TFC Alerts Multi Time Frame
TFC Alerts Multi Time Frame
The TFC Alerts Multi Time Frame indicator is a powerful tool designed to monitor full timeframe continuity (FTFC) across multiple symbols and multiple timeframes simultaneously. This indicator tracks the performance of four selected symbols (e.g., SPY, QQQ, DIA, IWM) across four distinct timeframes, providing visual alerts when all selected symbols are in full continuity.
### Key Features:
- **Multi-Timeframe Monitoring:** Track up to four different symbols across four separate timeframes (e.g., 60-minute, daily, weekly, monthly) in a single indicator, offering a comprehensive view of market continuity over various time horizons.
- **FTFC Alerts:** The indicator provides visual labels on the chart when all selected symbols are in full continuity across the chosen timeframes. Green labels indicate that all symbols are above their open prices across all timeframes (bullish FTFC), while red labels show that all symbols are below their open prices (bearish FTFC).
- **Versatile Timeframe Selection:** Each symbol is monitored across four customizable timeframes. Traders can adjust these to fit their trading strategy, whether they are looking at shorter intraday intervals like 5-minute, 15-minute, 30-minute, and 60-minute, or longer-term perspectives such as daily, weekly, monthly, and even quarterly timeframes.
### Image Explanation:
- **Full Timeframe Continuity Overview:** This image illustrates the indicator set to monitor the 5-minute, 15-minute, 30-minute, and 60-minute timeframes for each of the four symbols (SPY, QQQ, DIA, IWM). The FTFC labels plot on the chart when all four timeframes for each symbol align in the same direction. This setup is flexible and can easily be adjusted to longer timeframes such as the 60-minute, daily, weekly, and monthly intervals, depending on the trader’s preferred time horizon.
### Most Powerful Use Case:
The most powerful way to use this indicator is to confirm market trends across your chosen timeframes by monitoring major indices or sector ETFs. For short-term traders, setting the indicator to track 5-minute, 15-minute, 30-minute, and 60-minute timeframes allows for quick identification of intraday trends. For longer-term traders, adjusting the timeframes to 60-minute, daily, weekly, and monthly (or even quarterly and yearly) provides a robust analysis of market alignment over extended periods. This versatility makes it invaluable for executing trades that align with broader market momentum, regardless of the trading horizon.
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Mxwll OptAlgoIntroducing the Mxwll OptAlgo
Mxwll OptAlgo is a sophisticated algorithmic trading tool designed to identify potential long and short signals. It leverages an optimized combination of the M-Swift average, M-Smooth average, and M-RSI to fine-tune custom lengths and improve signal accuracy. The Mxwll OptAlgo provides long and short signals across various trading assets and timeframes. Additionally, it features optimized Take Profit (TP) and Stop Loss (SL) settings to help traders manage risk.
Key Features
Step-by-Step Complete Optimization: A systematic approach to optimize trading parameters.
Buy/Sell Signals: Clear indicators for long and short positions.
Easy to Use: User-friendly interface for seamless trading.
Predictive counter trend channels
Integrated trend following system and counter trend trading system
3-optimized strategies working cooperatively
Alerts and auto trading capabilities
How It Works
The Mxwll OptAlgo is comprised of three strategies:
Trend following using the OptAlgo
AI Reversal counter trend trading
Market crash shorting
Mxwll OptAlgo can be used for market analysis and trading similarly to any moving average.
The Mxwll OptAlgo MA is composed of two distinct moving averages to be used for trend following strategies.
M-Swift Average: The M-Swift Average accounts for volume and weights current price movement heavier than older price movement - allowing for improved responsiveness to current price movement. Volume is additionally weighted to the average to determine the significance of the price move and the resulting response of the M-Swift average. The M-Swift average consists of an HVWMA with OBV weighting. The HVWMA is used to create a moving average that adapts to volume, attempting to respond to significant price moves with high volume quicker and significant price moves with low volume slower - which might not be indicative of the start of a strong trend. To further reduce the M-Swift average’s responsiveness to weak volume price moves, the average is weighted with a normalized OBV. With this, the M-Swift moving average uses these two indicators to create a responsive moving average to significant price moves with high volume.
M-Smooth Average: The M-Smooth average consists of a McGinley average.
The McGinley Average is designed to address some of the limitations of traditional moving averages, such as the Simple Moving Average (SMA) or Exponential Moving Average (EMA), by reducing their lag and more accurately reflecting the market's true movements, especially during periods of volatility.
The McGinley Dynamic automatically adjusts its smoothing factor based on market speed. This means it responds more quickly to fast-moving markets and slows down during periods of consolidation, reducing the likelihood of false signals.
Unlike traditional moving averages that have a fixed period and can lag significantly behind fast-moving prices, the McGinley Dynamic adjusts dynamically, which helps to reduce lag and keeps the moving average closer to the price action.
The M-Smooth average uses bar low prices as a series during an uptrend - bar high prices as a series during a downtrend. A cross above the M-Smooth average indicates an uptrend, while a cross below the M-Smooth average indicates a downtrend. When this cross event occurs the M-Smooth average will “flip” from calculating on lows to highs, or highs to lows, contingent on the direction of the trend. The expectation is that a cross event of the M-Smooth average requires a substantial price move and, subsequent to this cross, price will continue to trend in the direction of the cross.
OptAlgo: The OptAlgo is simply the average of the M-Swift average and the M-smooth average.
By combining the M-Swift average and the M-Smooth average, the final output results in an average that slows during ranging markets and quickly adjusts to high volume breakouts and high volume reversals that initiate a trend. Due to the combination, the average will keep up quickly with a trend but remain at an appropriate distance from the current price - requiring a significant counter trend price move to change the direction of the OptAlgo average.
How does the OptAlgo follow trends?
The OptAlgo, comprising the two moving averages above, considers a cross event of the OptAlgo as a change in trend indication. The OptAlgo can be thought of as a moving average that significantly deviates from price. For price to cross the OptAlgo, a substantial price move must occur, and this event is treated as a "strong trend" or "new trend" indication.
M-RSI: The M-RSI is a fundamental component of the trend following strategy. Prior to a trend following “long” or “short” signal, the M-RSI must generate a signal in confluence with an OptAlgo cross event. When price crosses over the opt algo its color will change to green, indicating an uptrend. A buy signal will generate should the M-RSI provide a similar indication. The M-RSI portion of the trend following strategy is explained below. When price crosses under the opt algo its color will change to green, indicating a downtrend, and a sell signal becomes eligible. The foundational logic for using the Opt Algo as a trend following strategy is to treat crossovers/crossunders of the Opt Algo as strong trend indications, and trade them.
Steps to generate a trend following long signal:
1: M-RSI extends into oversold territory
2: Price crosses over the OptAlgo
Steps to generate a trend following short signal:
1: M-RSI extends into overbought territory
2: Price crosses under the OptAlgo
Our trend following strategy considers crossovers/crossunders at key market turning points as buy/sell opportunities. This strategy integrates the Mxwll RSI and Mxwll OptAlgo MA to determine entry points in anticipation of trend continuation.
The Mxwll RSI must move below/above the optimized OB/OS level prior to a cross event for a long/short signal to be considered. Entry points for this strategy are marked as "Long" or "Short".
At its core, the OptAlgo trend following strategy tries to enter a trend as close to the origin point as possible. As with any trend following strategy, price may not continue to move in the expected direction following entry, resulting in a losing trade.
AI Reversal Predictions
Our AI reversals strategy uses AI suggested turning points to capitalize on price reversions back towards the OptAlgo. These levels are considered by the AI on the selected days, and entry points at these levels are marked as "LLO" or "SLO".
How AI reversals work
Our AI reversals strategy attempts to trade price reversions back toward the Opt Algo.
These levels are calculated on specific days of the week, but can be traded any day. The internal algorithm determines which HTF highs/lows are most likely to function as tradable support/resistance levels. For instance, if Friday consists of heavy trading activity and high/low prices are tracked/recorded as causing significant support / resistance when tested in the future, the algorithm will consider support and resistance levels created on Friday as future tradable levels.
Additionally, if support/resistance levels created on Wednesday are recorded as weak or unpredictable when traded at in the future, the algorithm will not consider support/resistance levels generated on Thursday as tradable, and will not generate long or shit signals for these levels.
In the background, the AI reversals strategy is tracking success rates at multiple support and resistance levels. The best performers, if there are any, will be considered tradable. A “best performer” is calculated as the raw price move up to a threshold (i.e. 0.5%) that occurs subsequent to a test of the level.
Crash Short
The "Crash Short" strategy prioritizes short positions during retracements of a sell off. A simple yet effective strategy.
How Crash Short Works
The Crash Short strategy uses a customized momentum indicator (similar to ROC, MOM, etc.) to identify strong downside price moves. When our customized momentum indicator gives strong sell indications, the RSI is then referenced to identify an upside retracement. When the RSI exceeds a user-inputted level, a “Crash Short” signal is generated.
What is the customized momentum indicator?
The customized momentum indicator is the RoCR (Rate of Change Ratio). Instead of classic ROC, which is close - close , the RoCR divides the current close by a previous close. This formula creates a ratio that is more normalized than a simple price difference. This ratio is used to determine upside/downside momentum, with values greater than 1 indicating bullish momentum and values less than 1 indicating bearish momentum. The RoCR looks for deviating values to the downside (less than 1) to identify strong selling. From there, once the RSI crosses over an optimized level (such as 35), the indicator will print a sell signal titled "Crash Short".
Predictive Countertrend Channels
Our Predictive Countertrend Channel applies a two-stage recursive filter to smooth data using exponential decay and periodic adjustments for trend extraction. Our counter trend channels aren't directly used for signal processing; however, these channels provide useful visual cues for extended market moves.
Instructions for Optimization
Step 1: Optimize Mxwll OptAlgo
Begin by optimizing the M-Swift and M-Smooth averages for better signal accuracy.
This step simply finds better performing M-Swift and M-Smooth lookbacks. Again, if the strategy is unprofitable you will be notified and from there decide not to use the strategy.
Step 2: Optimize Mxwll RSI
Refine the Mxwll RSI settings to explore potential adjustments in smoothness and signal output. This step aims to evaluate whether these adjustments could improve the accuracy of the signals generated by Mxwll OptAlgo, while being mindful of any potential impacts.
Step 3: Optimize TP/SL
Consider adjusting the Take Profit and Stop Loss settings to potentially manage risk.
Step 4: Optimize Bars Between Trades
Set the number of bars between trades to regulate the frequency of trade executions. This adjustment may help in reducing the risk of overtrading and support a more disciplined trading strategy.
Step 5: Optimize Trade Flip
Adjust the trade flip parameters to potentially improve the management of transitions between long and short positions. This adjustment is intended to help achieve smoother trade executions, though outcomes may vary.
Step 6: Optimize RSI OB/OB Levels
Consider adjusting the overbought (OB) and oversold (OS) RSI levels to explore potential improvements in signal sensitivity. Careful calibration of these levels may help refine the accuracy of trend reversal signals, although results may depend on market conditions.
Finished!
From this point, consider setting alerts to make the most of the Mxwll Opt Algo's potential accuracy.
The effectiveness of the Opt Algo signal output can be evaluated using the "PF" table, which indicates the profit factor score for the strategy. A profit factor (PF) of less than or equal to 1 suggests that the strategy may not be profitable.
Disclaimer
No strategy works on any timeframe on any asset, so, if the Opt Algo underperforms for the asset/timeframe you're analyzing, the Opt Algo PF table lets you know it hasn't been generating accurate signals, in which case you can decide not to use it!
Optimization Disclaimer
Optimization can be tricky. It's helpful to test numerous strategies in aggregate to see if a strategy has potential. Despite this, optimization can cause overfitting. Overfitting occurs when a strategy is too closely fit to the data it's trading. Overfit backtests are deceptively phenomenal. While the historical performance looks great, the future expectancy of the strategy remains unpredictable - an overfit strategy will profit from periods of random price movement which, being random, are irreproducible and cannot be profited from other than their initial occurrence. When a strategy trades random price movement profitably, any and all profit earned can be reduced to chance. Keep this in mind when using the in-built optimization system. Optimization should be kept to a minimum, a tool to point you in the right direction, whether confirming potential or signifying a useless system.
Cumulative Gain/Loss Histogram This TradingView Pine Script indicator combines several analytical tools to assist traders in making informed investment decisions. It calculates and visualizes cumulative gain/loss percentage, standard deviation levels, and normalizes trading volume on a reversed scale.
Components:
Basis for Calculation:
Users can select the basis data for the calculations: Price, VIX (Volatility Index), VVIX (Volatility of Volatility Index), or MOVE (Volatility Index for Treasury Securities).
Cumulative Gain/Loss:
This is computed based on the selected basis. The script tracks the cumulative percentage change in the selected basis data. Positive changes are aggregated to track gains, while negative changes accumulate to track losses.
Standard Deviation Levels:
The script calculates standard deviation (StdDev) for the cumulative gain/loss data over a specified period. Two levels are determined:
Positive StdDev Level: Shows the upper threshold for gains.
Negative StdDev Level: Shows the lower threshold for losses.
These levels are useful for identifying extreme deviations in the data.
Normalized Volume:
The trading volume is normalized to fit within a -5 to 5 scale, but the scale is reversed. Higher trading volumes will be represented by lower values on this scale. This normalized volume is plotted as a gray line on the chart.
How to Use This Indicator:
Identify Trends and Extremes:
Cumulative Gain/Loss: Look for periods where the cumulative gain/loss exceeds the standard deviation levels. This can indicate significant trend changes or potential reversals. Standard Deviation Levels: Use these levels to gauge whether the market is experiencing extreme conditions. For example, if the cumulative gain/loss crosses above the positive StdDev level, it might suggest an overbought condition.
Volume Analysis:
Normalized Volume: Analyze the volume trends with the reversed scale. Higher normalized volume values (which are lower on the -5 to 5 scale) could indicate high trading activity or market interest, potentially signaling a strong move or trend. Conversely, lower normalized volume values (which are higher on the -5 to 5 scale) may suggest lower trading activity or consolidation.
Decision-Making:
Combine the insights from cumulative gain/loss and standard deviation levels with volume analysis to make more informed trading decisions.
Buy Signal: Consider entering a position when the cumulative gain/loss reaches or exceeds the negative StdDev level and volume analysis supports increased market activity.
Sell Signal: Consider exiting a position when the cumulative gain/loss exceeds the positive StdDev level, indicating possible overbought conditions, especially if volume trends also align with the potential reversal.
Summary:
This script is designed to help traders understand market dynamics through cumulative gain/loss trends, standard deviation thresholds, and volume analysis. By interpreting these elements together, traders can identify potential trading opportunities and make more informed decisions based on market conditions and trends.
Uptrick: Bullish/Bearish Signal DetectorDetailed Explanation of the "Uptrick: Bullish/Bearish Signal Detector" Script
The "Uptrick: Bullish/Bearish Signal Detector" script is a sophisticated tool designed for the TradingView platform, leveraging Pine Script version 5. This script is crafted to enhance traders' ability to identify bullish (buy) and bearish (sell) signals directly on their trading charts. By combining the power of the MACD (Moving Average Convergence Divergence) and RSI (Relative Strength Index) indicators, this script provides a unique and efficient method for detecting potential trading opportunities. Below is an in-depth exploration of its purpose, features, and functionality.
Purpose
The primary purpose of this script is to assist traders in identifying potential entry and exit points in the market by signaling bullish and bearish conditions. This automated detection helps traders make more informed decisions without the need to manually analyze complex indicators. By overlaying signals directly on the price chart, the script allows for quick visual identification of market trends and reversals.
Uniqueness
What sets this script apart is its dual use of MACD and RSI indicators. While many trading strategies might rely on a single indicator, combining MACD and RSI enhances the reliability of the signals by filtering out false positives. The script not only identifies trends but also adds a layer of confirmation through the RSI, which measures the speed and change of price movements.
Inputs and Features
Customizable Label Appearance:
The script allows users to customize the appearance of the labels that indicate bullish and bearish signals. Users can set their preferred colors for the labels and the text, ensuring that the signals are easily distinguishable and aesthetically pleasing on their charts.
MACD Calculation:
The script calculates the MACD line and signal line using user-defined input values for the fast length, slow length, and signal length. The MACD histogram, which is the difference between the MACD line and the signal line, is used to determine the momentum of the market.
RSI Calculation:
The RSI is calculated using a user-defined input length. The RSI helps in identifying overbought or oversold conditions, which are crucial for confirming the strength of the trend detected by the MACD.
Bullish and Bearish Conditions:
The script defines bullish conditions as those where the MACD histogram is positive and the RSI is above 50. Bearish conditions are defined where the MACD histogram is negative and the RSI is below 50. This combination of conditions ensures that signals are generated based on both momentum and relative strength, reducing the likelihood of false signals.
Label Plotting:
The script plots labels on the chart to indicate bullish and bearish signals. When a bullish condition is met, and the previous signal was not bullish, a "LONG" label is plotted. Similarly, when a bearish condition is met, and the previous signal was not bearish, a "SHORT" label is plotted. This feature helps in clearly marking the points of interest for traders, making it easier to spot potential trades.
Tracking Previous Signals:
To avoid repetitive signals, the script keeps track of the last signal. If the last signal was bullish, it avoids plotting another bullish signal immediately. The same logic applies to bearish signals. This tracking ensures that signals are spaced out and only significant changes in market conditions are highlighted.
How It Works
The script operates in a loop, processing each bar (or candlestick) on the chart as new data comes in. It calculates the MACD and RSI values for each bar and checks if the current conditions meet the criteria for a bullish or bearish signal. If a signal is detected and it is different from the last signal, a label is plotted on the chart at the current bar's price level. This real-time processing allows traders to see the signals as they form, providing timely insights into market movements.
Practical Application
For practical use, a trader would add this script to their TradingView chart. They can customize the input parameters for the MACD and RSI calculations to fit their trading strategy or preferred settings. Once added, the script will automatically analyze the price data and start plotting "LONG" and "SHORT" labels based on the detected signals. Traders can then use these labels to make decisions on entering or exiting trades, adjusting their strategy as necessary based on the signals provided.
Conclusion
The "Uptrick: Bullish/Bearish Signal Detector" script is a powerful tool for any trader looking to leverage technical indicators for better trading decisions. By combining MACD and RSI, it offers a robust method for detecting market trends and potential reversals. The customizable features and real-time signal plotting make it a versatile and user-friendly addition to any trading toolkit. This script not only simplifies the process of technical analysis but also enhances the accuracy of trading signals, thereby potentially increasing the trader's success rate in the market.
[XSO-Premium-X1]The indicator is a comprehensive, premium trading indicator designed to optimize your trading strategy through advanced price action analysis. By examining raw price data and market structure, it identifies key areas where price movements are likely to occur. This indicator serves as an essential trading companion, significantly reducing the time required for analysing price action and enabling you to place trades manually or via automated alerts.
Summary:
The indicator is a sophisticated tool crafted for analysing and predicting market trends using a variety of technical analysis techniques. It integrates multiple calculations, filters, and conditions to pinpoint optimal buy and sell signals, thereby assisting you in making well-informed decisions. The indicator emphasizes trend detection, sideways market identification, and signal generation, all while providing visual cues and alerts for trading actions.
The indicator leverages price action calculations to evaluate the market's bullish or bearish tendencies, ensuring that signals are only triggered when price action is strong enough.
This indicator performs extensive calculations, consolidating our top tools into a master signal generator that includes new, extensively tested methods previously unavailable to the public. Signals are confirmed when multiple factors, including price action, align. The indicator swiftly reacts to market changes, providing early signals at the first signs of a reversal.
HOW TO USE THE INDICATOR
Buy Signal
An orange “Buy Signal” will be plotted on the chart to indicate when the most opportunistic time is to place a trade. The indicator includes alert functionality so that you can be notified using the standard Trading View alert management options.
You will see indicated by the blue arrows on the above graph the entry or ‘buy’ signals. The signal is represented by an orange box and clearly states ‘Buy Signal’ inside it. You are also provided with the close price of the bar for which the entry/buy value should be.
Sell Signal
The sell signal will look at the market and detect changes within the trend. There are multiple tools that are used to determine the best time to exit/sell the trade. Our advanced algorithm continually monitors the current action and will determine the most desirable time to display a sell signal box which is blue in colour. This signal will be shown directly on the chart.
Indicated in blue arrows you will see the sell signals. Each signal has four values:
Type of Signal
The current close price of the current bar
The percentage change from the original corresponding buy signal
The previous buy signal’s close price
The indicator will look at many factors when determining if you should exit a trade. Look at the image below and you can see a typical buy and sell signal combination:
The bottom blue arrow indicates your entry or “buy” trade and the top blue arrow indicates your exit or “sell” trade. As you can see you would have entered/bought at 185.76 and exited/sold at 186.895 with a 0.61% margin.
Here is another example:
Hold Asset / Stop Loss
If the market moves to the downside after you have entered a trade then the indicator will track this. Our analysis may determine that the market may continue to fall or that simply the conditions are no longer favourable. Under these circumstances the indicator will flag for you to Hold Asset / Stop Loss. You can then make a decision if you want to hold onto your asset or sell it at a loss.
If you look on the chart below you can see an example of these signals plotted on the chart indicated by the blue arrow.
Alert Management
There are 3 alerts that are fixed. They are:
Buy Signal
Sell Signal
Hold Asset / Stop Loss
You can select which alert you would like to trigger from the standard trading view alert management page. For all buying you would select “Buy Signal” for all selling/take profit you would select “Sell Signal” and for holding the asset (maybe to set a limit order) or to sell the asset at a loss (stop loss), you would choose “Hold Asset / Stop Loss”.
Best Utilization of Our Indicator with Lower Time Frames
Our indicator is specifically designed to excel in short-term trading environments, making it the perfect tool for scalping strategies. For optimal performance, it is best utilized with time frames under 5 minutes . Here’s why our indicator is tailored for lower time frames and not suitable for long-term signalling:
1. Scalping Focus:
o Scalping involves making numerous trades throughout the trading session to capture small price movements. Our indicator is engineered to identify these quick, short-term opportunities, making it ideal for time frames of 3 minutes and under.
2. Rapid Signal Generation:
o Lower time frames generate more data points in a shorter period, allowing our indicator to provide rapid buy and sell signals. This frequency is crucial for scalpers who need to react quickly to market changes.
3. Minimized Market Noise:
o While lower time frames can be more volatile, our indicator includes filters to minimize market noise and focus on significant trading signals. This feature ensures that you receive reliable signals even in fast-paced trading environments.
Suitable Markets
This indicator is versatile and suitable for all markets, offering comprehensive analysis and reliable signals for various trading environments. Its advanced features and customizable settings ensure optimal performance across different market conditions, making it an essential tool for traders in any market.
Strategies
This indicator is ideal for both scalping whilst taking long positions, providing precise, timely signals for short-term trades while also identifying strong trends. Its versatility and advanced features make it a valuable tool for traders with diverse strategies.
What makes our indicator different?
Our indicator incorporates predefined parameters tailored to identify opportunities within a long strategy, rendering this indicator particularly advantageous for traders focused on long positions. Upon identifying a buy position, the indicator issues a buy signal and subsequently initiates asset tracking. A sell signal is generated only when the indicator identifies substantial uncertainty regarding the continuation of the upward trend. Its simple to use.
ATH Distance HeatmapThe "ATH Distance Heatmap" is a powerful visualization tool designed for traders and investors who seek to quickly assess the relative performance of assets against their All-Time Highs (ATH). By mapping the percentage distance of current prices from their historical peaks, this script provides a unique perspective on market sentiment, potential recovery opportunities, and overvaluation risks.
Key Features:
Visual Clarity: Utilize a color-coded heatmap to instantly recognize which assets are near or far from their ATHs. Colors transition smoothly from cool to warm tones, indicating smaller to larger distances respectively.
Real-Time Updates: The script updates dynamically with live market data, ensuring you have the most current information at your fingertips.
Versatile Application: Whether you're tracking stocks, cryptocurrencies, commodities, or indices, the "ATH Distance Heatmap" adapts to a wide array of assets, making it a versatile tool for your trading arsenal.
Insightful Analysis: Beyond mere visualization, this tool can help identify potential buying opportunities in assets that are significantly below their ATHs, or highlight caution for those nearing their peaks.
How to Use:
Configure Your Assets: Start by selecting the assets you wish to track. The script can be customized to monitor a broad market range or a specific segment.
Interpret the Colors: Use the color gradient to gauge the distance of each asset from its ATH. Cooler colors indicate assets closer to their ATH, while warmer colors highlight those further away.
Ideal for:
Traders looking for a quick visual guide to market trends and asset performance.
Investors aiming to capitalize on recovery opportunities or to evaluate entry and exit points.
Market analysts interested in a concise overview of asset health relative to historical performance.
FlexiSuperTrend - Strategy [presentTrading]█ Introduction and How it is Different
The "FlexiSuperTrend - Strategy" by PresentTrading is a cutting-edge trading strategy that redefines market analysis through the integration of the SuperTrend indicator and advanced variance tracking.
BTC 6H L/S
This strategy stands apart from conventional methods by its dynamic adaptability, capturing market trends and momentum shifts with increased sensitivity. It's designed for traders seeking a more responsive tool to navigate complex market movements.
Local
█ Strategy, How It Works: Detailed Explanation
The "FlexiSuperTrend - Strategy" employs a multifaceted approach, combining the adaptability of the SuperTrend indicator with variance tracking. The strategy's core lies in its unique formulation and application of these components:
🔶 SuperTrend Polyfactor Oscillator:
- Basic Concept: The oscillator is a series of SuperTrend calculations with varying ATR lengths and multipliers. This approach provides a broader and more nuanced perspective of market trends.
- Calculation:
- For each iteration, `i`, the SuperTrend is calculated using:
- `ATR Length = indicatorLength * (startingFactor + i * incrementFactor)`.
- `Multiplier = dynamically adjusted based on market conditions`.
- The SuperTrend output for each iteration is compared with the indicator source (like hlc3), and the deviation is recorded.
SuperTrend Calculation:
- `Upper Band (UB) = hl2 + (ATR Length * Multiplier)`
- `Lower Band (LB) = hl2 - (ATR Length * Multiplier)`
- Where `hl2` is the average of high and low prices.
Deviation Calculation:
- `Deviation = indicatorSource - SuperTrend Value`
- This value is calculated for each SuperTrend setting in the oscillator series.
🔶 Indicator Source (`hlc3`):
- **Usage:** The strategy uses the average of high, low, and close prices, providing a balanced representation of market activity.
🔶 Adaptive ATR Lengths and Factors:
- Dynamic Adjustment: The strategy adjusts the ATR length and multiplier based on the `startingFactor` and `incrementFactor`. This adaptability is key in responding to changing market volatilities.
- Equation: ATR Length at each iteration `i` is given by `len = indicatorLength * (startingFactor + i * incrementFactor)`.
incrementFactor - 1
incrementFactor - 2
🔶 Normalization Methods:
Purpose: To standardize the deviations for comparability.
- Methods:
- 'Max-Min': Scales the deviation based on the range of values.
- 'Absolute Sum': Uses the sum of absolute deviations for normalization.
Normalization 'Absolute Sum'
- For 'Max-Min': `Normalized Deviation = (Deviation - Min(Deviations)) / (Max(Deviations) - Min(Deviations))`
- For 'Absolute Sum': `Normalized Deviation = Deviation / Sum(Absolute(Deviations))`
🔶 Trading Logic:
The strategy integrates the SuperTrend indicator, renowned for its effectiveness in identifying trend direction and reversals. The SuperTrend's incorporation enhances the strategy's ability to filter out false signals and confirm genuine market trends. * The SuperTrend Toolkit is made by @QuantiLuxe
- Long Entry Conditions: A buy signal is generated when the current trend, as indicated by the SuperTrend Polyfactor Oscillator, turns positive.
- Short Entry Conditions: A sell signal is triggered when the current trend turns negative.
- Entry and Exit Strategy: The strategy opens or closes positions based on these signals, aligning with the selected trade direction (long, short, or both).
█ Trade Direction
The strategy is versatile, allowing traders to choose their preferred trading direction: long, short, or both. This flexibility enables traders to tailor their strategies to their market outlook and risk appetite.
█ Usage
The FlexiSuperTrend strategy is suitable for various market conditions and can be adapted to different asset classes and time frames. Traders should set the strategy parameters according to their risk tolerance and trading goals. It's particularly useful for capturing long-term movements, ideal for swing traders, yet adaptable for short-term trading strategies.
█ Default Settings
1. Trading Direction: Choose from "Long", "Short", or "Both" to define the trade type.
2. Indicator Source (HLC3): Utilizes the HLC3 as the primary price reference.
3. Indicator Length (Default: 10): Influences the moving average calculation and trend sensitivity.
4. Starting Factor (0.618): Initiates the ATR length, influenced by Fibonacci ratios.
5. Increment Factor (0.382): Adjusts the ATR length incrementally for dynamic trend tracking.
6. Normalization Method: Options include "None", "Max-Min", and "Absolute Sum" for scaling deviations.
7. SuperTrend Settings: Varied ATR lengths and multipliers tailor the indicator's responsiveness.
8. Additional Settings: Features mesh style plotting and customizable colors for visual distinction.
The default settings provide a balanced approach, but users are encouraged to adjust them based on their individual trading style and market analysis.
lib_retracement_patternsLibrary "lib_retracement_patterns"
types and functions for XABCD pattern detection and plotting
method set_tolerances(this, tolerance_Bmin, tolerance_Bmax, tolerance_Cmin, tolerance_Cmax, tolerance_Dmin, tolerance_Dmax)
sets tolerances for B, C and D retracements. This creates another Pattern instance that is set as tolerances field on the original and will be used for detection instead of the original ratios.
Namespace types: Pattern
create_config(pattern_line_args, pattern_point_args, name_label_args, retracement_line_args, retracement_label_args, line_args_Dtarget, line_args_completion, line_args_tp1, line_args_tp2, line_args_sl, label_args_completion, label_args_tp1, label_args_tp2, label_args_sl, label_terminal, label_terminal_up_char, label_terminal_down_char, color_bull, color_bear, color_muted, fill_opacity, draw_point_labels, draw_retracements, draw_target_range, draw_levels, hide_shorter_if_shared_legs_greater_than_max, hide_engulfed_pattern, hide_engulfed_pattern_of_same_type, hide_longer_pattern_with_same_X, mute_previous_pattern_when_next_overlaps, keep_failed_patterns)
method direction(this)
Namespace types: Match
method length(this)
return the length of this pattern, determined by the distance between X and D point
Namespace types: Match
method height(this)
return the height of this pattern, determined by the distance between the biggest distance between A/C and X/D
Namespace types: Match
method is_forming(this)
returns true if not complete, not expired and not invalidated
Namespace types: Match
method tostring(this)
return a string representation of all Matches in this map
Namespace types: Match
method tostring(this)
Namespace types: map
remove_complete_and_expired(this)
method add(this, item)
Namespace types: map
method is_engulfed_by(this, other)
checks if this Match is engulfed by the other
Namespace types: Match
method update(tracking_matches, zigzag, patterns, max_age_idx, detect_dir, pattern_minlen, pattern_maxlen, max_sub_waves, max_shared_legs, max_XB_BD_ratio, debug_log)
checks this map of tracking Matches if any of them was completed or invalidated in
Namespace types: map
method mute(this, mute_color, mute_fill_color)
mute this pattern by making it all one color (lines and labels, for pattern fill there's another)
Namespace types: Match
method mute(this, mute_color, mute_fill_color)
mute all patterns in this map by making it all one color (lines and labels, for pattern fill there's another)
Namespace types: map
method hide(this)
hide this pattern by muting it with a transparent color
Namespace types: Match
method reset_styles(this)
reset the style of a muted or hidden match back to the preset configuration
Namespace types: Match
method delete(this)
remove the plot of this Match from the chart
Namespace types: Match
method delete(this)
remove all the plots of the Matches in this map from the chart
Namespace types: map
method draw(this)
draw this Match on the chart
Namespace types: Match
method draw(this, config, all_patterns, debug_log)
draw all Matches in this map, considering all other patterns for engulfing and overlapping
Namespace types: map
method check_hide_or_mute(this, all, config, debug_log)
checks if this pattern needs to be hidden or muted based on other plotted patterns and given configuration
Namespace types: Match
method add_if(id, item, condition)
convenience function to add a search pattern to a list, only if given condition (input.bool) is true
Namespace types: Pattern
Pattern
type to hold retracement ratios and tolerances for this pattern, as well as targets for trades
Config
allows control of pattern plotting shape and colors, as well as settings for hiding overlapped patterns etc.
Match
holds all information on a Pattern and a successful match in the chart. Includes XABCD pivot points as well as all Line and Label objects to draw it
ICT Donchian Smart Money Structure (Expo)█ Concept Overview
The Inner Circle Trader (ICT) methodology is focused on understanding the actions and implications of the so-called "smart money" - large institutions and professional traders who often influence market movements. Key to this is the concept of market structure and how it can provide insights into potential price moves.
Over time, however, there has been a notable shift in how some traders interpret and apply this methodology. Initially, it was designed with a focus on the fractal nature of markets. Fractals are recurring patterns in price action that are self-similar across different time scales, providing a nuanced and dynamic understanding of market structure.
However, as the ICT methodology has grown in popularity, there has been a drift away from this fractal-based perspective. Instead, many traders have started to focus more on pivot points as their primary tool for understanding market structure.
Pivot points provide static levels of potential support and resistance. While they can be useful in some contexts, relying heavily on them could provide a skewed perspective of market structure. They offer a static, backward-looking view that may not accurately reflect real-time changes in market sentiment or the dynamic nature of markets.
This shift from a fractal-based perspective to a pivot point perspective has significant implications. It can lead traders to misinterpret market structure and potentially make incorrect trading decisions.
To highlight this issue, you've developed a Donchian Structure indicator that mirrors the use of pivot points. The Donchian Channels are formed by the highest high and the lowest low over a certain period, providing another representation of potential market extremes. The fact that the Donchian Structure indicator produces the same results as pivot points underscores the inherent limitations of relying too heavily on these tools.
While the Donchian Structure indicator or pivot points can be useful tools, they should not replace the original, fractal-based perspective of the ICT methodology. These tools can provide a broad overview of market structure but may not capture the intricate dynamics and real-time changes that a fractal-based approach can offer.
It's essential for traders to understand these differences and to apply these tools correctly within the broader context of the ICT methodology and the Smart Money Concept Structure. A well-rounded approach that incorporates fractals, along with other tools and forms of analysis, is likely to provide a more accurate and comprehensive understanding of market structure.
█ Smart Money Concept - Misunderstandings
The Smart Money Concept is a popular concept among traders, and it's based on the idea that the "smart money" - typically large institutional investors, market makers, and professional traders - have superior knowledge or information, and their actions can provide valuable insight for other traders.
One of the biggest misunderstandings with this concept is the belief that tracking smart money activity can guarantee profitable trading.
█ Here are a few common misconceptions:
Following Smart Money Equals Guaranteed Success: Many traders believe that if they can follow the smart money, they will be successful. However, tracking the activity of large institutional investors and other professionals isn't easy, as they use complex strategies, have access to information not available to the public, and often intentionally hide their moves to prevent others from detecting their strategies.
Instantaneous Reaction and Results: Another misconception is that market movements will reflect smart money actions immediately. However, large institutions often slowly accumulate or distribute positions over time to avoid moving the market drastically. As a result, their actions might not produce an immediate noticeable effect on the market.
Smart Money Always Wins: It's not accurate to assume that smart money always makes the right decisions. Even the most experienced institutional investors and professional traders make mistakes, misjudge market conditions, or are affected by unpredictable events.
Smart Money Activity is Transparent: Understanding what constitutes smart money activity can be quite challenging. There are many indicators and metrics that traders use to try and track smart money, such as the COT (Commitments of Traders) reports, Level II market data, block trades, etc. However, these can be difficult to interpret correctly and are often misleading.
Assuming Uniformity Among Smart Money: 'Smart Money' is not a monolithic entity. Different institutional investors and professional traders have different strategies, risk tolerances, and investment horizons. What might be a good trade for a long-term institutional investor might not be a good trade for a short-term professional trader, and vice versa.
█ Market Structure
The Smart Money Concept Structure deals with the interpretation of price action that forms the market structure, focusing on understanding key shifts or changes in the market that may indicate where 'smart money' (large institutional investors and professional traders) might be moving in the market.
█ Three common concepts in this regard are Change of Character (CHoCH), and Shift in Market Structure (SMS), Break of Structure (BMS/BoS).
Change of Character (CHoCH): This refers to a noticeable change in the behavior of price movement, which could suggest that a shift in the market might be about to occur. This might be signaled by a sudden increase in volatility, a break of a trendline, or a change in volume, among other things.
Shift in Market Structure (SMS): This is when the overall structure of the market changes, suggesting a potential new trend. It usually involves a sequence of lower highs and lower lows for a downtrend, or higher highs and higher lows for an uptrend.
Break of Structure (BMS/BoS): This is when a previously defined trend or pattern in the price structure is broken, which may suggest a trend continuation.
A key component of this approach is the use of fractals, which are repeating patterns in price action that can give insights into potential market reversals. They appear at all scales of a price chart, reflecting the self-similar nature of markets.
█ Market Structure - Misunderstandings
One of the biggest misunderstandings about the ICT approach is the over-reliance or incorrect application of pivot points. Pivot points are a popular tool among traders due to their simplicity and easy-to-understand nature. However, when it comes to the Smart Money Concept and trying to follow the steps of professional traders or large institutions, relying heavily on pivot points can create misconceptions and lead to confusion. Here's why:
Delayed and Static Information: Pivot points are inherently backward-looking because they're calculated based on the previous period's data. As such, they may not reflect real-time market dynamics or sudden changes in market sentiment. Furthermore, they present a static view of market structure, delineating pre-defined levels of support and resistance. This static nature can be misleading because markets are fundamentally dynamic and constantly changing due to countless variables.
Inadequate Representation of Market Complexity: Markets are influenced by a myriad of factors, including economic indicators, geopolitical events, institutional actions, and market sentiment, among others. Relying on pivot points alone for reading market structure oversimplifies this complexity and can lead to a myopic understanding of market dynamics.
False Signals and Misinterpretations: Pivot points can often give false signals, especially in volatile markets. Prices might react to these levels temporarily but then continue in the original direction, leading to potential misinterpretation of market structure and sentiment. Also, a trader might wrongly perceive a break of a pivot point as a significant market event, when in fact, it could be due to random price fluctuations or temporary volatility.
Over-simplification: Viewing market structure only through the lens of pivot points simplifies the market to static levels of support and resistance, which can lead to misinterpretation of market dynamics. For instance, a trader might view a break of a pivot point as a definite sign of a trend, when it could just be a temporary price spike.
Ignoring the Fractal Nature of Markets: In the context of the Smart Money Concept Structure, understanding the fractal nature of markets is crucial. Fractals are self-similar patterns that repeat at all scales and provide a more dynamic and nuanced understanding of market structure. They can help traders identify shifts in market sentiment or direction in real-time, providing more relevant and timely information compared to pivot points.
The key takeaway here is not that pivot points should be entirely avoided or that they're useless. They can provide valuable insights and serve as a useful tool in a trader's toolbox when used correctly. However, they should not be the sole or primary method for understanding the market structure, especially in the context of the Smart Money Concept Structure.
█ Fractals
Instead, traders should aim for a comprehensive understanding of markets that incorporates a range of tools and concepts, including but not limited to fractals, order flow, volume analysis, fundamental analysis, and, yes, even pivot points. Fractals offer a more dynamic and nuanced view of the market. They reflect the recursive nature of markets and can provide valuable insights into potential market reversals. Because they appear at all scales of a price chart, they can provide a more holistic and real-time understanding of market structure.
In contrast, the Smart Money Concept Structure, focusing on fractals and comprehensive market analysis, aims to capture a more holistic and real-time view of the market. Fractals, being self-similar patterns that repeat at different scales, offer a dynamic understanding of market structure. As a result, they can help to identify shifts in market sentiment or direction as they happen, providing a more detailed and timely perspective.
Furthermore, a comprehensive market analysis would consider a broader set of factors, including order flow, volume analysis, and fundamental analysis, which could provide additional insights into 'smart money' actions.
█ Donchian Structure
Donchian Channels are a type of indicator used in technical analysis to identify potential price breakouts and trends, and they may also serve as a tool for understanding market structure. The channels are formed by taking the highest high and the lowest low over a certain number of periods, creating an envelope of price action.
Donchian Channels (or pivot points) can be useful tools for providing a general view of market structure, and they may not capture the intricate dynamics associated with the Smart Money Concept Structure. A more nuanced approach, centered on real-time fractals and a comprehensive analysis of various market factors, offers a more accurate understanding of 'smart money' actions and market structure.
█ Here is why Donchian Structure may be misleading:
Lack of Nuance: Donchian Channels, like pivot points, provide a simplified view of market structure. They don't take into account the nuanced behaviors of price action or the complex dynamics between buyers and sellers that can be critical in the Smart Money Concept Structure.
Limited Insights into 'Smart Money' Actions: While Donchian Channels can highlight potential breakout points and trends, they don't necessarily provide insights into the actions of 'smart money'. These large institutional traders often use sophisticated strategies that can't be easily inferred from price action alone.
█ Indicator Overview
We have built this Donchian Structure indicator to show that it returns the same results as using pivot points. The Donchian Structure indicator can be a useful tool for market analysis. However, it should not be seen as a direct replacement or equivalent to the original Smart Money concept, nor should any indicator based on pivot points. The indicator highlights the importance of understanding what kind of trading tools we use and how they can affect our decisions.
The Donchian Structure Indicator displays CHoCH, SMS, BoS/BMS, as well as premium and discount areas. This indicator plots everything in real-time and allows for easy backtesting on any market and timeframe. A unique candle coloring has been added to make it more engaging and visually appealing when identifying new trading setups and strategies. This candle coloring is "leading," meaning it can signal a structural change before it actually happens, giving traders ample time to plan their next trade accordingly.
█ How to use
The indicator is great for traders who want to simplify their view on the market structure and easily backtest Smart Money Concept Strategies. The added candle coloring function serves as a heads-up for structure change or can be used as trend confirmation. This new candle coloring feature can generate many new Smart Money Concepts strategies.
█ Features
Market Structure
The market structure is based on the Donchian channel, to which we have added what we call 'Structure Response'. This addition makes the indicator more useful, especially in trending markets. The core concept involves traders buying at a discount and selling or shorting at a premium, depending on the order flow. Structure response enables traders to determine the order flow more clearly. Consequently, more trading opportunities will appear in trending markets.
Structure Candles
Structure Candles highlight the current order flow and are significantly more responsive to structural changes. They can provide traders with a heads-up before a break in structure occurs
-----------------
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!
Adjusted OBVThis script shows On-Balance Volume adjusted for volume weighted candle body size.
This means that the wick lengths, body length, and sell/buy pressure are calculated into percentages of volume that contributed to each.
The body volume is the accumulatively tracked across candles to give a more accurate On-Balance Volume that has been traded to achieve the current price over time.
The script output is in Orange and for comparison the original technical OBV is in Blue.
As this is my first script, I hope to update it to include a 'buy' and 'sell' pressure gauge to perhaps turn this from a mere indicator into potentially a bit more predictive.
In the meantime, it should be useful for tracking OBV for other uses in a more accurate and less volatile way.
Cuban's Open Interest Spaghetti [CE]Cuban's Open Interest Spaghetti is an indicator built for traders to track the open interest changes of highly correlated markets, spreads, and ecosystems.
The tool provides three different viewing modes for tracking open interest; a rolling bar lookback, a specific data and time anchor, and a visible range -- similar to the native Tradingview 'Compare' tool.
Included are pre-built lists for tracking the open interest of all 160+ Binance Futures assets, including custom fields for creating new spreads or watchlists. This gives the trader the ability to monitor the entire futures ecosystem within a single charting window.
We have also added an optional table to the right of the screen so that the trader can clearly see outperforming assets. This table is toggleable using radio buttons within the Style menu.
To improve asset visibility, the script also calculates the 'long tail' of the asset distribution and automatically lowers the visibility of clustered assets in the center.
While the Compare tool only allows for % returns and absolute value on the chart asset or separate scale, Cuban's Open Interest Spaghetti allows the trader to use a separate oscillator window with the open interest on a % scale. This gives the trader the ability to watch OI changes in real-time within any Tradingview window.
Within the user inputs, the user gains the ability to customize the following:
Lookback mode
Rolling lookback period
Timezone and time anchor
Percentage of assets highlighted
Dynamic label offset
Asset lists
TO DO:
Add % labels to assets in the tails of the distribution
Expected Move w/ Volatility Panel (advanced) [Loxx]This indicator shows the expected range of movement of price given the assumption that price is log-normally distributed. This includes 3 multiples of standard deviation and 1 user selected level input as a multiple of standard deviation. Expected assumes that volatility remains static on the next bar. In reality, this may or may not be the case, so use caution when making broad assumptions about the levels shown when using this indicator. However, these levels match the same levels on Loxx's backtests and Multi-Panel indicator. These static levels are used as the take profit targets and stoploss on all Loxx's scripts previously posted.
This indicator can be be used on all timeframes, but the internal timeframe must be higher than the current timeframe or an error is thrown. The purpose for internal MTF is so that you can track the deviation range from higher timeframes on lower timeframes. When "current bar" is selected, this indicator will change with live prices changes. This is useful if you wish to enter a trade before the current bar closes and need to know the deviation ranges before the close. Current bar is also useful to see the past ranges of literally that bar. When "past bar" is selected, then the values shown on the current bar are values that were calculated on the last bar. The previous bar setting is useful to track price changes with the assumption that you entered a trade at the close of the previous bar. The default set to the previous bar. (careful, this default setting won't match Loxx's Muti-Panel tool since the Multi-Panel is built using the current bar. To make them match, you must change this setting to current bar)
I've included the ability for you to smooth the output around a moving average. Included are Loxx's Moving Averages. There are 41 to choose from. See more details here:
Smoothing applied yielding Keltner Channels
Also included are various UI options to manipulate line styling and colors.
Volatility Panel
Shows information about user selected volatility included confidence range of the chosen volatility. The following volatility types are included with additional volatility types to added in future releases.
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Chi-squared Confidence Interval:
Confidence interval of volatility is calculated using an inverse CDF of a Chi-Squared Distribution. You can change the volatility input used to either realized, upper confidence interval, or lower confidence interval. This is included in case you'd like to see how far price can extend if volatility hits it's upper or lower confidence levels. Generally, you'd just used realized volatility , so I wouldn't change this setting.
Inverse CDF of a Chi-Squared Distribution
The chi-square distribution is a one-parameter family of curves. The parameter ν is the degrees of freedom.
The icdf of the chi-square distribution is
x=F^−1(p∣ν) = {x:F(x∣ν) = p}
where
p=F(x∣ν)= ∫ (t^(v-2)/2 * e^t/2) / (2^(v/2) / Γ(v/2))
ν is the degrees of freedom, and Γ( · ) is the Gamma function. The result p is the probability that a single observation from the chi-square distribution with ν degrees of freedom falls in the interval .
Related Indicators
Multi-Panel: Trade-Volatility-Probability
Variety Distribution Probability Cone
[PlayBit] FVG/EMAThis Indicator was made for the PlayBit Community by @FFriZz
This indicator includes 2 of the most used indicators within the community
1. FVG indicator -- Very minimalistic version seems to be the most used
2. EMA indicator -- Indicator made by using two 200 EMAs one tracking highs and one tracking closes -- to form a 200 EMA Channel
-- The EMA Can be used as a single one on the current chart or there are 5 other options that will allow you to track up to 5 timeframes
higher or lower
----- Options ------
-- FVGs --
1. Ability to keep FVGs on chart when Filled/Mitigated or have them Deleted
2. Setting to Change the border of the FVG when it has been tested
3. Can have the FVGs resize to the untapped area
4. Setting to adjust the number of FVGs that are displayed on Chart at a time
-- EMA --
1. Up to 5 Different timeframes
2. Color Switch if close is above or below EMAs
3. Color Settings
Shout out to the PlayBit Community
for being a great community for Trading and in general!
If anyone finds any bugs Please let me know on here or on PlayBit
or if I removed something in this version you would like to see put back..
Hope you enjoy!
@FFriZz | @FrizLabz
WilliamTrendFollowerWith this indicator, we try to catch the trends in price. With continued use of this indicator, we expect it to eventually escape horizontal positions and catch up with continuous trends.
Combined with the WilliamsR indicator and the exponential moving average indicator.
The WilliamsR Fisher Transforms are combined with the ATR indicator to create a line that lags behind the moving average value.
Since it is a tracking indicator, we created a line that is more connected to the price and itself.
In this way, a curve close to the price line is obtained in uptrends and downtrends.
In this indicator, if you choose the parameters correctly, you can easily bypass the horizontal positions. This gives you a safe visualization of support and resistance points as well.
With this tracker, you can generate Buy and Sell signals and you can see them on the chart.
From the settings of these indicators, you can set the multiplier and the exponential moving average period.
It works in all time intervals.
But it was calculated without volume , instead it was created using fisher transforms, moving averages, and the average true range .
You can set an alarm for Buy and Sell orders.
You can see the processing entry and exit areas in a straight line.
The Fisher Transform indicator is an oscillator that helps identify trend reversals and can be applied to any financial instrument. J.F. Created by Ehlers
Triple CSWhat this indicator does:
This indicator will be scanning for ranges of extremity.
It measures multiple underlying factors in the financial markets like measuring levels of strength using RSI, momentum using Stochastics and extreme ranges using Bollinger Bands.
What is "extreme range" criteria: ranges above 70 or below 30 on RSI and Stoch are considered extreme, as well as moments of extreme volatility exceeding overbought and oversold levels on BBs.
All monitored data is to be plotted in a horizontal row, providing information about oversold, overbought and mid-range market conditions. This data will either meet the criteria simultaneously and plot a Red or Green indication or it will miss one or more requirements, plotting Gray indications.
This indicator is a real-time indicator, meaning it's updating live and due to this tracking in real-time, indications not yet 'printed' can give false readings. For performance purposes, it is best practice to allow all indication plots to 'print', meaning if a plot ever changes in color, it's best to allow that candle to fully close , ticking to 0:00 before confirming the accuracy of the indicator's findings.
How it works:
This indicator scans multiple sources of data simultaneously. When appropriate conditions within a trading range are met, the indicator will update it's color.
The indicator will plot Gray , Green , and Red indications which can be explained below.
-
Grey plots : No indication of full extremity, meaning one or more conditions being tracked has not met requirements, suggesting price is likely in mid-range.
-
Green plots : Extremity level lows have been simultaneously met, data indicates extreme oversold conditions are likely present.
-
Red plots : Extremity level highs have been simultaneously met, data indicates extreme overbought conditions are likely present.
What market will this indicator work on?
Stocks > Forex > Crypto
All the above are supported by this indicator.
Charts with more history have more data for the indicator to utilize. (Lack of data can result in poor performance.)
- This indicator performs best on 4H, 12H, D, and W timeframes, although you can use this indicator on any timeframe TradingView supports.
This indicator was created to find ranges of extreme trade which can help traders be more confident in their timing with the market.
Trading can be difficult, let an algorithm scan the market and monitor for early signs of volatility changes.
Past performance does not guarantee future results. Please do your due diligence when placing trades.
Compare Crypto Bollinger Bands//This is not financial advice, I am not a financial advisor.
//What are volatility tokens?
//Volatility tokens are ERC-20 tokens that aim to track the implied volatility of crypto markets.
//Volatility tokens get their exposure to an asset’s implied volatility using FTX MOVE contracts.
//There are currently two volatility tokens: BVOL and IBVOL.
//BVOL targets tracking the daily returns of being 1x long the implied volatility of BTC
//IBVOL targets tracking the daily returns of being 1x short the implied volatility of BTC.
/////////////////////////////////////////////////////////////////
CAN USE ON ANY CRYPTO CHART AS BINANCE:BTCUSD is still the most dominant crypto, positive volatility for BTC is positive for all.
/////////////////////////////////////////////////////////////////
//The Code.
//The blue line (ChartLine) is the current chart plotted on in Bollinger
//The red line (BVOLLine) plots the implied volatility of BTC
//The green line (IBVOLLine) plot the inverse implied volatility of BTC
//The orange line (TOTALLine) plots how well the crypto market is performing on the Bolling scale. The higher the number the better.
//There are 2 horizontal lines, 0.40 at the bottom & 0.60 at the top
/////////To Buy
//1. The blue line (ChartLine) must be higher than the green line (IBVOLLine)
//2. The green line (IBVOLLine) must be higher than the red line (BVOLLine)
//3. The red line (BVOLLine) must be less than 0.40 // This also acts as a trendsetter
//4. The orange line (TOTALLine) MUST be greater than the red line. This means that the crypto market is positive.
//5.IF THE BLUE LINE (ChartLine) IS GREATER THAN THE ORANGE LINE (TOTALLine) IT MEANS YOUR CRYPTO IS OUTPERFOMING THE MARKET {good for short term explosive bars}
//6. If the orange line (TOTALLine) is higher than your current chart, say BTCUSD. And BTC is going up to. It just means BTC is going up slowly. it's fine as long as they are moving in the same position.
//5. I use this on the 4hr, 1D, 1W timeframes
///////To Exit
//1.If the blue line (ChartLine) crosses under the green line (IBVOLLine) exit{ works best on 4hr,1D, 1W to avoid fakes}
//2.If the red line crosses over the green line when long. {close positions, or watch positions} It means negative volatility is wining
RedK Compound Ratio Moving Average (CoRa_Wave)
Compound Ratio Weighted Average (CoRa_Wave) is a moving average where the weights increase in a "logarithmically linear" way - from the furthest point in the data to the current point - the formula to calculate these weights work in a similar way to how "compound ratio" works - you start with an initial amount, then add a consistent "ratio of the cumulative prior sum" each period until you reach the end amount. The result is, the "step ratio" between the weights is consistent - This is not the case with linear-weights moving average (WMA), or EMA
- for example, if you consider a Weighted Moving Average (WMA) of length 5, the weights will be (from the furthest point towards the most current) 1, 2, 3, 4, 5 -- we can see that the ratio between these weights are inconsistent. in fact, the ratio between the 2 furthest points is 2:1, but the ratio between the most recent points is 5:4 -- the ratio is inconsistent, and in fact, more recent points are not getting the best weights they should/can get to counter-act the lag effect. Using the Compound ratio approach addresses that point.
a key advantage here is that we can significantly reduce the "tail weight" - which is "relatively" large in other MAs and would be main cause for lag - giving more weights to the most recent data points - and in a way that is consistent, reliable and easy to "code"
- the outcome is, a moving average line that suffers very little lag regardless of the length, and that can be relied on to track the price movements and swings closely.
other features:
===============
- An accelerator, or multiplier, has been added to further increase the "aggressiveness" of the moving average line, giving even more weights to the more recent points - the multiplier will have more effect between 1 and 5, then will have a diminishing effect after that - note that a multiplier of 0 (which effectively causes a comp. ratio of 0 to be applied) will produce a Simple Moving Average line :)
- We also added the ability to use an "automatic smoothing" mechanism, that user can over-ride by manually choosing how much smoothing is used. This gives more flexibility to how we can leverage this Moving Average in our charting.
- User can also select the Resolution and Source price for the CoRa_Wave. by default, they will be set to "same as chart" and hlc3
here are the formulas for our Compound Ratio moving average:
Compound Weight ratio r = (A/P)^1/t - 1
Weight at time t A = P(1 + r)^t
= Start_val * (1 + r) ^ index
index in the above formula is 0 for the furthest point out
Here's how CoRa_Wave compares to other common moving averages all set to the same length (20)
Proposed Usage
- CoRa_Wave can be used for any scenarios where we need a moving average that closely tracks the price, trend, swings with high responsiveness and little lag
- MA Cross-over scenarios - against another CoRa_Wave or any other MA
- below is a quick example scenario for how to utilize 2 CoRa_Wave lines of same length (one for open and one for closing price) to track swings and trends
- get as creative as you need :)
Code is commented - please feel free to leverage or customize further as you need.
👉 if you are interested in other moving averages i posted before, please check out the FiMA and the v_Wave ...
Reversal Algo (Expo)"It has never been easier to find high probability trades"
Reversal Algo (Expo) is an automated Reversal System that analyzes the market in real-time and identifies high probability short term and long term trend reversal- and scalping signals as well as key market zones, and trends. The adaptive and unique reversal bands act as support & resistance zones, and together with the trend tracking feature, it serves as a trend confirmation. The system does also comes with a Top & Bottom finder that detects potential tops and bottoms that can be used as scalping entries or take profit points.
This Reversal System is developed to catch both short term and long term trend reversal and provide clarity in the current trend direction. The system aims to make it easier to come in early in a new trend as well as to stay longer in that trend. One of the main features is that the system has already filtered out false and choppy signals and aims to leave the most accurate ones.
One of the main goals was to make a system that works well without having Heiken Ashi candles. However, if you apply the system to Heiken Ashi candles you will have an additional layer of noise filtering.
Key differences between Trend Algo and Reversal Algo are that Reversal Algo is more responsive to price action and has a dynamic and adaptive Reversal cloud. The Reversal Algo does also has the tops/bottoms finder. These two systems can be used together.
The user can enable the following:
ATR Trailing Stop - Helps to identify the trend as well as where to have your stop loss.
Trend Tracking Line - Helps to identify Strong trends and areas of trend reversals.
Trend Steps- Helps to highlight where the current trend direction has found a new base.
Reversal Band - Helps to identify the trading range, strong trends, and areas of reversals.
Trend Scalping Dots - Helps to keep track of the short term price action.
Noise- and Signal filters:
Depending on your trading style you can choose between different trend filters and signals sensitivities.
Real-Time Alerts
No Repainting
Works on any market and in any timeframe
The indicator can be used standalone or as a part of your current trading strategy.
HOW TO USE
Use the indicator to identify reversal signals.
Use the indicator to identify trends.
Use the indicator to identify tops & bottoms signals.
Use the indicator to identify scalping signals.
INDICATOR IN ACTION
1-hour chart
Top/Bottom Finder
1-hour chart
I hope you find this indicator useful , and please comment or contact me if you like the script or have any questions/suggestions for future improvements. Thanks!
I will continually work on this indicator, so please share your experience and feedback as it will enable me to make even better improvements. Thanks to everyone that has already contacted me regarding my scripts. Your feedback is valuable for future developments!
-----------------
Disclaimer
Copyright by Zeiierman.
The information contained in my scripts/indicators/ideas 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, 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/strategies/ideas are only for educational purposes!
ACCESS THE INDICATOR
• Contact me on TradingView or use the links below
ACAT (450-600 Hi-Res) [acatwithcharts]Adaptive Comprehensive Average Tracker is a 2 in 1 version of Mean Reversion MA and Compression MA. The slightly odd name is a backronym that spells "ACAT" - suffice it to say, I'm pretty proud of what these two indicators have developed into.
This is 4 of 4 in a series of Hi-Res indicators from 14-600 that are intended to be used in concert weaved together. Some of the default display settings are slightly tweaked to account for the assumption that they would not be used by themselves individual. The labels are intended to weave with the other instances of ACAT, which is very obviously not something that was designed for in the v4 labeling code and works about as passably well as I could get it, noting that coming up with a method for setting variable distances that always looks sharp across instruments and timeframes is near-impossible.
Compared to what subscribers will be used to from using standard resolution ACAT, this should greatly sharpen the borders of the compression bands in particular. A key caveat to be aware of is that dividing the range into multiple instances like this means that there can be tracking of several distributions at the same time if different indicators are triggering independently after being reset on different ranges - which in some cases means more relevant periods are being identified but often times can mean a mess of information with some less important periods being overlaid as if they were of equal importance to the longest period lengths.
My volatility indicators are available by subscription in several packages through SharkCharts.live - and this is planned to be the first new one ready to add. I plan to on totally overhauling my explanation videos on ACAT since the indicator just does so much more than it used to when the previous videos were recorded, but as of the time of this writing the videos on Mean Reversion MA, Compression MA, and my livestream with DadShark do cover most parts of it. These videos and videos on my other indicators are currently hosted on DadShark's YouTube channel.
Current pricing and subscription details will be kept up-to-date on SharkCharts.live
ACAT (300-450 Hi-Res) [acatwithcharts]Adaptive Comprehensive Average Tracker is a 2 in 1 version of Mean Reversion MA and Compression MA. The slightly odd name is a backronym that spells "ACAT" - suffice it to say, I'm pretty proud of what these two indicators have developed into.
This is 3 of 4 in a series of Hi-Res indicators from 14-600 that are intended to be used in concert weaved together. Some of the default display settings are slightly tweaked to account for the assumption that they would not be used by themselves individual. The labels are intended to weave with the other instances of ACAT, which is very obviously not something that was designed for in the v4 labeling code and works about as passably well as I could get it, noting that coming up with a method for setting variable distances that always looks sharp across instruments and timeframes is near-impossible.
Compared to what subscribers will be used to from using standard resolution ACAT, this should greatly sharpen the borders of the compression bands in particular. A key caveat to be aware of is that dividing the range into multiple instances like this means that there can be tracking of several distributions at the same time if different indicators are triggering independently after being reset on different ranges - which in some cases means more relevant periods are being identified but often times can mean a mess of information with some less important periods being overlaid as if they were of equal importance to the longest period lengths.
My volatility indicators are available by subscription in several packages through SharkCharts.live - and this is planned to be the first new one ready to add. I plan to on totally overhauling my explanation videos on ACAT since the indicator just does so much more than it used to when the previous videos were recorded, but as of the time of this writing the videos on Mean Reversion MA, Compression MA, and my livestream with DadShark do cover most parts of it. These videos and videos on my other indicators are currently hosted on DadShark's YouTube channel.
Current pricing and subscription details will be kept up-to-date on SharkCharts.live
ACAT (150-300 Hi-Res) [acatwithcharts]Adaptive Comprehensive Average Tracker is a 2 in 1 version of Mean Reversion MA and Compression MA. The slightly odd name is a backronym that spells "ACAT" - suffice it to say, I'm pretty proud of what these two indicators have developed into.
This is 2 of 4 in a series of Hi-Res indicators from 14-600 that are intended to be used in concert weaved together. Some of the default display settings are slightly tweaked to account for the assumption that they would not be used by themselves individual. The labels are intended to weave with the other instances of ACAT, which is very obviously not something that was designed for in the v4 labeling code and works about as passably well as I could get it, noting that coming up with a method for setting variable distances that always looks sharp across instruments and timeframes is near-impossible.
Compared to what subscribers will be used to from using standard resolution ACAT, this should greatly sharpen the borders of the compression bands in particular. A key caveat to be aware of is that dividing the range into multiple instances like this means that there can be tracking of several distributions at the same time if different indicators are triggering independently after being reset on different ranges - which in some cases means more relevant periods are being identified but often times can mean a mess of information with some less important periods being overlaid as if they were of equal importance to the longest period lengths.
My volatility indicators are available by subscription in several packages through SharkCharts.live - and this is planned to be the first new one ready to add. I plan to on totally overhauling my explanation videos on ACAT since the indicator just does so much more than it used to when the previous videos were recorded, but as of the time of this writing the videos on Mean Reversion MA, Compression MA, and my livestream with DadShark do cover most parts of it. These videos and videos on my other indicators are currently hosted on DadShark's YouTube channel.
Current pricing and subscription details will be kept up-to-date on SharkCharts.live
ACAT (14-150 Hi-Res) [acatwithcharts]Adaptive Comprehensive Average Tracker is a 2 in 1 version of Mean Reversion MA and Compression MA. The slightly odd name is a backronym that spells "ACAT" - suffice it to say, I'm pretty proud of what these two indicators have developed into.
This is 1 of 4 in a series of Hi-Res indicators from 14-600 that are intended to be used in concert weaved together. Some of the default display settings are slightly tweaked to account for the assumption that they would not be used by themselves individual. The labels are intended to weave with the other instances of ACAT, which is very obviously not something that was designed for in the v4 labeling code and works about as passably well as I could get it, noting that coming up with a method for setting variable distances that always looks sharp across instruments and timeframes is near-impossible.
Compared to what subscribers will be used to from using standard resolution ACAT, this should greatly sharpen the borders of the compression bands in particular. A key caveat to be aware of is that dividing the range into multiple instances like this means that there can be tracking of several distributions at the same time if different indicators are triggering independently after being reset on different ranges - which in some cases means more relevant periods are being identified but often times can mean a mess of information with some less important periods being overlaid as if they were of equal importance to the longest period lengths.
My volatility indicators are available by subscription in several packages through SharkCharts.live - and this is planned to be the first new one ready to add. I plan to on totally overhauling my explanation videos on ACAT since the indicator just does so much more than it used to when the previous videos were recorded, but as of the time of this writing the videos on Mean Reversion MA, Compression MA, and my livestream with DadShark do cover most parts of it. These videos and videos on my other indicators are currently hosted on DadShark's YouTube channel.
Current pricing and subscription details will be kept up-to-date on SharkCharts.live
SD85 My Special MACD v2Hello and welcome to SD85!
Happy holiday and happy new year. As a gift, I want to give people a stable tool to help us trade successfully.
If I do help us trade, please consider to donate to our paypal account, I would really apprectiated: ZonnieAdvertising@gmail.com
Here is an updated version of our special MACD, version 2. The sole purpose of this indicator is to track the movement and momentum of any market or any instrument. This is an important concept to keep in mind. This is built as an oscullator so also keep this in mind for the 80,20 levels for overbought and oversold respectively. This special MACD has three values: the current trend, mid trend, and higher trend and a fill from 45 to 55 that tracks the value of mid and high trend: higher trend is greater than mid trend, it's green; higher trend is lesser than mid trend, it's red.
Most important concept for this indicator: The current trend and mid trend will always want to get back with the higher trend; therefore, always keep track of the higher trend and trade accordingly.
It's important to trade with sound money management( trade with a maximum of 2% of your balance) and with a higher time frame (minimum of 4-hour chart). With that being said, it is safer to trade with the higher trend. Although, it is also many times, rewarding to try to catch the beginning of a reversal/trend change.
We will discuss different ways to trade from safest to riskiest as follow:
Safe trading:
Buy - higher trend should be at 100, with both current trend and mid-trend near zero. Middle fill color should be green. Check for divergence and enter buy when current-trend begins to rise with mid-trend or when current trend crosses over mid-trend. Buy example below:
photos.google.com
Sell - higher trend should be at 0, with both current trend and mid-trend near 100. Middle fill color should be red. Check for divergence and enter sell when current-trend begins to descend with mid-trend or when current trend crosses under mid-trend. Sell example below:
photos.google.com
Tip: For the fill color between current trend and mid-trend, the skinnier it is, the stronger the movement; vice versa, the fatter it is, the weaker the move or the higher the chance it reverses. Also, again, check for divergence!
Simple and think free trades:
Buy when the middle bar is green and current trend crosses over mid-trend below 10 and exit when it crosses under or gets to 100.
Sell when the middle bar is red and current-trend crosses under mid-trend above 90 and exit when it crosses over or reaches to 0.
Tip: When you see they cross, check for Divergence before pulling the trigger for added peace of mind (it is one of the main concepts of MACD - Moving Average Convergence Divergence). If you don't know, make sure to research and learn more about it.
Counter Trend Trade:
As much as current-trend and mid-trend love to come back to higher-trend, when they get together, they reject each other.
The only time you can counter-trend is when all three values are at or near 100 or at or near 0 and current trend breaks away. Check for divergence and then enter, exit when it reaches the opposite side. Obviously, this is a lot more risky trade but it is often rewarding. If you chose to go this route, I need to repeat: check for DIVERGENCE with any of the trend value, any divergence would suffice to trade. Counter-trend example below:
photos.google.com
Final tip: always be patient and check for divergence because market often has an imbalance before it reverses.
Final words: This is important to worth mentioning again, especially for beginner people: Use a maximum of 2% of your balance. Don't be greedy and you will blow your account. I use this method without stop loss because there are stop-loss hunter brokers out there. Just be safe. Use this money management system and you will see your account grow very fast. Trade only one trade at a time.
Please consider this indicator as educational purposes. All trades are risky and have the potential to lose all and more than you have in the account. Trade with care.
With that, again, happy holiday and a happy new year 2019. If I do help us trade, please consider to donate to our Paypal account, I would really appreciated: ZonnieAdvertising@gmail.com
Hope 2019 brings you prosperity, wealth and health. Many pips to you and yours!
SD85
