AI-Powered Breakout with Advanced FeaturesDescription
This script is designed to detect breakout moments in financial markets using a combination of traditional breakout detection methods and adaptive moving averages. By leveraging elements of artificial intelligence, the script provides a more dynamic and responsive approach to identifying potential entry and exit points in trading.
Usefulness
This script stands out by integrating a traditional breakout finder with an adaptive moving average component. The adaptive moving average adjusts dynamically based on the differences between fast and slow exponential moving averages (EMAs), offering a more flexible and responsive detection of support and resistance levels. This combination aims to reduce false signals and enhance the reliability of breakout detections, making it a valuable tool for traders seeking to capture market movements more effectively.
Features
1. Breakout Detection: Utilizes pivot highs and lows to identify significant breakout points over a user-defined period. This method helps in capturing the essential support and resistance levels that are critical in breakout trading.
2. AI Machine Learning Component - Adaptive Moving Average: Implements an adaptive moving average using two exponential moving averages (EMAs). adaptiveMA is dynamically adjusted based on the difference between a fast average and a slow average.
3. Buy/Sell Signals: The script generates buy and sell signals when bullish and bearish breakouts occur, respectively. These signals are visually represented on the chart, helping traders to quickly identify potential trading opportunities.
4. Visualization: Draws horizontal lines at identified breakout levels and plots shapes (arrows) on the chart to indicate buy/sell signals. This makes it easy for traders to see where significant breakout points are and where to consider entering or exiting trades.
Underlying Concepts
1. Breakout Finder Logic: The script uses pivot points (highs and lows) to detect breakout levels. It stores these pivot points in arrays and monitors them for persistence, ensuring that the detected breakouts are significant and reliable.
2. Adaptive Moving Average (AMA): The AMA is a key component that enhances the script's responsiveness. By calculating the differences between fast and slow EMAs, the AMA adapts to changing market conditions, providing a more accurate measure of trends and potential reversals.
How to Use
• Adjustable Parameters: The script includes several user-adjustable parameters:
o Lookback Length: Defines the period over which the script calculates the highest high and lowest low for breakout detection.
o Multiplier for Adaptive MA: Adjusts the sensitivity of the adaptive moving average.
o Period for Pivots: Sets the period for detecting pivot highs and lows.
o Max Breakout Length: Specifies the maximum length for breakout consideration.
o Threshold Rate: Determines the threshold rate for breakout validation.
o Minimum Number of Tests: Sets the minimum number of tests required to validate a breakout.
o Colors and Line Style: Customize the colors and line styles for breakout levels.
Interpreting Signals
o Green Arrows: Indicate a bullish breakout signal, suggesting a potential buy opportunity.
o Red Arrows: Indicate a bearish breakout signal, suggesting a potential sell opportunity.
o Horizontal Lines: Show the breakout levels, helping to visualize support and resistance areas.
By combining traditional breakout detection with advanced adaptive moving averages, this script aims to provide traders with a robust tool for identifying and capitalizing on market breakouts.
Credits
Parts of this script were inspired and adapted from the "Breakout Finder" script by LonesomeTheBlue. Significant improvements include the integration of the adaptive moving average component and enhancements to the breakout detection logic.
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GL LineIntroduction
The GL Line Indicator is a versatile tool designed to assist traders in identifying market trends by utilizing three different types of moving averages (EMA, SMA, VWMA) across multiple timeframes. This indicator provides a comprehensive view of market conditions, making it easier to spot potential trading opportunities.
Features
Multiple Moving Average Types:
Choose between Exponential Moving Average (EMA), Simple Moving Average (SMA), and Volume Weighted Moving Average (VWMA) for more tailored analysis.
Triple Timeframe Analysis:
Analyze trends across three different timeframes (Main, Secondary, Tertiary) to get a clearer picture of market direction.
Configurable Parameters:
Customizable lengths for fast and slow-moving averages. Adjustable ATR length and multiplier to refine trend detection sensitivity.
Visual Trend Indication:
Bullish and bearish trends are marked with color-coded lines and fills, enhancing visual clarity.
Confluence Table:
Optional confluence table that shows trend direction across the selected timeframes, aiding in decision-making.
How It Works
Main Trend Calculation:
Select the type of moving average and set the lengths for fast and slow MAs. The difference between these MAs, adjusted by the ATR multiplier, determines the trend direction.
Secondary and Tertiary Trends:
Similar calculations are done for secondary and tertiary timeframes, providing a broader market overview.
Trend Direction and Plotting:
The indicator plots the moving averages and fills the area between them with colors to denote bullish (green) and bearish (red) trends.
How to Use
Select Moving Average Type:
Choose between EMA, SMA, or VWMA based on your trading strategy.
Set Lengths and Multipliers:
Customize the lengths for the fast and slow-moving averages and adjust the ATR length and multiplier for better trend sensitivity.
Analyze Trends:
Use the color-coded plots and fills to identify market trends and make informed trading decisions.
Check Confluence Table:
Optionally display the confluence table to see trend directions across different timeframes.
Disclaimer
This indicator is designed to work best when the secondary and tertiary trends are set to higher timeframes than the chart's timeframe. Using higher timeframes for additional trends provides a broader market perspective and enhances the reliability of trend signals.
GL Gann Swing IndicatorIntroduction
The GL Gann Swing Indicator is a versatile tool designed to help traders identify market trends, support and resistance areas, and potential reversals. This indicator applies the principles of Gann Swing Charts, a technique developed by W.D. Gann, which focuses on market swings to determine the overall direction and turning points of price action. Gann Swing Charts are a time-tested method of technical analysis that simplifies price action by focusing on significant highs and lows, thereby eliminating market noise and providing a clearer view of the trend.
By analyzing price action and determining swing directions and turning points, the indicator filters out market noise using four distinct bar types:
Up Bar: Higher High, Higher Low
Down Bar: Lower High, Lower Low
Inside Bar: Lower High, Higher Low
Outside Bar: Higher High, Lower Low
This approach helps traders to:
Identify the primary trend direction.
Determine key support and resistance levels.
Recognize potential reversal points.
Filter out minor price fluctuations that do not affect the overall trend.
Features
Bar Types: Display bar types by checking the Show Bar Type box in the indicator's settings. Up bars appear as green upward-pointing triangles, down bars as red downward-pointing triangles, inside bars as grey circles, and outside bars as blue diamonds. These visual aids help traders quickly identify the type of bar and its significance.
Break Lines: These lines highlight when the price rises above a previous swing high or falls below a prior swing low. Green lines indicate breaks of swing highs, while red lines indicate breaks of swing lows. Break lines are enabled by default but can be turned off in the indicator's settings. Break lines provide visual confirmation of trend continuation or reversal.
Bar Count: Bar counts help determine if a swing is overextended and if a reversal is likely. This feature is off by default but can be enabled in the indicator's settings. Users can set a minimum bar count to focus on significant swings. Analyzing the number of bars in a swing can help traders gauge the strength and potential exhaustion of a trend.
Swing MA (Moving Averages): This feature plots the average of a user-defined number of previous swing highs and lows. Options are available to add two moving averages, allowing for both fast and slow averages. Swing MAs can be enabled in the indicator's settings. These moving averages smooth out the price data, making it easier to identify the underlying trend direction.
Why This Indicator is Useful
The GL Gann Swing Indicator is particularly useful for several reasons:
Trend Identification: By focusing on significant price swings, the indicator helps traders identify the primary trend direction, making it easier to align trades with the overall market movement.
Noise Reduction: The indicator filters out minor price fluctuations, allowing traders to focus on meaningful market movements and avoid being misled by short-term volatility.
Support and Resistance Levels: By highlighting key swing highs and lows, the indicator helps traders identify crucial support and resistance levels, which are essential for making informed trading decisions.
Potential Reversals: The indicator's ability to identify overextended swings and potential reversal points can help traders anticipate market turning points and adjust their strategies accordingly.
Customizability: With options to display bar types, break lines, bar counts, and swing moving averages, traders can customize the indicator to suit their specific trading style and preferences.
By incorporating Gann Swing principles, the GL Gann Swing Indicator offers traders a powerful tool to enhance their technical analysis, improve their trading decisions, and ultimately achieve better trading outcomes.
US M2### Relevance and Functionality of the "US M2" Indicator
#### Relevance
The "US M2" indicator is relevant for several reasons:
1. **Macro-Economic Insight**: The M2 money supply is a critical indicator of the amount of liquidity in the economy. Changes in M2 can significantly impact financial markets, including equities, commodities, and cryptocurrencies.
2. **Trend Identification**: By analyzing the M2 money supply with moving averages, the indicator helps identify long-term and short-term trends, providing insights into economic conditions and potential market movements.
3. **Trading Signals**: The indicator generates bullish and bearish signals based on moving average crossovers and the difference between current M2 values and their moving averages. These signals can be useful for making informed trading decisions.
#### How It Works
1. **Data Input**:
- **US M2 Money Supply**: The indicator fetches the US M2 money supply data using the "USM2" symbol with a monthly resolution.
2. **Moving Averages**:
- **50-Period SMA**: Calculates the Simple Moving Average (SMA) over 50 periods (months) to capture short-term trends.
- **200-Period SMA**: Calculates the SMA over 200 periods to identify long-term trends.
3. **Difference Calculation**:
- **USM2 Difference**: Computes the difference between the current M2 value and its 50-period SMA to highlight deviations from the short-term trend.
4. **Amplification**:
- **Amplified Difference**: Multiplies the difference by 100 to make the deviations more visible on the chart.
5. **Bullish and Bearish Conditions**:
- **Bullish Condition**: When the current M2 value is above the 50-period SMA, indicating a positive short-term trend.
- **Bearish Condition**: When the current M2 value is below the 50-period SMA, indicating a negative short-term trend.
6. **Short-Term SMA of Amplified Difference**:
- **14-Period SMA**: Applies a 14-period SMA to the amplified difference to smooth out short-term fluctuations and provide a clearer trend signal.
7. **Plots and Visualizations**:
- **USM2 Plot**: Plots the US M2 data for reference.
- **200-Period SMA Plot**: Plots the long-term SMA to show the broader trend.
- **Amplified Difference Histogram**: Plots the amplified difference as a histogram with green bars for bullish conditions and red bars for bearish conditions.
- **SMA of Amplified Difference**: Plots the 14-period SMA of the amplified difference to track the trend of deviations.
8. **Moving Average Cross Signals**:
- **Bullish Cross**: Plots an upward triangle when the 50-period SMA crosses above the 200-period SMA, signaling a potential long-term uptrend.
- **Bearish Cross**: Plots a downward triangle when the 50-period SMA crosses below the 200-period SMA, signaling a potential long-term downtrend.
### Summary
The "US M2" indicator provides a comprehensive view of the US M2 money supply, highlighting significant trends and deviations. By combining short-term and long-term moving averages with amplified difference analysis, it offers valuable insights and trading signals based on macroeconomic liquidity conditions.
Uptrick:Intensity IndexPurpose:
The "Uptrick: Intensity Index" strategy is designed to provide traders with insights into the trend intensity of security by combining multiple moving averages and their relative positions. This versatile tool can be used effectively by both short-term and long-term traders to identify potential buy and sell signals based on specific conditions.
Explanation:
Input Parameters and Customization:
Moving Averages Lengths:
Adjust MA1, MA2, and MA3 lengths to change the calculation periods for the moving averages.
Trend Intensity Index SMA Length:
Adjust the length of the SMA applied to the TII.
Plot Colors:
Change the colors of the TII and TII MA plots for better visualization.
Background Colors and Transparency:
Set different colors for positive and negative TII MA values.
Control the transparency of the background color.
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MA1 (Length 10): Short-term moving average, useful for capturing short-term market trends.
MA2 (Length 20): Medium-term moving average, providing a balanced view of market trends.
MA3 (Length 50): Long-term moving average, offering insights into long-term market trends.
The script calculates the relative positions of the closing price to each moving average (rel1, rel2, rel3) to determine how far the current price deviates from each average.
Trend Intensity Index (TII):
The TII is calculated as the average of the relative positions (rel1, rel2, rel3), multiplied by 100 to convert it into a percentage. This index reflects the overall intensity of the trend, considering short-term, medium-term, and long-term perspectives.
The TII is plotted in blue, providing a visual representation of trend intensity.
SMA of TII:
An additional SMA is applied to the TII (matii) to smooth out fluctuations and provide a clearer long-term trend signal.
The SMA of TII is plotted in orange, offering a reference for long-term trend analysis.
Determining Potential Price Movements:
For Short-Term Traders:
When the blue TII line crosses above the orange SMA of TII line, it indicates a potential buy signal.
When the blue TII line crosses below the orange SMA of TII line, it indicates a potential sell signal.
For Long-Term Traders:
When the orange SMA of TII line crosses above the highlighted 0 line, it indicates a potential buy signal.
When the orange SMA of TII line crosses below the highlighted 0 line, it indicates a potential sell signal.
Plotting and Visualization:
The TII and its SMA are plotted with distinct colors for easy identification.
A horizontal line at 0 is plotted in gray to serve as a reference point for long-term trend signals.
The background color changes based on the value of the SMA of TII (matii):
Green background for matii values above 0, indicating bullish conditions.
Red background for matii values below 0, indicating bearish conditions.
Utility and Potential Usage:
The "Uptrick: Intensity Index" indicator is a powerful tool for both short-term and long-term traders, offering clear buy and sell signals based on the crossover of the TII and its SMA, as well as the position of the SMA relative to the zero line.
By consolidating multiple moving averages and their relative positions into a single indicator, traders can gain comprehensive insights into market trends and intensity.
The ability to adjust all inputs and toggle visibility options enhances the flexibility and utility of the indicator, making it suitable for various trading styles and market conditions.
Through its versatile design and advanced features, the "Uptrick: Intensity Index" indicator equips traders with actionable insights into trend intensity and potential price movements. By integrating this robust tool into their trading strategies, traders can navigate the markets with greater precision and confidence, thereby enhancing their trading outcomes.
WHAT SETTINGS TO HAVE FOR THE MOVING AVERAGE:
Short-term traders (day traders) might prefer a shorter SMA length (e.g., 5-20 periods) as they are looking for quick signals and react to price changes more rapidly.
Medium-term traders (swing traders) might opt for a medium SMA length (e.g., 20-50 periods) which can filter out some noise and provide a clearer signal on the trend.
Long-term traders (position traders) might choose a longer SMA length (e.g., 50-200 periods) to get a broader view of the market trend and avoid reacting to short-term fluctuations.
Hull AMA SignalsThis script is a comprehensive trading indicator named "Hull AMA Signals", which combines AMA and HSO by LuxAlgo and ther video based strategy techniques to provide buy (long) and sell (short) signals. It overlays directly on the price chart, offering a dynamic and visually intuitive trading aid. The core components of this indicator are Adaptive Moving Averages (AMA), Hull Moving Average (HMA), and a unique Hull squeeze oscillator (HSO), each configured with customizable parameters for flexibility and adaptability to various market conditions.
Features and Components
Adaptive Moving Averages (AMA): This indicator employs two sets of AMAs, each with distinct lengths, multipliers, lags, and overshoot parameters. The AMAs are designed to adapt their sensitivity based on the market's volatility, making them more responsive during significant price movements and less prone to false signals during periods of consolidation.
Hull Moving Average (HMA): The HMA is calculated using a sophisticated algorithm that aims to reduce the lag commonly associated with traditional moving averages. It provides a smoother and more responsive moving average line, which helps in identifying the prevailing market trend more accurately.
Hull Squeeze Oscillator (HSO): A novel component of this indicator, the HSO, is designed to identify potential market breakouts. It does so by comparing the Hull Moving Average's direction and momentum against a dynamically calculated mean, generating bullish or bearish signals based on the crossover and divergence from this mean.
Buy (Long) and Sell (Short) Signals: The script intelligently combines signals from the AMA crossovers and the Hull squeeze oscillator to pinpoint potential buy and sell opportunities. Bullish signals are generated when there's a positive crossover in the AMAs accompanied by a bullish dot from the HSO, whereas bearish signals are indicated by a negative crossover in the AMAs along with a bearish dot from the HSO.
Customization and Style Options: Users have the ability to adjust various parameters such as the length of the moving averages, multipliers, and source data, enabling customization for different trading strategies and asset classes. Additionally, color-coded visual elements like gradients and shapes enhance the readability and instant recognition of trading signals.
Use Cases
Trend Identification: By analyzing the direction and position of the AMAs and HMA, traders can easily discern the prevailing market trend, helping them to align their trades with the market momentum.
Signal Confirmation: The combination of AMA crossovers and HSO signals provides a robust framework for confirming trade entries and exits, potentially increasing the reliability of the trading signals.
Volatility Adaptation: The adaptive nature of the AMAs and the dynamic calculation of the HSO mean allow this indicator to adjust to changing market volatility, making it suitable for a wide range of market environments.
This indicator is suitable for traders looking for a comprehensive and dynamic technical analysis tool that combines trend analysis with signal generation, offering both visual appeal and practical trading utility.
Trend FinderThe "𝙏𝙍𝙀𝙉𝘿 𝙁𝙄𝙉𝘿𝙀𝙍" indicator is a powerful tool designed to detect trends and identify potential reversal points in asset prices. It operates as both a trend-following and mean reversion indicator, offering insights into market movements.
Trend Identification:
Trend Detection:
This indicator primarily identifies trends in asset prices.
When the "𝙏𝙍𝙀𝙉𝘿 𝙁𝙄𝙉𝘿𝙀𝙍" value is above the middle line, it typically indicates an upward trend in the asset's price.
Color Coding: During an upward trend, the bars are colored green, signaling strength in the upward movement. Conversely, during a downtrend, the bars turn red, indicating a potential downward movement in the asset's price.
Calculation Process:
Moving Averages: The calculation involves using multiple Simple Moving Averages (SMAs) based on the open and close prices of the asset.
Incremental SMA Lengths: These SMAs are calculated with increasing lengths, creating a series of comparisons between closing and opening SMAs. If the closing SMA exceeds the opening SMA, a value of 1 is assigned; otherwise, it's assigned as 0.
Aggregation: All these SMA values are compiled into an array and processed to derive an average, emphasizing the trend direction and strength.
Application:
Trend Strength: The indicator's value reflects the overall strength and direction of the trend. Higher values suggest an end or reversing of trend, while lower values what crosses over or under Midline may indicate a trend changing and indicate incrising of trend strength.
Reversal Indication: Besides identifying trends, it can also serve as a mean reversion indicator, potentially pinpointing potential tops and bottoms in the market.
Midline: Additional in settings can be changed a position of midline to up or down to your personal preference.
The "𝙏𝙍𝙀𝙉𝘿 𝙁𝙄𝙉𝘿𝙀𝙍" indicator amalgamates moving averages and trend analysis, offering a comprehensive view of market trends and potential reversal points. Its adaptability through parameter adjustments allows for fine-tuning to suit various market conditions.
Webby's Quick & Grateful Dead RSWebby's Quick & Grateful Dead RS combines a Relative Strength Line and Moving Averages to help traders hold a core position in a winning stock by identifying moments of strength and weakness in a stocks advance.
The Relative Strength (RS) line is something many investors are familiar with. It is used to measure a stocks performance versus the S&P 500 (default setting) and is typically calculated by dividing the closing price of the stock by the closing price of the S&P. This means if a stock moves up and the S&P moves down or the stock moves up more than the S&P the RS line will increase, if the stock moves down while the S&P moves up the line will decrease.
While the RS Line by itself is a powerful tool, adding moving averages to the RS line can help better understand trends. This work was done by Mike Webster (Webby) as he tried to reverse engineer how William O'Neil was able to hold some of his biggest winning positions.
This indicator plots the RS line along with two moving averages and clearly labels and alerts the 3 signals shared by Webby:
Quick Break - RS line crosses below the fast moving average
Quicksand - RS line moves lower than it was at the time of the Quick Break
Grateful Dead Break - RS line crosses below the slow moving average
To ensure your chart doesn't get skewed, please use the multiplier in the setting to adjust the vertical offset of the RS line and moving averages.
Purchasing Managers Index (PMI)The Purchasing Managers Index (PMI) is a widely recognized economic indicator that provides crucial insights into the health and performance of an economy's manufacturing and services sectors. This index is a vital tool for anticipating economic developments and trends, offering an early warning system for changes in these sectors.
The PMI is calculated based on surveys conducted among purchasing managers in various businesses and organizations. These managers are asked about their perceptions of current business conditions and their expectations for future economic activity within their sectors. The responses are then compiled and used to calculate the PMI value.
A PMI value above 50 typically indicates that the manufacturing or services sector is expanding, suggesting a positive economic outlook. Conversely, a PMI value below 50 suggests contraction, which may be an early indication of economic challenges or a potential recession.
In summary, the Purchasing Managers Index (PMI) is an essential economic indicator that assesses the health of manufacturing and services sectors by surveying purchasing managers' opinions. It serves as an early warning system for changes in economic activity and is a valuable tool for forecasting economic trends and potential crises.
This code combines the Purchasing Managers Index (PMI) data with two Simple Moving Averages (SMA) and some visual elements.
Let's break down how this indicator works:
1. Loading PMI Data:
The indicator loads data for the "USBCOI" symbol, which represents the PMI data. It fetches the monthly closing prices of this symbol.
2. Calculating Moving Averages:
Two Simple Moving Averages (SMAs) are calculated based on the PMI data. The first SMA, sma_usbcoi, has a length defined by the input parameter (default: 2). The second SMA, sma2_usbcoi, has a different length defined by the second input parameter (default: 14).
3. Color Coding and Thresholds:
The line color of the PMI plot is determined based on the value of the PMI. If the PMI is above 52, the color is teal; if it's below 48, the color is red; otherwise, it's gray. These threshold values are often used to identify specific conditions in the PMI data.
4. Crossing Indicator:
A key feature of this indicator is to determine if the PMI crosses the first SMA (sma_usbcoi) from top to bottom while also being above the value of 52. This is indicated by the crossedUp variable. This condition suggests a specific situation where the PMI crosses a short-term moving average while indicating strength (above 52).
5. Visual Elements:
A "💀" skull emoji is defined as skullEmoji.
The PMI is plotted on the chart with color coding based on its value, as described earlier.
The two SMAs are also plotted on the chart.
When the crossedUp condition is met (PMI crosses the first SMA from top to bottom while above 52), a skull emoji (indicating potential danger) is plotted at the top of the indicator window.
RelativeVolatilityIndicator with Trend FilterGuide to the Relative Volatility Indicator with Trend Filter (RVI_TF)
Introduction
The Relative Volatility Indicator with Trend Filter (RVI_TF) aims to provide traders with a comprehensive tool to analyze market volatility and trend direction. This unique indicator combines volatility ratio calculations with a trend filter to help you make more informed trading decisions.
Key Components
Scaled Volatility Ratio: This measures the current market volatility relative to historical volatility and scales the values for better visualization.
Fast and Slow Moving Averages for Volatility: These provide a smoothed representation of the scaled volatility ratio, making it easier to spot trends in market volatility.
Trend Filter: An additional line representing a long-term Simple Moving Average (SMA) to help you identify the prevailing market trend.
User Inputs
Short and Long ATR Period: These allow you to define the length for calculating the Average True Range (ATR), used in the volatility ratio.
Short and Long StdDev Period: Periods for short-term and long-term standard deviation calculations.
Min and Max Volatility Ratio for Scaling: Scale the volatility ratio between these min and max values.
Fast and Slow SMA Period for Volatility Ratio: Periods for the fast and slow Simple Moving Averages of the scaled volatility ratio.
Trend Filter Period: Period for the long-term SMA, used in the trend filter.
Show Trend Filter: Toggle to show/hide the trend filter line.
Trend Filter Opacity: Adjust the opacity of the trend filter line.
Visual Components
Histogram: The scaled volatility ratio is displayed as a histogram. It changes color based on the ratio value.
Fast and Slow Moving Averages: These are plotted over the histogram for additional context.
Trend Filter Line: Shown when the corresponding toggle is enabled, this line gives an indication of the general market trend.
How to Use
Volatility Analysis: Look for divergences between the fast and slow MAs of the scaled volatility ratio. It can signal potential reversals or continuation of trends.
Trend Confirmation: Use the Trend Filter line to confirm the direction of the current trend.
Conclusion
The RVI_TF is a multi-faceted indicator designed for traders who seek to integrate both volatility and trend analysis into their trading strategies. By providing a clearer understanding of market conditions, this indicator can be a valuable asset in a trader's toolkit.
Traders Trend DashboardThe Traders Trend Dashboard (TTD) is a comprehensive trend analysis tool designed to assist traders in making informed trading decisions across various markets and timeframes. Unlike conventional trend-following scripts, TTD goes beyond simple trend detection by incorporating a unique combination of moving averages and a visual dashboard, providing traders with a clear and actionable overview of market trends. Here's how TTD stands out from the crowd:
Originality and Uniqueness:
TTD doesn't rely on just one moving average crossover to detect trends. Instead, it employs a dynamic approach by comparing two moving averages of distinct periods across multiple timeframes. This innovative methodology enhances trend detection accuracy and reduces false signals commonly associated with single moving average systems.
Market Applicability:
TTD is versatile and adaptable to various financial markets, including forex, stocks, cryptocurrencies, and commodities. Its flexibility ensures that traders can utilize it across different asset classes and capitalize on market opportunities.
Optimal Timeframe Utilization:
Unlike many trend indicators that work best on specific timeframes, TTD caters to traders with diverse trading preferences. It offers support for intraday trading (1m, 3m, 5m), short-term trading (15m, 30m, 1h), and swing trading (4h, D, W, M), making it suitable for a wide range of trading styles.
Underlying Conditions and Interpretation:
TTD is particularly effective during trending markets, where its multi-timeframe approach helps identify consistent trends across various time horizons. In ranging markets, TTD can indicate potential reversals or areas of uncertainty when moving averages converge or cross frequently.
How to Use TTD:
1. Timeframe Selection: Choose the relevant timeframes based on your trading style and preferences. Enable or disable timeframes in the settings to focus on the most relevant ones for your strategy.
2. Dashboard Interpretation: The TTD dashboard displays green (🟢) and red (🔴) symbols to indicate the relationship between two moving averages. A green symbol suggests that the shorter moving average is above the longer one, indicating a potential bullish trend. A red symbol suggests the opposite, indicating a potential bearish trend.
3. Confirmation and Strategy: Consider TTD signals as confirmation for your trading strategy. For instance, in an uptrend, look for long opportunities when the dashboard displays consistent green symbols. Conversely, in a downtrend, focus on short opportunities when red symbols dominate.
4. Risk Management: As with any indicator, use TTD in conjunction with proper risk management techniques. Avoid trading solely based on indicator signals; instead, integrate them into a comprehensive trading plan.
Conclusion:
The Traders Trend Dashboard (TTD) offers traders a powerful edge in trend analysis, combining innovation, versatility, and clarity. By understanding its unique methodology and integrating its signals with your trading strategy, you can make more informed trading decisions across various markets and timeframes. Elevate your trading with TTD and unlock a new level of trend analysis precision.
6 EMA/SMA/RMA + Forecasting 10 candles 6EMA/SMA/RMA + Forecasting 10 candles
The script allows the user to choose between different types of moving averages (SMA, EMA, RMA) using the soft_func_choice input.
The user can also choose between two types of forecasting: "Repetition" or "Linear Regression" using the type_of_forecast input.
For the linear regression forecast, the user can specify the number of candles to use in the linear regression calculation using the Linreglen input.
First Moving Average (MA) Calculation:
The script calculates the first MA based on the selected type (SMA, EMA, RMA) and plots it on the chart.
The user can customize the length and source of data for this MA.
If the selected forecast type is "Repetition," the script also calculates additional offset values for different repetitions of the MA.
Forecasting and Offset Calculation:
Depending on the chosen forecast type, the script calculates additional offset values for the MA. These offsets are used to forecast the future values of the MA.
The script calculates offsets for up to five repetitions (offset1, offset2, ..., offset5) for each MA.
If the forecast type is "Linear Regression," the script combines the MA's historical values with linear regression predictions to generate the forecasted values.
Plotting Additional Moving Averages:
The script allows the user to plot up to four additional MAs (Second MA, Third MA, Fourth MA, Fifth MA) with similar customizable settings for length and source of data.
Forecast Repetition:
If the forecast type is "Repetition," the script iterates through historical data and accumulates offset values, effectively simulating a repeated forecasting approach.
This repetition is controlled by a loop that adjusts the offset values based on historical price data.
Overall, this script provides a versatile tool for analyzing and forecasting multiple moving averages using various methods, allowing traders and analysts to experiment with different MA types and forecast strategies on their chosen price series.
MultiMovesCombines 3 different moving averages together with the linear regression. The moving averages are the HMA, EMA, and SMA. The script makes use of two different lengths to allow the end user to utilize common crossovers in order to determine entry into a trade. The edge of each "cloud" is where each of the moving averages actually are. The bar color is the average of the shorter length combined moving averages.
-The Hull Moving Average (HMA), developed by Alan Hull, is an extremely fast and smooth moving average. In fact, the HMA almost eliminates lag altogether and manages to improve smoothing at the same time. A longer period HMA may be used to identify trend.
-The exponential moving average (EMA) is a technical chart indicator that tracks the price of an investment (like a stock or commodity) over time. The EMA is a type of weighted moving average (WMA) that gives more weighting or importance to recent price data.
-A simple moving average (SMA) is an arithmetic moving average calculated by adding recent prices and then dividing that figure by the number of time periods in the calculation average.
-The Linear Regression Indicator plots the ending value of a Linear Regression Line for a specified number of bars; showing, statistically, where the price is expected to be. Instead of plotting an average of past price action, it is plotting where a Linear Regression Line would expect the price to be, making the Linear Regression Indicator more responsive than a moving average.
The lighter colors = default 50 MA
The darker colors = default 200 MA
peacefulIndicatorsWe are delighted to present the PeacefulIndicators library, a modest yet powerful collection of custom technical indicators created to enhance your trading analysis. The library features an array of practical tools, including MACD with Dynamic Length, Stochastic RSI with ATR Stop Loss, Bollinger Bands with RSI Divergence, and more.
The PeacefulIndicators library offers the following functions:
macdDynamicLength: An adaptive version of the classic MACD indicator, which adjusts the lengths of the moving averages based on the dominant cycle period, providing a more responsive signal.
rsiDivergence: A unique implementation of RSI Divergence detection that identifies potential bullish and bearish divergences using a combination of RSI and linear regression.
trendReversalDetection: A helpful tool for detecting trend reversals using the Rate of Change (ROC) and Moving Averages, offering valuable insights into possible market shifts.
volume_flow_oscillator: A custom oscillator that combines price movement strength and volume to provide a unique perspective on market dynamics.
weighted_volatility_oscillator: Another custom oscillator that factors in price volatility and volume to deliver a comprehensive view of market fluctuations.
rvo: The Relative Volume Oscillator highlights changes in volume relative to historical averages, helping to identify potential breakouts or reversals.
acb: The Adaptive Channel Breakout indicator combines a moving average with an adjustable volatility multiplier to create dynamic channels, useful for identifying potential trend shifts.
We hope this library proves to be a valuable addition to your trading toolbox.
Library "peacefulIndicators"
A custom library of technical indicators for trading analysis, including MACD with Dynamic Length, Stochastic RSI with ATR Stop Loss, Bollinger Bands with RSI Divergence, and more.
macdDynamicLength(src, shortLen, longLen, signalLen, dynLow, dynHigh)
Moving Average Convergence Divergence with Dynamic Length
Parameters:
src (float) : Series to use
shortLen (int) : Shorter moving average length
longLen (int) : Longer moving average length
signalLen (int) : Signal line length
dynLow (int) : Lower bound for the dynamic length
dynHigh (int) : Upper bound for the dynamic length
Returns: tuple of MACD line and Signal line
Computes MACD using lengths adapted based on the dominant cycle period
rsiDivergence(src, rsiLen, divThreshold, linRegLength)
RSI Divergence Detection
Parameters:
src (float) : Series to use
rsiLen (simple int) : Length for RSI calculation
divThreshold (float) : Divergence threshold for RSI
linRegLength (int) : Length for linear regression calculation
Returns: tuple of RSI Divergence (positive, negative)
Computes RSI Divergence detection that identifies bullish (positive) and bearish (negative) divergences
trendReversalDetection(src, rocLength, maLength, maType)
Trend Reversal Detection (TRD)
Parameters:
src (float) : Series to use
rocLength (int) : Length for Rate of Change calculation
maLength (int) : Length for Moving Average calculation
maType (string) : Type of Moving Average to use (default: "sma")
Returns: A tuple containing trend reversal direction and the reversal point
Detects trend reversals using the Rate of Change (ROC) and Moving Averages.
volume_flow_oscillator(src, length)
Volume Flow Oscillator
Parameters:
src (float) : Series to use
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on price movement strength and volume
weighted_volatility_oscillator(src, length)
Weighted Volatility Oscillator
Parameters:
src (float) : Series to use
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on price volatility and volume
rvo(length)
Relative Volume Oscillator
Parameters:
length (int) : Period for the calculation
Returns: Custom Oscillator value
Computes the custom oscillator based on relative volume
acb(price_series, ma_length, vol_length, multiplier)
Adaptive Channel Breakout
Parameters:
price_series (float) : Price series to use
ma_length (int) : Period for the moving average calculation
vol_length (int) : Period for the volatility calculation
multiplier (float) : Multiplier for the volatility
Returns: Tuple containing the ACB upper and lower values and the trend direction (1 for uptrend, -1 for downtrend)
Multiple Moving Average ToolkitFeatures Overview:
Multiple Moving Averages: The script allows you to plot up to five different Moving Averages (MAs) on your chart at the same time. You can choose the type of MA (EMA, SMA, HMA, WMA, DEMA, VWMA, VWAP) and the length of each one.
Color Ribbon: You can turn the MAs into a color ribbon by selecting the "Turn into Color Ribbon?" option. This will make the area between the MAs colored and can help you identify trends more easily.
MA Value Table: You can draw a table on your chart that displays the current values of each MA, whether the trend is bullish or bearish along with the length of the MAs. The current ATR value is also shown in the last cell of the table. You can choose the location of the table (Top Left, Top Right, Bottom Left, Bottom Right) and the transparency of the background color.
Crosses: The script can detect when two MAs cross over each other (1st MA crosses 5th MA and vice versa), indicating a potential trend reversal. It will plot crosses on the chart at the point of the crossover and give an alert if the "Bullish Cross Detected" or "Bearish Cross Detected" condition is met.
How to use:
Once the script is added to your chart, you can customize the settings to fit your preferences. You can choose the type and length of each MA, whether to turn them into a color ribbon, whether to plot crosses, and whether to draw the MA Value Table.
The MA Value Table can be moved to a different location on the chart by selecting the "Location of Table" option and choosing Top Left, Top Right, Bottom Left, or Bottom Right.
Watch for MA crossovers and alerts to identify potential trend reversals. The script can help you identify bullish and bearish trends by color-coding the area between the MAs and displaying the current values of each MA in the table.
Breakdown of the script:
User Inputs
The first section of the script defines several user inputs that allows you to customize the indicator. These include options for turning the MAs into a color ribbon, plotting crosses when there is a bullish or bearish cross of the MAs, drawing a table of the MA values, and setting the transparency of the ribbon. You can also select the location of the MA value table and customize the settings for each individual MA.
Moving Average Calculation
The script defines a function called "getMA" that calculates the moving average for a given type and length. The function uses a switch statement to determine which type of moving average to use, such as an exponential moving average (EMA), simple moving average (SMA), Hull moving average (HMA), weighted moving average (WMA), double exponential moving average (DEMA), volume-weighted moving average (VWMA), or volume-weighted average price (VWAP).
The script then calls this function to calculate the values of up to five different MAs, depending on the user input. The ATR (average true range) is also calculated using the TA library.
Color Filter and Cross Detection
The script sets a color filter based on the relationship between the MAs. If the shorter-term MAs are above the longer-term MAs, the filter is set to green to indicate a bullish trend, and if the shorter-term MAs are below the longer-term MAs, the filter is set to red to indicate a bearish trend. You can adjust the transparency of the ribbon to make it more or less visible.
The script also detects when there is a bullish or bearish cross of the MAs and can generate alerts to notify you.
MA Plotting
The script plots up to five MAs on the chart, depending on the user input. The MAs are plotted as lines with different colors and thicknesses, and you can choose to turn them into a color ribbon if desired.
Cross Plotting
The script plots crosses on the chart when there is a bullish or bearish cross of the MAs. The crosses are plotted as X shapes at the location of the cross and are color-coded to indicate the direction of the cross.
MA Value Table
Finally, the script draws a table of the MA values on the chart, displaying the values of each MA as well as the current trend and the ATR. You can customize the location of the table, and the table is colored to match the color filter of the MAs.
Feel free to message me or comment on the post with any questions or issues!
Much more to come!
Thanks for reading, enjoy!
Stochastic MACD - Slow and FastStochastic MACD - Slow and Fast
The "Stochastic MACD - Slow and Fast" indicator combines two popular technical indicators, the Stochastic Oscillator and the Moving Average Convergence Divergence ( MACD ).
The Stochastic Oscillator is a momentum indicator that measures the current closing position of an asset relative to its recent price range. This indicator helps traders identify possible turning points in an asset's trend, it is used to identify if the market is overbought or oversold.
On the other hand, the MACD is an indicator used to identify the trend and strength of the market and shows the difference between two exponential moving averages ( EMA ) of different periods. The MACD is commonly used to determine the direction of an asset's price trend.
The combination of both indicators can help traders identify market entry and exit opportunities. This indicator has two parts: a slow part and a fast part. The slow part uses input values for the lengths of the moving averages and the length of the signal for the MACD indicator. The fast part uses different input values for the lengths of the moving averages. Also, each part has its own set of line colors and histogram colors for easy visualization.
In general, the "Stochastic MACD - Slow and Fast" indicator is used to identify possible turning points in the trend of an asset. Traders can use the indicator to determine when to enter or exit a position based on the signals generated by the indicator. The stochastic MACD is a variation of the regular MACD that incorporates a stochastic oscillator to provide additional signals.
In summary, this indicator can be useful for those looking for a combination of two popular indicators to help identify trading opportunities.
In addition, parameters were defined to activate or deactivate the graphic signal.
When the Stochastic MACD Slow Line Crosses the Stochastic MACD Slow Signal Line:
Long or Buy = ↑ // The Entry is more Effective if it is made when the signal is below the Zero Trend Line .
Short or Sell = ↓ // The Entry is more Effective if it is made when the signal is above the Zero Trend Line .
When the Fast Stochastic MACD Line Crosses the Slow Stochastic MACD Line:
Long or Buy = ▲ // The Entry is more Effective if it is made when the signal is below the Zero Trend Line .
Short or Sell = ▼ // The Entry is more Effective if it is made when the signal is above the Zero Trend Line .
Taking into account the above, alerts were also defined for possible Purchases or Sales or entries in Long or Short.
COPOSITION AND USE OF THE INDICATOR
This script is an implementation of the Stochastic MACD indicator with two variations - Slow and Fast. It uses a combination of the Stochastic Oscillator and the Moving Average Convergence Divergence (MACD) indicator to identify trend reversals and momentum shifts in the price of an asset.
The Slow version of the Stochastic MACD is built using three inputs - fastLength, slowLength, and signalLength. The fastLength and slowLength are used to calculate two exponential moving averages (EMAs), while the signalLength is used to calculate a signal line as an EMA of the difference between the two EMAs. The Stochastic Oscillator is then applied to the difference between the two EMAs, and the resulting values are plotted on the chart.
The Fast version of the Stochastic MACD is built using the same inputs as the Slow version, but with different values. It uses a shorter fastLength value and a longer slowLength value to generate the two EMAs, and the resulting values are plotted on the chart.
The script also includes inputs for choosing the type of moving average to use (SMA, EMA, etc.), the source of price data (open, close, etc.), the lookback period, and the colors for the lines and histogram bars.
This script can be used in different markets such as forex, indices, and cryptocurrencies for analysis and trading. However, it is important to note that no trading strategy is guaranteed to be profitable, and traders should always conduct their own research and risk management.
Historical AverageHistorical Average is a script written in the Pine Script language and is used to calculate various types of moving averages. Moving averages are statistical measures that smooth out data over time, making it easier to identify trends and patterns. This script allows the user to select from several different types of moving averages, including Simple Moving Average (SMA), Linear Weighted Moving Average (LWMA), Exponential Moving Average (EMA), Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), and Quadruple Exponential Moving Average (QEMA). The script also allows the user to specify a data source for the moving averages to be calculated from.
To use this script, the user simply needs to specify the data source and select the desired moving average type from the list. The script will then calculate and plot the selected moving average on the chart. This can be useful for traders and investors who want to gain a better understanding of the trends and patterns in the data they are analyzing.
Qullamaggie Daily with ADR% and Compression RangeQullamaggie Daily
This Indicator is a Combination of Moving Averages (Simple and Exponential) as definied from Qullamaggie and used in his TC2000 Setup
Moving Averages:
- The Moving Averages are Guidelines for the current Trend and are not decive for the Entry
- They shall be a quick view and visual assistance to find strong momentum stock that are currently in a Phase of a "Flag Pattern"
ADR% 20 Day:
- Average Daily Range in % should indicate the Momentum of the Stock. It is similar but still works different as the Volalitily indicators.
- A stock is recommend to a have a ADR% above 5-6 to be considered a Momentum Leading Stock.
Consolidation Range:
- This Indicator should help to define Ranges in which the Volumen get compressed(increase) while the price movement is minimal
- A strong breakout is to be expected. The Range should be easier to be identified with this indication.
Adaptive Oscillator constructor [lastguru]Adaptive Oscillators use the same principle as Adaptive Moving Averages. This is an experiment to separate length generation from oscillators, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. Note that all Oscillators here are normalized to -1..1 range. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource , so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Oscillators.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers , but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers . I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power ( exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Oscillators section offer you a choice of Oscillator algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
CMO - Chande Momentum Oscillator
RSI - Relative Strength Index
Volume-scaled RSI - my own version of RSI. It scales price movements by the proportion of RMS of volume
Momentum RSI - RSI of price momentum
Rocket RSI - inspired by RocketRSI by John F. Ehlers (not an exact implementation)
MFI - Money Flow Index
LRSI - Laguerre RSI by John F. Ehlers
LRSI with Fractal Energy - a combo oscillator that uses Fractal Energy to tune LRSI gamma
Fractal Energy - Fractal Energy or Choppiness Index by E. W. Dreiss
Efficiency ratio - based on Kaufman Adaptive Moving Average calculation
DMI - Directional Movement Index (only ADX is drawn)
Fast DMI - same as DMI, but without secondary smoothing
If no Adaptation is selected (None option), you can set Length directly. If an Adaptation is selected, then Cycle multiplier can be set.
Before an Oscillator, a High Pass filter may be executed to remove cyclic components longer than the provided Highpass Length (no High Pass filter, if Highpass Length = 0). Both before and after the Oscillator a Moving Average can be applied. The following Moving Averages are included: SMA, RMA, EMA, HMA , VWMA, 2-pole Super Smoother, 3-pole Super Smoother, Filt11, Triangle Window, Hamming Window, Hann Window, Lowpass, DSSS. For more details on these Moving Averages, you can check my other Adaptive Constructor indicator:
The Oscillator output may be renormalized and postprocessed with the following Normalization algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
Inverse Fisher Transform - Inverse Fisher Transform
Noise Elimination Technology - a simplified Kendall correlation algorithm "Noise Elimination Technology" by John F. Ehlers
Except for Inverse Fisher Transform, all Normalization algorithms can have Length parameter. If it is not specified (set to 0), then the calculated Oscillator length is used.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Adaptive MA constructor [lastguru]Adaptive Moving Averages are nothing new, however most of them use EMA as their MA of choice once the preferred smoothing length is determined. I have decided to make an experiment and separate length generation from smoothing, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource, so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Moving Averages.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers, but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers. I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power (exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Length Adaptaton section offer you a choice of Moving Average algorithms. Most of the Adaptations are originally used with EMA, so this is a good starting point for exploration.
SMA - Simple Moving Average
RMA - Running Moving Average
EMA - Exponential Moving Average
HMA - Hull Moving Average
VWMA - Volume Weighted Moving Average
2-pole Super Smoother - 2-pole Super Smoother by John F. Ehlers
3-pole Super Smoother - 3-pole Super Smoother by John F. Ehlers
Filt11 -a variant of 2-pole Super Smoother with error averaging for zero-lag response by John F. Ehlers
Triangle Window - Triangle Window Filter by John F. Ehlers
Hamming Window - Hamming Window Filter by John F. Ehlers
Hann Window - Hann Window Filter by John F. Ehlers
Lowpass - removes cyclic components shorter than length (Price - Highpass)
DSSS - Derivation Scaled Super Smoother by John F. Ehlers
There are two Moving Averages that are drown on the chart, so length for both needs to be selected. If no Adaptation is selected ( None option), you can set Fast Length and Slow Length directly. If an Adaptation is selected, then Cycle multiplier can be selected for Fast and Slow MA.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Configurable Multi MA Crossover Voting SystemThis strategy goes long when all fast moving averages that you have defined are above their counterpart slow moving averages.
Long position is closed when profit or loss target is hit and at least one of the fast moving averages is below its counterpart slow moving average.
The format of the config is simple. The format is : FASTxSLOW,FASTxSLOW,...
Example : If you want 2 moving averages fast=9,slow=14 and fast=20,slow=50 you define it like this : 9x14,20x50
Another example : 5x10,10x15,15x20 => means 3 moving average setups : first wih fast=5/slow=10, second with fast=10/slow=15, last with fast=15/slow=20
You can chose the type of moving average : SMA, WMA, VWMA (i got issues with EMA/RMA so i removed them)
You can chose the source of the moving average : high, close, hl2 etc.
You can chose the period on which ATR is calculated and ATR profit/loss factors.
Profit is calculated like : buy_price + atr_factor*atr
Loss is calculated like : buy_price - atr_factor*atr
Performance in backtest is variable depending on the timeframe, the options and the market.
Performance in backtest suggests it works better for higher timeframes like 1d, 4h etc.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Moving Average MultitoolI made this script as a personal tool while backtesting multiple moving averages. It allows you to easily access and switch between different types of moving averages, without having to continuously add and remove different moving averages from your chart.
It also has the option to show the a 14 period average distance between the closing price of an asset and the selected moving average, as a multiple of ATR. This number can be shown by enabling the "Show ATR Between MA and Close" setting. The intention of this value is to quantify and compare the speed of different moving averages across any instrument and any timeframe. The higher the value, the slower the moving average. The lower the value, the faster the moving average.
trend_vol_stopThe description below is copied from the script's comments. Because TradingView does not allow me to edit this description, please refer to the script's comments section, as well as the release notes, for the most up-to-date information.
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Usage:
The inputs define the trend and the volatility stop.
Trend:
The trend is defined by a moving average crossover. When the short
(or fast) moving average is above the long (slow) moving average, the
trend is up. Otherwise, the trend is down. The inputs are:
long: the number of periods in the long/slow moving average.
short: the number of periods in the short/fast moving average.
The slow moving average is shown in various colors (see explanation
below. The fast moving average is a faint blue.
Volatility stop:
The volatility stop has two modes, percentage and rank. The percentage
stop is given in terms of annualized volatility. The rank stop is given
in terms of percentile.
stop_pct and stop_rank are initialized with "-1". You need to set one of
these to the values you want after adding the indicator to your chart.
This is the only setting that requires your input.
mode: choose "rank" for a rank stop, "percentage" for a percentage stop.
vol_window: the number of periods in the historical volatility
calculation. e.g. "30" means the volatility will be a weighted
average of the previous 30 periods. applies to both types of stop.
stop_pct: the volatility limit, annualized. for example, "50" means
that the trend will not be followed when historical volatility rises
above 50%.
stop_rank: the trend will not be followed when the volatility is in the
N-th percentile. for example, "75" means the trend will not be
followed when the current historical volatility is greater than 75%
of previous volatilities.
rank_window: the number of periods in the rank percentile calculation.
for example, if rank_window is "252" and "stop_rank" is "80", the
trend will not be followed when current historical volatility is
greater than 80% of the previous 252 historical volatilities.
Outputs:
The outputs include moving averages, to visually identify the trend,
a volatility table, and a performance table.
Moving averages:
The slow moving average is colored green in an uptrend, red in a
downtrend, and black when the volatility stop is in place.
Volatility table:
The volatility table gives the current historical volatility, annualized
and expressed as a whole number percentage. E.g. "65" means the
instrument's one standard deviation annual move is 65% of its price.
The current rank is expressed, also as a whole number percentage. E.g.
"15" means the current volatility is greater than 15% of previous
volatilities. For convenience, the volatilities corresponding to the
0, 25, 50, 75, and 100th percentiles are also shown.
Performance table:
The performance table shows the current strategy's performance versus
buy-and-hold. If the trend is up, the instrument's return for that
period is added to the strategy's return, because the strategy is long.
If the trend is down, the negative return is added, because the strategy
is short. If the volatility stop is in (the slow moving average is
black), that period's return is excluded from the strategy returns.
Every period's return is added to the buy-and-hold returns.
The table shows the average return, the standard deviation of returns,
and the sharpe ratio (average return / standard deviation of returns).
All figures are expressed as per-period, whole number percentages.
For exmaple, "0.1" in the mean column on a daily chart means a
0.1% daily return.
The number of periods (samples) for each strategy is also shown.
