candle direction
Trend
Biggest Buy and Sell on level prices
HOW TO USE:
The volume bar will have buy and sell colors, by default the buy color is blue and the sell is red. The size of bar is important matter, the biggest bar size means that price level has strong volume or transaction and the smallest bar size indicates the lowest transaction or volume. How to read it?
The bar above the candle is the resistance
The bar below the candle is the support
If you want long the market, find the biggest or bigger support, which is below the candle
If you want short the market, find the biggest or bigger resistance which is above the candle
Trading style and the maximum range (total candle), default is 60. This setup to analyze volumes in specific candle range. Please check the following recommendation based on trading style:
Scalping: 30 - 60 candles, recommendation timeframe: 5m - 1h
Day Trading: 50 - 120 candles, recommendation timeframe: 30m - 4h
Swing Trading: 100- 240 candles, recommendation timeframe: 1h- 3D
The white box is to visualize trading area by total candle. Every line has the meaning:
The left line is the start candle
The right line is the end candle
The top line is the highest price of volume profile
The bottom line is the lowest price of volume profile
The fibonacci line will help you to confirm and compare of supports and resistances with the volume profile lines.
The TABLE CELLS
it contains information to help trader to understand the recent situation of market and to take strategy of trading:
Total Candle : the maximum candles are used to analyze the volume from previous active candle
Biggest Sell : the horizontal price area which has the largest of sell volume of the last total candle
Biggest Buy : the horizontal price area which has the largest of buy volume of the last total candle
Buy Rate : the ratio of buy and sell volume of the last total candle
Support: the closest price to be the support from the active candle, auto changed if support to be invalid
Resistance : the closest price to be the resistance from the active candle, auto changed if support to be invalid
PnL : the percentage profit if you trade using the support and resistance prices and it can be used for Risk Management. Wisely the risk is 50% of the profit, example if the profit 1% the your risk should be 0.5% from entry.
Estimate : to analize the next direction of candle or target, it will be changed automatically by volume condition.
CONFIGURATION:
Table Position : You can change the table position to top or bottom, to left, right or center
Calculation : You can include the active candle in volume calculation or you can choose the behind active candle. If you use active candle, there could be possible repainting.
The volume profile configuration is about appearance configuration, to setup the thickness, colors, position.
The fibonacci configuration is about appearance configuration, to setup the thickness, extend lines, label styles.
W and M Pattern Indicator- SwaGThis is a TradingView indicator script that identifies potential buy and sell signals based on ‘W’ and ‘M’ patterns in the Relative Strength Index (RSI). It provides visual alerts and draws horizontal lines to indicate potential trade entry points.
User Manual:
Inputs: The script takes two inputs - an upper limit and a lower limit. The default values are 70 and 40, respectively.
RSI Calculation: The script calculates the RSI based on the closing prices of the last 14 periods.
Pattern Identification: It identifies ‘W’ patterns when the RSI makes a higher low within the lower limit, and ‘M’ patterns when the RSI makes a lower high within the upper limit.
Visual Alerts: The script plots these patterns on the chart. ‘W’ patterns are marked with small green triangles below the bars, and ‘M’ patterns are marked with small red triangles above the bars.
Trade Entry Points: A horizontal line is drawn at the high or low of the candle to represent potential trade entry points. The line starts from one bar to the left and extends 10 bars to the right.
Trading Strategy:
For investing, use a weekly timeframe.
For swing trading, use a daily timeframe.
For intraday trading, use a 5 or 15-minute timeframe. Only consider sell-side signals for intraday trading.
Take a buy position if the high breaks above the green line or sell if the low breaks below the red line.
Use recent signals only and avoid signals that are too old.
Swing highs or lows will be your stop-loss level.
Always think about your stop-loss before entering a trade, not your target.
Avoid trades with a large stop-loss.
Remember, this script is a tool to aid in your trading decisions. Always test your strategies thoroughly before live trading. Happy trading! 😊
Trend Correlation HeatmapHello everyone!
I am excited to release my trend correlation heatmap, or trend heatmap for short.
Per usual, I think its important to explain the theory before we get into the use of the indicator, so let's get into the theory!
The theory:
So what is a correlation?
Correlation is the relationship one variable has to another. Correlations are the basis of everything I do as a quantitative trader. From the correlation between the same variables (i.e. autocorrelation), the correlation between other variables (i.e. VIX and SPY, SPY High and SPY Low, DXY and ES1! close, etc.) and, as well, the correlation between price and time (time series correlation).
This may sound very familiar to you, especially if you are a user, observer or follower of my ideas and/or indicators. Ninety-five percent of my indicators are a function of one of those three things. Whether it be a time series based indicator (i.e.my time series indicator), whether it be autocorrelation (my autoregressive cloud indicator or my autocorrelation oscillator) or whether it be regressive in nature (i.e. my SPY Volume weighted close, or even my expected move which uses averages in lieu of regressive approaches but is foundational in regression principles. Or even my VIX oscillator which relies on the premise of correlations between tickers.) So correlation is extremely important to me and while its true I am more of a regression trader than anything, I would argue that I am more of a correlation trader, because correlations are the backbone of how I develop math models of stocks.
What I am trying to stress here is the importance of correlations. They really truly are foundational to any type of quantitative analysis for stocks. And as such, understanding the current relationship a stock has to time is pivotal for any meaningful analysis to be conducted.
So what is correlation to time and what does it tell us?
Correlation to time, otherwise known and commonly referred to as "Time Series", is the relationship a ticker's price has to the passing of time. It is displayed in the traditional Pearson Correlation Coefficient or R value and can be any value from -1 (strong negative relationship, i.e. a strong downtrend) to + 1 (i.e. a strong positive relationship, i.e. a strong uptrend). The higher or lower the value the stronger the up or downtrend is.
As such, correlation to time tells us two very important things. These are:
a) The direction of the stock; and
b) The strength of the trend.
Let's take a look at an example:
Above we have a chart of QQQ. We can see a trendline that seems to fit well. The questions we ask as traders are:
1. What is the likelihood QQQ breaks down from this trendline?
2. What is the likelihood QQQ continues up?
3. What is the likelihood QQQ does a false breakdown?
There are numerous mathematical approaches we can take to answer these questions. For example, 1 and 2 can be answered by use of a Cumulative Distribution Density analysis (CDDA) or even a linear or loglinear regression analysis and 3 can be answered, more or less, with a linear regression analysis and standard error ascertainment, or even just a general comparison using a data science approach (such as cosine similarity or Manhattan distance).
But, the reality is, all 3 of these questions can be visualized, at least in some way, by simply looking at the correlation to time. Let's look at this chart again, this time with the correlation heatmap applied:
If we look at the indicator we can see some pivotal things. These are:
1. We have 4, very strong uptrends that span both higher AND lower timeframes. We have a strong uptrend of 0.96 on the 5 minute, 50 candle period. We have a strong uptrend at the 300 candle lookback period on the 1 minute, we have a strong uptrend on the 100 day lookback on the daily timeframe period and we have a strong uptrend on the 5 minute on the 500 candle lookback period.
2. By comparison, we have 3 downtrends, all of which have correlations less than the 4 uptrends. All of the downtrends have a correlation above -0.8 (which we would want lower than -0.8 to be very strong), and all of the uptrends are greater than + 0.80.
3. We can also see that the uptrends are not confined to the smaller timeframes. We have multiple uptrends on multiple timeframes and both short term (50 to 100 candles) and long term (up to 500 candles).
4. The overall trend is strengthening to the upside manifested by a positive Max Change and a Positive Min change (to be discussed later more in-depth).
With this, we can see that QQQ is actually very strong and likely will continue at least some upside. If we let this play out:
We continued up, had one test and then bounced.
Now, I want to specify, this indicator is not a panacea for all trading. And in relation to the 3 questions posed, they are best answered, at least quantitatively, not only by correlation but also by the aforementioned methods (CDDA, etc.) but correlation will help you get a feel for the strength or weakness present with a stock.
What are some tangible applications of the indicator?
For me, this indicator is used in many ways. Let me outline some ways I generally apply this indicator in my day and swing trading:
1. Gauging the strength of the stock: The indictor tells you the most prevalent behavior of the stock. Are there more downtrends than uptrends present? Are the downtrends present on the larger timeframes vs uptrends on the shorter indicating a possible bullish reversal? or vice versa? Are the trends strengthening or weakening? All of these things can be visualized with the indicator.
2. Setting parameters for other indicators: If you trade EMAs or SMAs, you may have a "one size fits all" approach. However, its actually better to adjust your EMA or SMA length to the actual trend itself. Take a look at this:
This is QQQ on the 1 hour with the 200 EMA with 200 standard deviation bands added. If we look at the heatmap, we can see, yes indeed 200 has a fairly strong uptrend correlation of 0.70. But the strongest hourly uptrend is actually at 400 candles, with a correlation of 0.91. So what happens if we change the EMA length and standard deviation to 400? This:
The exact areas are circled and colour coded. You can see, the 400 offers more of a better reference point of supports and resistances as well as a better overall trend fit. And this is why I never advocate for getting married to a specific EMA. If you are an EMA 200 lover or 21 or 51, know that these are not always the best depending on the trend and situation.
Components of the indicator:
Ah okay, now for the boring stuff. Let's go over the functionality of the indicator. I tried to keep it simple, so it is pretty straight forward. If we open the menu here are our options:
We have the ability to toggle whichever timeframes we want. We also have the ability to toggle on or off the legend that displays the colour codes and the Max and Min highest change.
Max and Min highest change: The max and min highest change simply display the change in correlation over the previous 14 candles. An increasing Max change means that the Max trend is strengthening. If we see an increasing Max change and an increasing Min change (the Min correlation is moving up), this means the stock is bullish. Why? Because the min (i.e. ideally a big negative number) is going up closer to the positives. Therefore, the downtrend is weakening.
If we see both the Max and Min declining (red), that means the uptrend is weakening and downtrend is strengthening. Here are some examples:
Final Thoughts:
And that is the indicator and the theory behind the indicator.
In a nutshell, to summarize, the indicator simply tracks the correlation of a ticker to time on multiple timeframes. This will allow you to make judgements about strength, sentiment and also help you adjust which tools and timeframes you are using to perform your analyses.
As well, to make the indicator more user friendly, I tried to make the colours distinctively different. I was going to do different shades but it was a little difficult to visualize. As such, I have included a toggle-able legend with a breakdown of the colour codes!
That's it my friends, I hope you find it useful!
Safe trades and leave your questions, comments and feedback below!
GKD-C Variety Stepped, Variety Filter [Loxx]Giga Kaleidoscope GKD-C Variety Stepped, Variety Filter 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 Stochastic 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: Variety Stepped, Variety Filter 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 Variety Stepped, Variety Filter
Variety Stepped, Variety Filter is an indicator that uses various types of stepping behavior to reduce false signals. This indicator includes 5+ volatility stepping types and 60+ moving averages.
Stepping calculations
First off, you can filter by both price and/or MA output. Both price and MA output can be filtered/stepped in their own way. You'll see two selectors in the input settings. Default is ATR ATR. Here's how stepping works in simple terms: if the price/MA output doesn't move by X deviations, then revert to the price/MA output one bar back.
ATR
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.
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 σ 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. And added to that, 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 standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
See how this compares to Standard Devaition here:
Adaptive Deviation
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, I used a manual recreation of the quantile function in Pine Script. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is widely used indicator in many occasions for technical analysis . It is calculated as the RMA of true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range
See how this compares to ATR here:
ER-Adaptive ATR
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.
For Pine Coders, this is equivalent of using ta.dev()
Included Filters
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
Ehlers Optimal Tracking Filter - EOTF
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
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
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
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
Description. 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
Ehlers Optimal Tracking Filter - EOTF
The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving
Average
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
T3 is basically an EMA on steroids, You can read about T3 here:
T3 Striped
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.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Kalman Filter
Kalman filter is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies. This means that the filter was originally designed to work with noisy data. Also, it is able to work with incomplete data. Another advantage is that it is designed for and applied in dynamic systems; our price chart belongs to such systems. This version is true to the original design of the trade-ready Kalman Filter where velocity is the triggering mechanism.
Kalman Filter is a more accurate smoothing/prediction algorithm than the moving average because it is adaptive: it accounts for estimation errors and tries to adjust its predictions from the information it learned in the previous stage. Theoretically, Kalman Filter consists of measurement and transition components.
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.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness.
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"
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.
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.
Unicorn QuantDeeply customizable trading algorithm with instant backtesting. It emulates real trading and displays all the actions it takes on the chart. For example, it shows when to enter or partially close a position, move Stop-Loss to breakeven, etc. The user can replicate these actions in their trading terminal in real time. The algorithm uses up to three Take-Profit levels, and a Stop-Loss level that can move in a trade to protect the floating profit.
The script can send real-time alerts to the user’s Email and to the cell phone via notifications in the TradingView app.
The indicator is designed to be used on all timeframes, including lower ones for intraday trading and scalping.
HOW TO USE
Set the Stop-Loss and up to three Take-Profit levels. Choose the rules for moving the Stop-Loss level in a trade. Adjust the sensitivity of the trading signals. And check the backtest result in the Instant Backtesting dashboard. If the performance of the strategy satisfies you, proceed with the forward testing or live trading.
When using this script, please, keep in mind that past results do not necessarily reflect future results and there are many factors that influence trading results.
FEATURES
Trading Signals
The feature calculates Buy and Sell signals for trend or swing trading. The user can change the Sensitivity parameter to control the frequency of the signals. This allows them to be adjusted for different markets and timeframes.
Position Manager
To make the Position Manager setup as easy as possible, the algorithm calculates Stop-Loss and Take-Profit levels in Average True Range (ATR) units. They are self-adjusting for any market and timeframe, since they account for its average volatility .
You don't have to worry about what market you are trading - Forex, Stocks, Crypto, etc. With the self-adjusting Stop-Loss and Take-Profit, you can find settings that work for one market and use the same numerical values as a starting point for a completely different market.
Instant Backtesting
After changing any settings, you can immediately see the performance of the strategy on the Instant Backtesting panel. Two metrics are displayed there - the percentage of profitable trades and the total return. This information, as well as the historical trades shown on the chart, will help you quickly and easily evaluate the settings.
SETTINGS
TRADING SIGNALS
Sensitivity - controls the sensitivity of the trading signals algorithm. It determines the frequency of the trading signals. The higher the value of this parameter, the less trading signals you get and the longer trends the algorithm tries to catch. The lower the sensitivity value, the more signals you receive. This can be useful if you want to profit from small price movements.
POSITION MANAGER
SL - sets the Stop-Loss level measured in ATR units.
TP1, TP2, TP3 - set the Take-Profit levels measured in the ATR units.
Close % at TP1, Close % at TP2, Close % at TP3 - set portions of the open position (as a percentage of the initial order size) to close at each of the TP levels.
At TP1 move SL to, At TP2 move SL to - set the rules for moving the Stop-Loss level in an open trade to protect the floating profit.
Show Open Position Dashboard - turns on/off a dashboard that shows the current Stop-Loss and Take-Profit levels for the open position.
BACKTESTING
Use Starting Date - turns on/off the starting date for the strategy and backtests. When off, all available historical data is used.
Starting Date - sets the starting date for the strategy and backtests.
Show Instant Backtesting Dashboard - turns on/off a dashboard that shows the current strategy performance: the percentage of profitable trades and total return.
Leverage - sets the leverage that the strategy uses.
Auto Fibonacci Retracement - Real-Time (Expo)█ Fibonacci retracement is a popular technical analysis method to draw support and resistance levels. The Fibonacci levels are calculated between 2 swing points (high/low) and divided by the key Fibonacci coefficients equal to 23.6%, 38.2%, 50%, 61.8%, and 100%. The percentage represents how much of a prior move the price has retraced.
█ Our Auto Fibonacci Retracement indicator analyzes the market in real-time and draws Fibonacci levels automatically for you on the chart. Real-time fib levels use the current swing points, which gives you a huge advantage when using them in your trading. You can always be sure that the levels are calculated from the correct swing high and low, regardless of the current trend. The algorithm has a trend filter and shifts the swing points if there is a trend change.
The user can set the preferred swing move to scalping, trend trading, or swing trading. This way, you can use our automatic fib indicator to do any trading. The auto fib works on any market and timeframe and displays the most important levels in real-time for you.
█ This Auto Fib Retracement indicator for TradingView is powerful since it does the job for you in real-time. Apply it to the chart, set the swing move to fit your trading style, and leave it on the chart. The indicator does the rest for you. The auto Fibonacci indicator calculates and plots the levels for you in any market and timeframe. In addition, it even changes the swing points based on the current trend direction, allowing traders to get the correct Fibonacci levels in every trend.
█ How does the Auto Fib Draw the levels?
The algorithm analyzes the recent price action and examines the current trend; based on the trend direction, two significant swings (high and low) are identified, and Fibonacci levels will then be plotted automatically on the chart. If the algorithm has identified an uptrend, it will calculate the Fibonacci levels from the swing low and up to the swing high. Similarly, if the algorithm has identified a downtrend, it will calculate the Fibonacci levels from the swing high and down to the swing low.
█ HOW TO USE
The levels allow for a quick and easy understanding of the current Fibonacci levels and help traders anticipate and react when the price levels are tested. In addition, the levels are often used for entries to determine stop-loss levels and to set profit targets. It's also common for traders to use Fibonacci levels to identify resistance and support levels.
Traders can set alerts when the levels are tested.
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Disclaimer
Copyright by Zeiierman.
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Moving Average Filters Add-on w/ Expanded Source Types [Loxx]Moving Average Filters Add-on w/ Expanded Source Types is a conglomeration of specialized and traditional moving averages that will be used in most of indicators that I publish moving forward. There are 39 moving averages included in this indicator as well as expanded source types including traditional Heiken Ashi and Better Heiken Ashi candles. You can read about the expanded source types clicking here . About half of these moving averages are closed source on other trading platforms. This indicator serves as a reference point for future public/private, open/closed source indicators that I publish to TradingView. Information about these moving averages was gleaned from various forex and trading forums and platforms as well as TASC publications and other assorted research publications.
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Included moving averages
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.
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.
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.
Hull Moving Average - HMA
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.
IE/2 - Early T3 by Tim Tilson
The IE/2 is a Moving Average that uses Linear Regression slope in its calculation to help with smoothing. It's a worthy Moving Average on it's own, even though it is the precursor and very early version of the famous "T3 Indicator".
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.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and it's smoothness.
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 price 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.
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 weight 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.
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 tomorrows price.
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 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 a 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 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.
The TMA and Sine Weighted Moving Average Filter are almost identical at times.
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, it's 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.
Volume Weighted EMA - VEMA
Utilizing tick volume in MT4 (or real volume in MT5), this EMA will use the Volume reading in its decision to plot its moves. The more Volume it detects on a move, the more authority (confirmation) it has. And this EMA uses those Volume readings to plot its movements.
Studies show that tick volume and real volume have a very strong correlation, so using this filter in MT4 or MT5 produces very similar results and readings.
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.
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What are Heiken Ashi "better" candles?
The "better formula" was proposed in an article/memo by BNP-Paribas (In Warrants & Zertifikate, No. 8, August 2004 (a monthly German magazine published by BNP Paribas, Frankfurt), there is an article by Sebastian Schmidt about further development (smoothing) of Heikin-Ashi chart.)
They proposed to use the following:
(Open+Close)/2+(((Close-Open)/( High-Low ))*ABS((Close-Open)/2))
instead of using :
haClose = (O+H+L+C)/4
According to that document the HA representation using their proposed formula is better than the traditional formula.
What are traditional Heiken-Ashi candles?
The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise.
Heikin-Ashi charts, developed by Munehisa Homma in the 1700s, share some characteristics with standard candlestick charts but differ based on the values used to create each candle. Instead of using the open, high, low, and close like standard candlestick charts, the Heikin-Ashi technique uses a modified formula based on two-period averages. This gives the chart a smoother appearance, making it easier to spots trends and reversals, but also obscures gaps and some price data.
Expanded generic source types:
Close = close
Open = open
High = high
Low = low
Median = hl2
Typical = hlc3
Weighted = hlcc4
Average = ohlc4
Average Median Body = (open+close)/2
Trend Biased = (see code, too complex to explain here)
Trend Biased (extreme) = (see code, too complex to explain here)
Included:
-Toggle bar color on/off
-Toggle signal line on/off
RobocanThis script is equipped with
🔵 Robo 2
It offers strategic trading entry and exit points. Truly unique tool for technical analysis for the financial market as it includes calculation of specific metrics like MACD, ATR and RSI.
🔵 Bull & Bear
The signal can be a fairly valuable tool. Momentum is one of those aspects of the market that is crucial to understanding price movements, yet it is so hard to get a solid grip on. It can be used in some instances to generate quality signals but much like with any signal generating indicator, it should be used with caution.
When indicator gives you " Bull " signal , short term momentum is now rising faster than the long term momentum. This can present a bullish buying opportunity.
When indicator gives you "Bear " signal, short term momentum is now falling faster then the long term momentum. This can present a bearish selling opportunity.
🔵 Robo's Cloud
The indicator inspired from Ichimoku CLoud, it uses an unique formula to generate clouds on its own system!
" BUY or ENTER "when the price breaks the Cloud in the direction of the breakout (UP ) and the cloud turns to green colour. Stay in the market until the cloud turns to red colour. Let's assume that You are a swing trader and use 1D candles as long as The candle is above the "green " cloud , you should continue with a trend! No need to hurry to sell until you see the " red " cloud.
🔵 Super Robo
It can perform greatly in a bull and bear market
It's unique algorithm find profitable coins based on "Early Bird + Buy 2 + Volume "gives you ENTRY and EXIT ideas
It works perfectly on the 1W - 3D - 1D charts
🔵 Hell & Moon
When the “Moon or Hell “closes below top of the closing price, a Moon - Buy signal is generated
It works perfectly on the 1W - 1D - 3H charts
🔵 Early Bird Signals
Being an early bird rather than a night owl will naturally lead you to become more successful in trading. There is no secret magic formula to success; this is something you must accept. Trading success is the result of a ‘simple’ list made up of four things: hard work, timing, persistence , and a good dose of Early Bird signals.
it provides high risk & high reward opportunities.
Dont use more than 3 Robo signals at the same time on the chart. Why?
Example, Robo 2 already included 3 different indicators in the formula.
Robo 2 : Truly unique tool for technical analysis for the financial market as it includes calculation of specific metrics like SAR + MACD + Price Movement that gives you ENTRY and EXIT ideas ( Buy 2 & Sell 2 )
If you use more than 3 robo signals, you try to use around " 10 - 12 " different indicators at the same time!
DON'T DO IT!
To get maximum results from your robo advisors, follow the advice below ;
A ) 3 robo signals
B ) 3 robo signals + 1 side strategy
A or B + Pick one bonus below
Dynamic Support Resistance,
Fibonacci Levels
Pivot Support Resistance
Robo signals :
Robo 1
Robo 2
Super EngineeringRobo
Robo 3
Robo 4
Bull & Bear
Hell & Moon
Early Bird
EngineeringRobo's cloud
Ultimate MA crossover strategy
Side strategies :
McGinley Dynamic
Bollinger Bands Strategy
MA 20 & MA 50
MA 50 & MA 200
EMA Trendlines
Robo ( 2 + 3 ) shows you that if the signals are covering each other. So, It is good to keep open it when you use Robo 2 and Robo 3 at the same time.
If you are following any signals, you should always wait for the candle close before buying or selling.
The signal can come and go anytime during the live candle. ALL indicators do that, that is not considered repainting.
Repainting is when a signal appears, the candle is closed, and when you refresh the chart it disappeared. It is logical that until the candle is closed the signal is not decided yet, hence the alert setup as Once per bar Close.
Deluxe never repaints! Yes, you heard it right: you will never have to worry about signal changing after the candle is closed.
________________________________________________________________________Timeframes_____________________________________________________________________
Our recommendations to get the best results:
Swing Trading Crypto : Use 1D Time Frame Candles
Swing Trading Stocks : Use 1W Time Frame Candles
Swing Trading Commodities : Use 1W Time Frame Candles
Day Trading Crypto : Use 3H Time Frame Candles
Day Trading Stocks : Use 1D Time Frame Candles
Day Trading Commodities : Use 1D Time Frame Candles
Not recommended any other time frames.
It gives you all the tools and information you need for day-to-day trading and investing, while also keeping a great buy and sell signals! No excuse to lose in any financial market anymore! Try now!
How can you add the algorithm into your chart?
1. Login to TradingView.com
2. From the homepage, click on ‘Chart’ in the top navigation bar
3. Select “Indicators” on the top-center-middle panel
4. In the indicator library, type "Robocan "
5. Use the website link below to obtain access to this indicator
INTRADAY/SWING TRADING - 3 EMASEstimados/as inversores:
Diagramé este indicador para hacer tradings de corto o muy corto plazo.
Es un indicador que a simple vista ayuda al usuario a entrar en posiciones de Compra o de Venta.
Este indicador es un sistema de 3 EMAS. La primera, la de color verde es una EMA de 4 periodos. La segunda, la de color amarillo es una EMA de 9 periodos. Y por último, la de color rojo es una EMA de 18 periodos.
Por otro lado tiene señales de Compra y de Venta las cuales tienen una alta eficacia y eficiencia.
Las señales de BUY (Compra) se dan cuando la EMA verde cruza al alza a la EMA roja. Las señales de SELL (Venta) se dan cuando la EMA roja cruza a la baja a la EMA verde.
En algunas ocasiones, estos cruces se pueden producir muy rápido generando unas falsas entradas en compra o en venta según corresponda.
Para subsanar esto, es importante que se utilice este sistema de BUY y SELL con las columnas de color verde o rojo según corresponda según se ve el gráfico.
El fondo de color verde se da cuando la EMA verde y la EMA amarilla se encuentran por encima de la EMA roja. Sin embargo, cuando la EMA roja se encuentra por encima de la EMA verde y de la EMA amarilla el fondo es de color rojo.
Es importante remarcar que si la EMA verde está por encima de la EMA roja pero la EMA amarilla se encuentra por debajo de la EMA roja, en el gráfico no se va a ver ningún color de fondo. Por otro lado, cuando la EMA verde este por debajo de la EMA roja, pero la EMA amarilla todavía se encuentre por encima de la EMA roja, tampoco va a poder verse ningún tipo de color de fondo.
En resumidas cuentas:
COMPRA-BUY -> Cuando aparezca la señal de BUY y además, esta señal se complemente con un fondo de color VERDE, entonces debemos entrar en LONG. Para cerrar la operación, de manera ganadora, tenemos que esperar a que desaparezca el color de fondo VERDE.
VENTA-SELL -> Cuando aparezca la señal de SELL y además, esta señal se complemente con un fondo de color ROJO, entonces, debemos entrar en SHORT. Para cerrar la operación, de manera ganadora, tenemos que esperar a que desparezca el color de fondo ROJO.
RECOMENDACIÓN: Siempre tener presente que cada inversor tiene una aversión al riesgo distinta. Por favor, cada uno que use este indicador, primero haga una gestión de riesgo y utilice SIEMPRE Stop Loss luego de abrir una posición ya sea estipulando que el precio va a subir o a bajar, es decir, entrando en LONG o en SHORT.
Espero que este indicador les sirva.
Saludos a todos.
DEAR INVESTORS:
I plotted this indicator for short or very short term trading.
It is an indicator that at a glance helps the user to enter Buy or Sell positions.
This indicator is a 3 EMAS system. The first, the green one, is a 4-period EMA . The second one, the one in yellow, is a 9-period EMA . And finally, the one in red is an EMA of 18 periods.
On the other hand, it has Buy and Sell signals which are highly effective and efficient.
The BUY signals are given when the green EMA crosses higher than the red EMA . SELL (Sell) signals are given when the red EMA crosses down to the green EMA .
On some occasions, these crosses can occur very quickly, generating false tickets for purchase or sale as appropriate.
To correct this, it is important that this system of BUY and SELL is used with the green or red columns as appropriate as the graph is seen.
The green colored background occurs when the green EMA and the yellow EMA are above the red EMA . However, when the red EMA is above the green EMA and the yellow EMA the bottom is red.
It is important to note that if the green EMA is above the red EMA but the yellow EMA is below the red EMA , no background color will be seen on the chart. On the other hand, when the green EMA is below the red EMA , but the yellow EMA is still above the red EMA , you will not be able to see any kind of background color either.
In short:
BUY-BUY -> When the BUY signal appears and this signal is complemented by a GREEN background, then we must enter LONG. To close the operation, in a winning way, we have to wait for the GREEN background color to disappear.
VENTA-SELL -> When the SELL signal appears and also this signal is complemented with a RED background, then, we must enter SHORT. To close the operation, in a winning way, we have to wait for the RED background color to disappear.
RECOMMENDATION: Always keep in mind that each investor has a different aversion to risk. Please, everyone who uses this indicator, first do a risk management and ALWAYS use Stop Loss after opening a position either by stipulating that the price is going to rise or fall, that is, entering LONG or SHORT.
I hope this indicator helps you.
Greetings to all.
[blackcat] L2 Ehlers Fisherized Deviation Scaled OscillatorLevel: 2
Background
John F. Ehlers introuced Fisherized Deviation Scaled Oscillator in Oct, 2018.
Function
In “Probability—Probably A Good Thing To Know,” John Ehlers introduces a procedure for measuring an indicator’s probability distribution to determine if it can be used as part of a reversion-to-the-mean trading strategy. Dr. Ehlers demonstrates this method with several of his existing indicators and presents a new indicator that he calls a deviation-scaled oscillator with Fisher transform. It charts the probability density of an oscillator to evaluate its applicability to swing trading.
Key Signal
FisherFilt --> Ehlers Fisherized Deviation Scaled Oscillator fast line
Trigger --> Ehlers Fisherized Deviation Scaled Oscillator slow line
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 91th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
[blackcat] L2 Swing Oscillator Swing MeterLevel: 2
Background
Swing trading is a type of trading aimed at making short to medium term profits from a trading pair over a period of a few days to several weeks. Swing traders mainly use technical analysis to look for trading opportunities. In addition to analyzing price trends and patterns, these traders can also use fundamental analysis.
Function
L2 Swing Oscillator Swing Meter is an oscillator based on breakouts. Another important feature of it is the swing meter, which confirms the top or bottom's confidence level with different color candles. The higher of the candles stack up, the higher confidence level is indicated.
Key Signal
absolutebot ---> absolute bottom with very high confidence level
ltbot ---> long term bottom with high confidence level
mtbot ---> middle term bottom with moderate confidence level
stbot ---> short term bottom with low confidence level
absolutetop ---> absolute top with very high confidence level
lttop ---> long term top with high confidence level
mttop ---> middle term top with moderate confidence level
sttop ---> short term top with low confidence level
fastline ---> oscillator fast line
slowline ---> oscillator slow line
Pros and Cons
Pros:
1. reconfigurable swing oscillator based on breakouts
2. swing meter can confirm/validate the bottom and top signal
Cons:
1. not appliable with trading pairs without volume information
2. small time frame may not trigger swing meter function
Remarks
This is a simple but very comprehensive technical indicator
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Stock Analysis SoftwareStock Analysis Software is a full trading setup and style that is meant for swing trading stocks, but can also be used for Forex, cryptocurrencies, indices and commodities. Whatever your choice of trading style (Intraday, Scalping, Swing trading, Investing) or trading instrument is (FX, Futures, Cryptos, Stocks) I can tailor it for you specifically. For example if you want to use it for trading Forex intraday I will show you how to use it for that.
The software consists of 11 indicators, 7 are custom and 4 are common and well known indicators available on Tradingview. The system itself is part software and part learning my specific pattern finding techniques. There is no one without the other. This is a complete system
This trading system is something I have developed over the last 10 years through extensive research and development and is now available on this platform.
The indicators used are mostly screening for trend breakouts, support and resistance, specific candle patterns, overextended, volume spikes and more.
This is a system that can be taught easily if one is motivated to learn.
The setup includes a video guide and a live one-on-one full breakdown on how to use it to your benefit.
Trade Crusher: Swing and Day Trade IndicatorHow to use the indicator
Add to favorites/apply to chart.
The indicator can be used for both Swing trade and Intra-day trading.
Swing trading:
--Use with background colors
--Input: 30 or 36
--Time frame: Daily or Weekly
--Buy only when background is aqua
--Sell only when background is red
--Use with bars or candles (use candles without borders to avoid confusion). I suggest to just use bars.
--Place buy orders above the 1st or 2nd blue bar after black bars. The background must be aqua.
--Ignore yellow bars with aqua background. They are shake out bars at the beginning or a trend and warnings of reversal
towards the end of trend.
--Place sell orders bellow the 1st or 2nd yellow bar after black bars. The background must be red.
--Ignore blue bars with red background (same as above).
--Black bars are nothing: Pullbacks/Chop
Day Trading:
--DO NOT use background colors. Un-click.
--Input: 10
--Time frame: 5 minutes
--Use with bars or candles (use candles without borders to avoid confusion). I suggest to just use bars.
--Place buy orders above the 1st or 2nd blue bar after black bars.
--Place sell orders bellow the 1st or 2nd yellow bar after black bars.
--Utilize some sort of scanner that can identify stocks with heavy pre-market volume (news, earnings, etc)
***
Use stop losses however you normally do. Take profits however you normally do.
I do not suggest using with other indicators as you may just paralyze your brain, however, if you find something that works, drop a comment.
Best of luck
TrendShikari NTS - StudyTrendShikari NTS is a Nifty Index, Swing trading system with great profitability. This is the STUDY file for you to generate E-mail / SMS signal alerts (based on your TV plan) and to see crisp and clear graphical Daily trade level plotting. For seeing backtest results and next day trading levels in advance use the STRATEGY file from indicator library. Access to this system will be limited. See my profile status field to see how you can gain access.
Salient Features
1. Daily Bar System. System analyzes a Daily chart of NIFTY to give signals with average holding period of 5 days.
2. Automatic Long and Short signal generation. No need to draw waves / lines and other fancy stuff on your charts to analyze NIFTY any more.
3. Backtester Results Available - Thanks to TradingView, backtest results for previous years (from 1990) are available right in the charting platform for NIFTY.
Having a good trading system is one thing and trading it to make money is a whole different ball game. One thing you must always do if you want to mimic the backtest results in live trading is to follow the rules mentioned below as if your life depends on it.
Trading Rules
1. Each day the system gives you a Long and Short trading level. You go Long on NIFTY when the Daily Long level is breached and you go Short on NIFTY when the Daily Short Level is breached.
2. Trade using Nifty Options, In the Money calls, one strike below the nearest strike price for going Long using Call Option or one strike above the nearest strike price for going Short using Put Option.
3. Preset exit and entry orders of appropriate option contracts every day at market open. To set the levels see the difference in Nifty spot price and the trading levels given by system and then multiply it with 0.8 to give an approximate order trigger price in both directions for the corresponding option contracts.
4. Book profit when Nifty moves significantly along signal direction. Every time NIFTY moves 100 points in your direction you exit the current option contract and enter a trade in the next strike price in the same direction.
5. Rollover before expiry. Its important that you rollover (ideally one day before the expiry day) your Option contact positions by exiting the current month contract and take a new position in the next month contract of the same type and strike price of the current month contract.
6. Trade only Nifty using this system. Also Daily chart has to be used for trading. System parameters have been tested and optimized for Nifty Index Daily patterns only and hence is likely to give stated results with Nifty Daily chart only.
7. Trade all signals. Don't pick and choose or add your own or someone else's analysis to filter the signals. Take confidence from the objective backtest results and not any subjective interpretations.
8. Trade with only that amount of money you can afford to loose. Initial capital that you need to have to trade one lot of NIFTY Option using this system should be at least INR 150000. You need only INR 7500 - 15000 to open a position and the rest is the margin of safety you need to have in your trading account to account for drawdowns in trading. You can add the capital in a staggered need to basis to your trading account. But make sure you have the initial capital mentioned above at your disposal, if need be.
As always your thoughts and inputs are welcome. Happy Trading !!!
Adaptive Freedom Machine w/labelsAdaptive Freedom Machine w/ Labels
Overview
The Adaptive Freedom Machine w/ Labels is a versatile Pine Script indicator designed to assist traders in identifying buy and sell opportunities across various market conditions (trending, ranging, or volatile). It combines Exponential Moving Averages (EMAs), Relative Strength Index (RSI), Average True Range (ATR), and customizable time filters to generate actionable signals. The indicator overlays on the price chart, displaying EMAs, a dynamic cloud, scaled RSI levels, buy/sell signals, and market condition labels, making it suitable for swing trading, day trading, or scalping.
What It Does
This indicator generates buy and sell signals based on the interaction of two EMAs, filtered by RSI thresholds, ATR-based volatility, and user-defined time windows. It adapts to the selected market condition by adjusting EMA lengths, RSI thresholds, and trading hours. A dynamic cloud highlights trend direction or neutral zones, and candlestick bodies are colored in neutral conditions for clarity. A table displays real-time trend and volatility status.
How It Works
The indicator uses the following components:
EMAs: Two EMAs (short and long) are calculated on a user-selected timeframe (1, 5, 15, 30, or 60 minutes). Their crossover or crossunder generates potential buy/sell signals, with lengths adjusted based on the market condition (e.g., longer EMAs for trending markets, shorter for ranging).
Dynamic Cloud: The area between the EMAs forms a cloud, colored green for uptrends, red for downtrends, or a user-defined color (default yellow) for neutral zones (when EMAs are close, determined by an ATR-based threshold). Users can widen the cloud for visibility.
RSI Filter: RSI is scaled to price levels and plotted on the chart (optional). Signals are filtered to ensure RSI is within user-defined buy/sell thresholds and not in overbought/oversold zones, with thresholds tailored to the market condition.
ATR Volatility Filter: An optional filter ensures signals occur during sufficient volatility (ATR(14) > SMA(ATR, 20)).
Time Filter: Signals are restricted to a user-defined or market-specific time window (e.g., 10:00–15:00 UTC for volatile markets), with an option for custom hours.
Visual Aids: Buy/sell signals appear as green triangles (buy) or red triangles (sell). Candlesticks in neutral zones are colored (default yellow). A table in the top-right corner shows the current trend (Uptrend, Downtrend, Neutral) and volatility (High or Low).
The indicator ensures compatibility with standard chart types (e.g., candlestick charts) to produce realistic signals, avoiding non-standard types like Heikin Ashi or Renko.
How to Use It
Add to Chart: Apply the indicator to a candlestick or bar chart on TradingView.
Configure Settings:
Timeframe: Choose a timeframe (1, 5, 15, 30, or 60 minutes) to align with your trading style.
Market Condition: Select one market condition (Trending, Ranging, or Volatile). Volatile is the default if none is selected. Only one condition can be active.
Filters:
Enable/disable the ATR volatility filter to trade only in high-volatility periods.
Enable the time filter and choose default hours (specific to the market condition) or set custom UTC hours.
Cloud Settings: Adjust the cloud width, neutral zone threshold, and color. Enable/disable the neutral cloud.
RSI Display: Toggle the scaled RSI and its thresholds on the chart.
Interpret Signals:
Buy Signal: A green triangle below the bar indicates a potential long entry (EMA crossover, RSI above buy threshold, within time window, and passing volatility filter).
Sell Signal: A red triangle above the bar indicates a potential short entry (EMA crossunder, RSI below sell threshold, within time window, and passing volatility filter).
Neutral Zone: Yellow candlesticks and cloud (if enabled) suggest a lack of clear trend; avoid trading or use for range-bound strategies.
Monitor the Table: Check the top-right table for real-time trend (Uptrend, Downtrend, Neutral) and volatility (High or Low) to confirm market context.
Unique Features
Adaptive Parameters: Automatically adjusts EMA lengths, RSI thresholds, and trading hours based on the selected market condition, reducing manual tweaking.
Neutral Zone Detection: Uses an ATR-based threshold to identify low-trend periods, helping traders avoid choppy markets.
Scaled RSI Visualization: Plots RSI and thresholds directly on the price chart, making it easier to assess momentum relative to price action.
Flexible Time Filtering: Supports both default and custom UTC-based trading windows, ideal for day traders targeting specific sessions.
Dynamic Cloud: Enhances trend visualization with customizable width and neutral zone coloring, improving readability.
Notes
Use on standard candlestick or bar charts to ensure realistic signals.
Test the indicator on a demo account to understand its behavior in your chosen market and timeframe.
Adjust settings to match your trading strategy, but avoid over-optimizing for past data.
The indicator is not a standalone system; combine it with other analysis (e.g., support/resistance, news events) for better results.
Limitations
Signals may lag in fast-moving markets due to EMA-based calculations.
Neutral zone detection may vary in extremely volatile or illiquid markets.
Time filters are UTC-based; ensure your platform’s timezone settings align.
This indicator is designed for traders seeking a customizable, trend-following tool that adapts to different market environments while providing clear visual cues and robust filtering.
TSLA2DTesla Swing Indicator
Overview
The Tesla Swing Indicator is a powerful and versatile trading tool designed to help traders identify swing trading opportunities, with a primary focus on Tesla (TSLA) stock. While optimized for TSLA, this indicator can also be applied to other stocks, making it a flexible addition to any trader’s toolkit. It combines multiple technical elements—Moving Averages (MAs), Stochastic signals, RSI-based background coloring, high volume detection, and a unique Bottom Line trend indicator—to provide a comprehensive view of market conditions.
Key Features
Moving Averages (MAs): The indicator plots four customizable MAs (default lengths: 20, 50, 150, and 300) to help identify trends and potential reversals. You can toggle between SMA and EMA for each MA and adjust their lengths and linewidths to suit your trading style.
MA1 (20-period EMA, yellow).
MA2 (50-period SMA, blue).
MA3 (150-period SMA, red).
MA4 (300-period SMA, white).
Stochastic Signals: The indicator uses Stochastic %K and %D to generate buy and sell signals:
Pre-Buy Signal (blue circles below candles): Indicates a potential buy when %K crosses above %D in oversold territory (below 20).
Crossover in Oversold (gold squares below candles): Confirms a buy signal when %K crosses above %D while both are below 20.
Crossunder in Overbought (pink squares above candles): Signals a potential sell when %K crosses below %D in overbought territory (above 80).
Note: While the Stochastic component works well for TSLA, it may produce less reliable signals on other stocks due to differences in volatility and price behavior. Adjust the Stochastic parameters (e.g., lengths) or test thoroughly when applying to non-TSLA stocks.
RSI Background Coloring: The background turns green when the 15-period RSI is above 50, indicating bullish momentum. This helps traders quickly gauge the strength of the current trend.
High Volume Background: The background highlights in yellow when volume exceeds 1.5 times the 20-period average volume, signaling significant market activity that often precedes big moves.
Bottom Line Trend Indicator: Positioned at the bottom of the chart, the Bottom Line acts as a trend indicator based on price interactions with the MAs:
Green: Indicates a bullish trend when the price is above MA2 (50-period).
Red: Signals a bearish trend when the price is below MA3 (150-period).
Gray: Reflects a neutral or transitional state when the price crosses below MA2 but isn’t below MA3, or when MA1 is above MA2 in a neutral context.
The Bottom Line provides a quick visual cue for the overall trend direction, helping traders align their strategies accordingly.
PVSRA Candle Coloring: The indicator applies Price-Volume-Sentiment-Range Analysis (PVSRA) to color candles based on volume and price action:
Lime (200% Bullish): High volume bullish candle (volume ≥ 2x average or weighted range condition).
Red (200% Bearish): High volume bearish candle.
Blue (150% Bullish): Rising volume bullish candle (volume ≥ 1.5x average).
Fuchsia (150% Bearish): Rising volume bearish candle.
White (Normal Bullish): Normal volume bullish candle.
Gray (Normal Bearish): Normal volume bearish candle.
This coloring helps traders identify significant candles driven by strong volume, often indicating potential trend continuations or reversals.
MACD Divergence Detection (Disabled by Default): The indicator includes logic to detect bullish and bearish MACD divergences, which can be enabled via the code for advanced users.
Usage
Best for Tesla (TSLA): The indicator is fine-tuned for TSLA, leveraging its volatility and volume characteristics to generate reliable signals. The Stochastic signals, in particular, are optimized for TSLA’s price action.
Other Stocks: The indicator can be applied to other stocks, but caution is advised with the Stochastic component. Stocks with different volatility profiles may require adjustments to the Stochastic parameters (e.g., k_length, k_smoothing, d_smoothing) to improve signal accuracy. Test thoroughly on your chosen stock and consider disabling Stochastic signals if they underperform.
Timeframes: Works on any timeframe, but swing traders may find the best results on daily higher. Ensure your chart has enough historical data (at least 300 bars) to calculate the longest MA (300 periods).
Customization: Adjust MA lengths, toggle between SMA/EMA, and tweak RSI and volume thresholds via the indicator settings to match your trading preferences.
How to Interpret
Trend Direction: Use the Bottom Line’s color (green, red, gray) to assess the overall trend. Green suggests a bullish bias, red indicates bearish conditions, and gray signals neutrality or a potential transition.
Momentum and Strength: The green RSI background (RSI > 50) confirms bullish momentum, while the absence of green indicates weaker momentum. Yellow high volume backgrounds highlight periods of significant market activity, often preceding major price movements.
Entry/Exit Signals: Look for Pre-Buy Signals (blue circles) and Crossover in Oversold (gold squares) for potential buy opportunities, and Crossunder in Overbought (pink squares) for sell signals. Confirm these signals with the trend direction (Bottom Line) and volume activity (yellow background).
Significant Candles: PVSRA candle colors help identify key price action. Lime and red candles (200% volume) indicate strong momentum, while blue and fuchsia (150% volume) suggest rising interest that may lead to bigger moves.
Limitations
Stochastic on Other Stocks: As noted, the Stochastic signals are optimized for TSLA and may generate false signals on stocks with different price behaviors. Adjust parameters or disable if necessary.
Historical Data: Ensure your chart has sufficient historical bars (at least 300) to calculate the longest MA. If not, reduce the MA4 length in the settings.
Volatility: The indicator assumes a certain level of volatility (as seen in TSLA). On low-volatility stocks, signals may be less frequent or less reliable.
Final Notes
The Tesla Swing Indicator is a robust tool for swing traders looking to capitalize on TSLA’s price movements, with the flexibility to adapt to other stocks with proper adjustments. Its combination of trend analysis (Bottom Line), momentum (RSI background), volume detection (high volume background), and entry/exit signals (Stochastic) provides a well-rounded approach to technical analysis. Use it as part of a broader trading strategy, and always backtest on your chosen stock and timeframe to ensure optimal performance.
WREKS Theory📊 WREKS Theory – Advanced Market Structure & Auto-Fibonacci Indicator
By WREKS Trading Community
📊 WREKS Theory – Advanced Market Structure & Auto-Fibonacci Indicator
By WREKS Trading Community
✅ Overview
The WREKS Theory indicator is a robust, all-in-one technical analysis tool designed to identify trend direction, generate buy/sell signals, and project key Fibonacci levels for precision trading. It merges the logic of Dow Theory (Higher Highs & Higher Lows), SMA filtering, and automated Fibonacci clusters based on ZigZag pivots to highlight optimal price zones for entry, reversal, and take-profit.
🧠 Built-in Logic
Dow Theory Engine: Detects confirmed uptrends and downtrends based on recent pivot highs and lows.
SMA-144 Filter: Confirms signal strength by filtering trades aligned with the dominant trend.
ZigZag-based Auto-Fibonacci: Dynamically maps Fibonacci retracement and extension levels from the most recent swing, with color-coded visual lines and labels.
Signal Dashboard: Displays trend change counts (Uptrends / Downtrends) and real-time status in a clean table on the chart.
Smart Alerts: Triggers when buy/sell signals occur or when price crosses Fibonacci levels.
📌 Key Features
🔺 Buy / Sell Markers: Auto-labeled on the chart using real-time trend shift confirmation.
📈 Fibonacci Cluster Map: Automatically draws up to 22 customizable Fib levels including negative retracements and advanced extensions (0.236 to 4.618+).
🎯 Trend Labels: Clearly marks “Uptrend” and “Downtrend” zones.
💡 Visual Table: Quick reference for signal frequency and trend transitions.
🔔 Alerts: Built-in alerts for trade signals and price interactions with Fib levels.
⚙️ Fully Customizable: Modify SMA, pivot length, depth, deviation multiplier, line extension style, color themes, and more.
📈 Benefits for Traders
✅ Enhanced Trend Confirmation using Dow Theory logic with SMA filtering.
✅ Precision Entry & Exit Zones through auto-drawn Fibonacci retracement and extension levels.
✅ Reduces False Signals by requiring both market structure and trend alignment.
✅ Saves Time with automated drawing and real-time alerts.
✅ Ideal for All Assets & Timeframes: Works seamlessly across Forex, Crypto, Stocks, and Commodities.
💼 Best Use Cases
Intraday & swing trading using market structure.
Identifying major retracement zones for pullback entries.
Recognizing Fibonacci confluence zones to set stop-loss and take-profit levels.
Trend-following strategies validated by SMA and Dow confirmation.
Stock price mastery📘 Cycle-Based Support and Resistance – Price Levels
🔍 What this tool does:
This indicator helps you identify key price zones where the market is likely to start or end a trend, pause, or reverse. These zones are derived from vibrational price cycles and work like natural support and resistance levels.
It automatically calculates and plots:
Entry Zones
Take Profits (TP1, TP2, TP3)
Stop Loss Areas
Cycle Start/End points
🧠 How to Use It:
1. Start from Larger Vibrations
Always begin your analysis from higher vibration levels and move down to smaller ones.
Larger vibrations provide major turning points, while smaller ones help refine entries and exits.
2. Understand Each Level:
Cycle Start/End:
Usage: Turning points where trends may begin or end.
Style: Solid line, with shaded area.
Trade Entry Zone:
Usage: Ideal price zone to enter a trade.
Style: Dashed lines with shade.
TP1 / TP2 / TP3 (Take Profit Levels):
Usage: Take profit levels.
Style: Dotted line zone, dashed, or solid line.
Stop Loss:
Usage: Place Stop Loss (SL) beyond these zones.
Style: Dotted line.
✅ These levels flip meaning when the market direction flips. For example, a bullish cycle start becomes a bearish end if price is reversing.
⚙️ Settings Explained:
Vibration Level:
Choose the strength (depth) of the cycles.
Color:
Each vibration has a different color.
Toggle Levels:
Show or hide different vibration levels individually.
Fill Zones:
Optionally fill the zones for better visibility.
📈 Trading Tips:
Use higher vibration zones for context and bias.
Wait for price to react at a zone before entering — don’t preempt.
Combine with your existing strategy (volume, structure, indicators).
When price hits a Cycle Start, prepare for trend to begin.
When it nears a Cycle End, protect profits or exit if trend weakens.
🌀 Multi-Timeframe Example :
*same chart zoomed in for lower vibration
🧠 How to Use It
1. Start with Higher Vibration (Main Cycle)
Use higher vibration zones to define the primary trend.
These levels guide your overall bias (bullish/bearish).
Great for swing trading or trend confirmation.
2. Zoom into Lower Vibrations (Micro Cycles)
Within a big trend, smaller cycles provide entry/exit zones.
Perfect for intraday trading or refining entries on lower timeframes.
These mini-cycles follow the same logic: entry > TP > SL zones, just on a smaller scale.
🔄 All vibrations work together, like zoom levels on a map. Large cycles show direction. Small cycles show detailed movement.
Example use
Timeframe, Use Case, and What to Look For:
1D / 4H (High Vibration):
Use Case: Define major trend, strong reversal zones.
What to Look For: Trend direction, swing bias.
1H / 15m (Low Vibration):
Use Case: Refine entries, targets, stop loss (SL).
What to Look For: Exact entry/exit within a bigger move.
Back testing:
In settings check the "Rspt" for backtesting, the levels are dynamically calculated from closing price, on 1 min timeframe, so while backtesting check the box to calculate price based on the daily closing price
Market Availability
The Cycle-Based Support and Resistance indicators are versatile and designed to work across multiple asset classes:
Stocks:
Specially optimized for major Indian indices like NIFTY and BANKNIFTY, along with their constituent stocks. It helps traders identify potential pivot points based on time and price cycles, enhancing decision-making in both intraday and positional trading.
By following the hierarchy of vibrations from larger to smaller scales, users can apply the indicators effectively across different instruments and trading styles.
