Machine Learning Adaptive SuperTrend [AlgoAlpha]📈🤖 Machine Learning Adaptive SuperTrend - Take Your Trading to the Next Level! 🚀✨
Introducing the Machine Learning Adaptive SuperTrend , an advanced trading indicator designed to adapt to market volatility dynamically using machine learning techniques. This indicator employs k-means clustering to categorize market volatility into high, medium, and low levels, enhancing the traditional SuperTrend strategy. Perfect for traders who want an edge in identifying trend shifts and market conditions.
What is K-Means Clustering and How It Works
K-means clustering is a machine learning algorithm that partitions data into distinct groups based on similarity. In this indicator, the algorithm analyzes ATR (Average True Range) values to classify volatility into three clusters: high, medium, and low. The algorithm iterates to optimize the centroids of these clusters, ensuring accurate volatility classification.
Key Features
🎨 Customizable Appearance: Adjust colors for bullish and bearish trends.
🔧 Flexible Settings: Configure ATR length, SuperTrend factor, and initial volatility guesses.
📊 Volatility Classification: Uses k-means clustering to adapt to market conditions.
📈 Dynamic SuperTrend Calculation: Applies the classified volatility level to the SuperTrend calculation.
🔔 Alerts: Set alerts for trend shifts and volatility changes.
📋 Data Table Display: View cluster details and current volatility on the chart.
Quick Guide to Using the Machine Learning Adaptive SuperTrend Indicator
🛠 Add the Indicator: Add the indicator to favorites by pressing the star icon. Customize settings like ATR length, SuperTrend factor, and volatility percentiles to fit your trading style.
📊 Market Analysis: Observe the color changes and SuperTrend line for trend reversals. Use the data table to monitor volatility clusters.
🔔 Alerts: Enable notifications for trend shifts and volatility changes to seize trading opportunities without constant chart monitoring.
How It Works
The indicator begins by calculating the ATR values over a specified training period to assess market volatility. Initial guesses for high, medium, and low volatility percentiles are inputted. The k-means clustering algorithm then iterates to classify the ATR values into three clusters. This classification helps in determining the appropriate volatility level to apply to the SuperTrend calculation. As the market evolves, the indicator dynamically adjusts, providing real-time trend and volatility insights. The indicator also incorporates a data table displaying cluster centroids, sizes, and the current volatility level, aiding traders in making informed decisions.
Add the Machine Learning Adaptive SuperTrend to your TradingView charts today and experience a smarter way to trade! 🌟📊
Zmienność
TICK Price Label Colors[Salty]The ticker symbol for the NYSE CUMULATIVE Tick Index is TICK. The Tick Index is a short-term indicator that shows the number of stocks trading up minus the number of stocks trading down. Traders can use this ratio to make quick trading decisions based on market movement. For example, a positive tick index can indicate market optimism, while readings of +1,000 and -1,000 can indicate overbought or oversold conditions.
This script is used to color code the price label of the Symbol values zero or above in Green(default), and values below zero in red(default). For a dynamic symbol like the TICK this tells me the market is bullish when Green or Bearish when Red. I was previously using the baseline style with a Base level of 50 to accomplish this view of the symbol, but it was always difficult to maintain the zero level at the zero TICK value. This indicator is always able to color code the price label properly. Also, it has the benefit of setting the timeframe to 1 second(default) that is maintained even when the chart timeframe is changed.
Update: Added the ability to show the TICK Symbol to support viewing multiple TICK tickers at once as shown.
VIX Futures Basis StrategyVIX Futures Basis Strategy
The VIX Futures Basis Strategy is a trading approach that takes advantage of the unique characteristics of the VIX index and its futures market. The VIX, often referred to as the "fear index," measures market expectations of near-term volatility. This strategy focuses on how the VIX futures contracts behave in relation to the spot VIX index and seeks to capitalize on the market's contango and backwardation phases.
Key Concepts:
VIX Index and VIX Futures:
The VIX index reflects the market's expectation of volatility over the next 30 days.
VIX futures allow traders to speculate on the future value of the VIX index.
Contango and Backwardation:
Contango occurs when the futures price is higher than the spot price, often indicating that the market expects volatility to rise in the future.
Backwardation is when the futures price is lower than the spot price, suggesting that the market expects a decrease in volatility.
Basis:
The basis is the difference between the futures price and the spot price. This strategy examines the basis for two consecutive VIX futures contracts.
Strategy Overview:
The VIX Futures Basis Strategy uses the relationship between the VIX index and its futures contracts to generate trading signals:
Long Position on Contango:
When both the front month and the second month VIX futures contracts are in contango (their prices are above the spot VIX index by a specified threshold), the strategy takes a long position.
This implies an expectation that the market will move from a state of expected higher future volatility to a more stable state, allowing profits to be made as the futures prices converge toward the spot price.
Closing Position on Backwardation:
If the basis for both futures contracts indicates backwardation (their prices are below the spot VIX index by a threshold), the strategy closes any long positions.
This condition suggests that the market anticipates decreasing volatility, and closing positions helps to avoid potential losses.
Bollinger Bands Enhanced StrategyOverview
The common practice of using Bollinger bands is to use it for building mean reversion or squeeze momentum strategies. In the current script Bollinger Bands Enhanced Strategy we are trying to combine the strengths of both strategies types. It utilizes Bollinger Bands indicator to buy the local dip and activates trailing profit system after reaching the user given number of Average True Ranges (ATR). Also it uses 200 period EMA to filter trades only in the direction of a trend. Strategy can execute only long trades.
Unique Features
Trailing Profit System: Strategy uses user given number of ATR to activate trailing take profit. If price has already reached the trailing profit activation level, scrip will close long trade if price closes below Bollinger Bands middle line.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Major Trend Filter: Strategy utilizes 100 period EMA to take trades only in the direction of a trend.
Flexible Risk Management: Users can choose number of ATR as a stop loss (by default = 1.75) for trades. This is flexible approach because ATR is recalculated on every candle, therefore stop-loss readjusted to the current volatility.
Methodology
First of all, script checks if currently price is above the 200-period exponential moving average EMA. EMA is used to establish the current trend. Script will take long trades on if this filtering system showing us the uptrend. Then the strategy executes the long trade if candle’s low below the lower Bollinger band. To calculate the middle Bollinger line, we use the standard 20-period simple moving average (SMA), lower band is calculated by the substruction from middle line the standard deviation multiplied by user given value (by default = 2).
When long trade executed, script places stop-loss at the price level below the entry price by user defined number of ATR (by default = 1.75). This stop-loss level recalculates at every candle while trade is open according to the current candle ATR value. Also strategy set the trailing profit activation level at the price above the position average price by user given number of ATR (by default = 2.25). It is also recalculated every candle according to ATR value. When price hit this level script plotted the triangle with the label “Strong Uptrend” and start trail the price at the middle Bollinger line. It also started to be plotted as a green line.
When price close below this trailing level script closes the long trade and search for the next trade opportunity.
Risk Management
The strategy employs a combined and flexible approach to risk management:
It allows positions to ride the trend as long as the price continues to move favorably, aiming to capture significant price movements. It features a user-defined ATR stop loss parameter to mitigate risks based on individual risk tolerance. By default, this stop-loss is set to a 1.75*ATR drop from the entry point, but it can be adjusted according to the trader's preferences.
There is no fixed take profit, but strategy allows user to define user the ATR trailing profit activation parameter. By default, this stop-loss is set to a 2.25*ATR growth from the entry point, but it can be adjusted according to the trader's preferences.
Justification of Methodology
This strategy leverages Bollinger bangs indicator to open long trades in the local dips. If price reached the lower band there is a high probability of bounce. Here is an issue: during the strong downtrend price can constantly goes down without any significant correction. That’s why we decided to use 200-period EMA as a trend filter to increase the probability of opening long trades during major uptrend only.
Usually, Bollinger Bands indicator is using for mean reversion or breakout strategies. Both of them have the disadvantages. The mean reversion buys the dip, but closes on the return to some mean value. Therefore, it usually misses the major trend moves. The breakout strategies usually have the issue with too high buy price because to have the breakout confirmation price shall break some price level. Therefore, in such strategies traders need to set the large stop-loss, which decreases potential reward to risk ratio.
In this strategy we are trying to combine the best features of both types of strategies. Script utilizes ate ATR to setup the stop-loss and trailing profit activation levels. ATR takes into account the current volatility. Therefore, when we setup stop-loss with the user-given number of ATR we increase the probability to decrease the number of false stop outs. The trailing profit concept is trying to add the beat feature from breakout strategies and increase probability to stay in trade while uptrend is developing. When price hit the trailing profit activation level, script started to trail the price with middle line if Bollinger bands indicator. Only when candle closes below the middle line script closes the long trade.
Backtest Results
Operating window: Date range of backtests is 2020.10.01 - 2024.07.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -9.78%
Maximum Single Profit: +25.62%
Net Profit: +6778.11 USDT (+67.78%)
Total Trades: 111 (48.65% win rate)
Profit Factor: 2.065
Maximum Accumulated Loss: 853.56 USDT (-6.60%)
Average Profit per Trade: 61.06 USDT (+1.62%)
Average Trade Duration: 76 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Financial Frontline:Integrated Market Analysis Toolkit[drshah93]Title: Financial Frontline: Bollinger BandWidth with Moving Average + Fractal & Alligator + Ichimoku Cloud + Anchored VWAP
This script is developed to integrate multiple robust technical analysis tools into a single, comprehensive indicator. Designed for traders seeking an all-in-one solution, this script combines Fractal and Alligator, Ichimoku Cloud, Anchored VWAP, and Bollinger BandWidth with Moving Average, providing a holistic view of the market.
Unlocking Market Dynamics: How It Works Together
This multi-tool indicator is more than just a mashup; it is a strategically crafted integration that maximizes the strengths of each component to deliver a versatile and insightful trading tool.
1. Fractal and Alligator:
o Concept:
The Fractal & Alligator combination serves as a powerful mechanism for identifying trend reversals and continuations.
Fractals pinpoint potential turning points in the market, while the Alligator lines, consisting of smoothed moving averages, provide a clear indication of trend direction and strength.
By plotting visual markers for completed top and bottom fractals, this component helps traders to easily identify critical potential turning points of market reversal.
The Bill Williams' Alligator’s three moving averages (jaw, teeth, and lips) further enhance this analysis by indicating the prevailing trend and its momentum, making it easier to discern when to enter or exit trades.
o Details: Customizable jaw, teeth, and lips represent the market's direction. Top and bottom fractals help identify potential support and resistance levels.
o Usage: Enable the Alligator to visualize the market's trend direction and use fractals to spot potential entry and exit points.
2. Ichimoku Cloud:
o Concept:
The Ichimoku Cloud component adds another layer of market insight by providing a comprehensive view of support and resistance levels, trend direction, and momentum.
The cloud (Kumo) itself indicates key support and resistance zones, while the Tenkan-sen and Kijun-sen lines offer shorter-term trend and momentum insights.
The Chikou Span, or lagging line, provides a perspective on current price action relative to past prices.
This multi-faceted approach helps traders to identify high-probability trading opportunities and to understand the broader market context, allowing for more informed trading decisions.
o Details: Includes conversion line (Tenkan-sen), base line (Kijun-sen), leading spans (Senkou Span A & B), and lagging span (Chikou Span). Customizable lengths and colors for each element.
o Usage: Use the cloud's color and position relative to price to determine bullish or bearish trends and identify potential trading signals.
3. Anchored VWAP:
o Concept:
Anchored VWAPs (Volume Weighted Average Price) are dynamically anchored to significant price points such as swing highs and lows.
This component helps traders to understand the average price paid over a specific period and to identify critical price levels that may act as support or resistance.
By anchoring the VWAP to significant points, this indicator provides a more precise view of where key market participants are positioned, aiding in the identification of potential reversal points and confirming trend direction.
Anchored VWAP (Volume Weighted Average Price) provides the average price of an asset, weighted by volume, from a specific anchor point.
o Details: Multiple Anchored VWAP lines from significant highs and lows. Customizable lengths and colors for each VWAP.
o Usage: Analyze the price's relationship to VWAP lines to assess market strength and potential reversal points.
4. Bollinger BandWidth with Moving Average:
o Concept:
This component combines the volatility insights of Bollinger BandWidth with the trend-following properties of moving averages.
The Bollinger BandWidth measures the distance between the upper and lower Bollinger Bands, offering a visual representation of market volatility.
Bollinger Bands measure market volatility, while BandWidth indicates the degree of volatility.
When combined with a moving average, it helps to identify periods of market contraction and expansion.
Crossovers between the Bollinger BandWidth and the moving average provide timely alerts for potential entry and exit points, enabling traders to react quickly to changing market conditions.
o Details: Bollinger Bands with customizable lengths, source, and standard deviation. BandWidth calculation and moving average with options for SMA, EMA, SMMA, WMA.
o Usage: Identify periods of high and low volatility using BandWidth and adjust trading strategies accordingly. Use the moving average to smooth out volatility signals.
Customization Options for Tailored Analysis
One of the standout features of this multi-tool indicator is its high level of customization. Traders can toggle each indicator on or off according to their preferences and adjust input parameters such as lengths, colors, and offsets. This flexibility allows traders to tailor the tool to their specific trading style and market conditions, ensuring that they can extract maximum value from the analysis provided.
The Synergy of Combined Indicators: Enhancing Technical Analysis
The real power of this script lies in how these four indicators work together to provide a comprehensive analysis of the market. When combined, they cover various aspects of technical analysis:
• Trend Detection: The Alligator and Ichimoku Cloud work together to confirm trend direction and strength, while the Anchored VWAP highlights critical price levels.
• Reversal Points: Fractals and Ichimoku's Tenkan-sen/Kijun-sen crossovers help identify potential market reversals.
• Volatility and Momentum: The Bollinger BandWidth with Moving Average provides insights into market volatility, which complements the momentum signals from the Ichimoku Cloud.
• Support and Resistance: Fractals and Anchored VWAP pinpoint key levels. They provide clear support and resistance levels, enhancing the trader's ability to make informed decisions.
Advantages to Technical Analysis
• Holistic View: Combines trend, momentum, volatility, and price levels into a single script.
• Enhanced Decision-Making: Multiple confirmation signals increase the reliability of trading signals.
• Flexibility: Customizable settings allow traders to tailor the indicator to their specific needs.
• Efficiency: Reduces the need to switch between multiple charts and indicators, streamlining the analysis process.
How to Use:
1. Access the indicator settings to customize each component according to your trading strategy.
2. Toggle visibility for Fractal and Alligator, Ichimoku Cloud, Anchored VWAP, and Bollinger BandWidth components.
3. Adjust lengths, colors, and calculation methods to match your charting style and preferences.
4. Combine insights from trend analysis, support/resistance levels, and volatility measures for informed trading decisions.
Elevate your trading analysis with this all-in-one tool, merging multiple indicators into a powerful script that offers a comprehensive view of the market.
In Conclusion: An Indispensable Tool for Traders
This multi-tool indicator is designed to cater to the needs of traders who seek a comprehensive and versatile analytical framework. By integrating Fractal & Alligator, Ichimoku Cloud, Anchored VWAP, and Bollinger BandWidth with Moving Average, it provides a holistic view of market conditions, enhancing the trader's ability to identify key trends, support/resistance levels, and potential trading signals. This script is not just a combination of indicators but a thoughtfully crafted tool that delivers actionable insights and helps traders to stay ahead in the financial markets.
Author: drshah93
Volumetric Volatility Blocks [UAlgo]The Volumetric Volatility Blocks indicator is designed to identify significant volatility blocks based on price and volume data. It utilizes a combination of the Average True Range (ATR) and Simple Moving Average (SMA) to determine the volatility level and identify periods of heightened market activity. The indicator highlights these volatility blocks, providing traders with visual cues for potential trading opportunities. It differentiates between bullish and bearish volatility by analyzing price movement and volume, offering a nuanced view of market sentiment. This tool is particularly useful for traders looking to capitalize on periods of high volatility and momentum shifts.
🔶 Key Features
Volatility Measurement Length: Controls the period used to calculate the ATR.
Smooth Length of Volatility: Defines the period for the SMA used to smooth the ATR.
Multiplier of SMA: Sets the minimum threshold for the ATR to be considered a "high volatility" block.
Show Last X Volatility Blocks: Determines how many of the most recent volatility blocks are displayed on the chart.
Mitigation Method: Choose between "Close" or "Wick" price to filter volatility blocks based on price action. This helps avoid highlighting blocks broken by the chosen price level.
Volume Info: Displaying the volume associated with each block.
Up/Down Block Color: Sets the color for bullish and bearish volatility blocks.
🔶 Usage
The Volumetric Volatility Blocks indicator visually represents periods of high volatility with blocks on the chart. Green blocks indicate bullish volatility, while red blocks indicate bearish volatility.
Bullish Volatility Blocks: When the ATR surpasses the smoothed ATR multiplied by the set multiplier, and the price closes higher than it opened, a bullish block is formed. These blocks are generally used to identify potential buying opportunities as they indicate upward momentum.
Bearish Volatility Blocks: Conversely, bearish blocks form under the same conditions, but when the price closes lower than it opened. These blocks can signal potential selling opportunities as they highlight downward momentum.
Volume Information: Each block can display volume data, providing insight into the strength of the market movement. The percentage shown on the block indicates the relative volume contribution of that block, helping traders assess the significance of the volatility.
The volume percentages in the Volumetric Volatility Blocks indicator are calculated based on the total volume of the most recent volatility blocks. For each of the most recent volatility blocks, the percentage of the total volume is calculated by dividing the block's volume by the total volume:
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
test - ClassificationTensor-Based Classification Experiment
This innovative script represents an experimental foray into classification techniques, specifically designed to analyze returns within a compact time frame. By leveraging tensor-based analytics, it generates a comprehensive table that visually illustrates the distribution of counts across both current and historical bars, providing valuable insights into market patterns.
The script's primary objective is to classify returns over a small window, using this information to inform trading decisions. The output table showcases a normal distribution of count values for each bar in the lookback period, allowing traders to gain a deeper understanding of market behavior and identify potential opportunities.
Key Features:
Experimental classification approach utilizing tensor-based analytics
Compact time frame analysis (small window)
Comprehensive table displaying return counts across current and historical bars
Normal distribution visualization for better insight into market patterns
By exploring this script, traders can gain a deeper understanding of the underlying dynamics driving market movements and develop more effective trading strategies.
Premarket Std Dev BandsOverview
The Premarket Std Dev Bands indicator is a powerful Pine Script tool designed to help traders gain deeper insights into the premarket session's price movements. This indicator calculates and displays the standard deviation bands for premarket trading, providing valuable information on price volatility and potential support and resistance levels during the premarket hours.
Key Features
Premarket Focus: Specifically designed to analyze price movements during the premarket session, offering unique insights not available with traditional indicators.
Customizable Length: Users can adjust the averaging period for calculating the standard deviation, allowing for tailored analysis based on their trading strategy.
Standard Deviation Bands: Displays both 1 and 2 standard deviation bands, helping traders identify significant price movements and potential reversal points.
Real-Time Updates: Continuously updates the premarket open and close prices, ensuring the bands are accurate and reflective of current market conditions.
How It Works
Premarket Session Identification: The script identifies when the current bar is within the premarket session.
Track Premarket Prices: It tracks the open and close prices during the premarket session.
Calculate Premarket Moves: Once the premarket session ends, it calculates the price movement and stores it in an array.
Compute Averages and Standard Deviation: The script calculates the simple moving average (SMA) and standard deviation of the premarket moves over a specified period.
Plot Standard Deviation Bands: Based on the calculated standard deviation, it plots the 1 and 2 standard deviation bands around the premarket open price.
Usage
To utilize the Premarket Std Dev Bands indicator:
Add the script to your TradingView chart.
Adjust the Length input to set the averaging period for calculating the standard deviation.
Observe the plotted standard deviation bands during the premarket session to identify potential trading opportunities.
Benefits
Enhanced Volatility Analysis: Understand price volatility during the premarket session, which can be crucial for making informed trading decisions.
Support and Resistance Levels: Use the standard deviation bands to identify key support and resistance levels, aiding in better entry and exit points.
Customizable and Flexible: Tailor the averaging period to match your trading style and strategy, making this indicator versatile for various market conditions.
ATR X-PowerATR X-Power is a simple graphical representation of Average True Range.
The ATR is calculated on a daily basis and averaged over the "Length" specified in settings (default is 14 days).
At the start of the day, the starting price is recorded and five horizontal lines are drawn which illustrate possible ranges for the day:
Starting price
Starting price + ATR (+100%)
Starting price - ATR (-100%)
Starting price + ATR/2 (+50%)
Starting price - ATR/2 (-50%)
The final two lines are drawn using the ATR half values in such a way that a X is formed. The X represents possible motion of the price back to starting price (also known as reversion to mean). The two lines are drawn as follows:
Beginning at (Starting Price + ATR/2) and ending at (Starting Price - ATR/2)
Beginning at (Starting Price - ATR/2) and ending at (Starting Price + ATR/2)
Use cases:
ATR presents us with the average amount of price fluctuation we can expect to see in a single day on a specific instrument
If price is near the extremes (+/-100% ATR) for the day, then probability of it moving outside that range is low, which increases odds of a reversal
Bugs?
Kindly report any issues you run into and I'll try to fix them promptly.
Thank you!
ADR (Log Scale) with MTF LabelsHere's a detailed presentation of the Average Daily Range (ADR) indicator, with a focus on its advantages compared to the classic ADR, its unique features, utility, and interpretation:
Advantages Compared to Classic ADR
1. Logarithmic Scale: Unlike the classic ADR, which uses a linear scale, this version uses a logarithmic scale for calculations. This approach provides a more accurate representation of relative price movements, especially for assets with large price ranges.
2. Multi-Timeframe Analysis: This enhanced ADR indicator allows traders to view daily, weekly, and monthly ADRs simultaneously. This multi-timeframe capability helps traders understand volatility trends over different periods, offering a more comprehensive market analysis.
3. Optional Smoothing: The inclusion of an optional smoothing feature (using Exponential Moving Average, EMA) helps reduce noise in the data. This makes the indicator more reliable by filtering out short-term fluctuations and highlighting the underlying volatility trend.
4. Information Display Labels: The indicator includes labels that display precise ADR values for each timeframe directly on the chart. This feature provides immediate, clear insights without requiring additional calculations or references.
Utility of the Indicator
1. Volatility Analysis: The ADR indicator is essential for assessing market volatility. By showing the average daily price range, it helps traders gauge how much an asset typically moves within a day, week, or month.
2. Risk Management: ADR levels can be used to set stop-loss points, improving risk management strategies. Knowing the average range helps traders avoid setting stops too close to the current price, which might otherwise be triggered by normal market fluctuations.
3. Setting Realistic Targets: By understanding the average daily range, traders can set more realistic profit targets. This helps in avoiding over-ambitious goals that are unlikely to be reached within the typical market movement.
4. Identifying Entry and Exit Points: The ADR can signal potential entry and exit points. For example, if the price approaches the upper or lower ADR boundary, it might indicate an overbought or oversold condition, respectively.
Interpretation and Examples
1. Increasing Volatility: If the ADR is increasing, it indicates rising market volatility. Traders might adjust their strategies accordingly, such as widening their stop-losses to accommodate larger price swings.
2. Range Breakout: If the price significantly exceeds the daily ADR, it may signal a strong trend or exceptional market movement. Traders can use this information to stay in the trade longer or to anticipate a potential reversal.
3. Mean Reversion: Prices often revert to the ADR mean. A trader might consider mean reversion trades when the price approaches the extremes of the ADR range, expecting it to move back towards the average.
4. Multi-Timeframe Comparison: If the daily ADR is higher than the weekly ADR, it may indicate unusually high short-term volatility. This can be a signal for traders to be cautious or to capitalize on the increased movement.
While the ADR indicator provides valuable insights into market volatility and can significantly enhance trading strategies, it is essential to remember that no indicator is foolproof. Market conditions can change rapidly, and past performance is not always indicative of future results. Traders should use the ADR indicator in conjunction with other tools and follow sound risk management practices to protect their capital.
Multi-Regression StrategyIntroducing the "Multi-Regression Strategy" (MRS) , an advanced technical analysis tool designed to provide flexible and robust market analysis across various financial instruments.
This strategy offers users the ability to select from multiple regression techniques and risk management measures, allowing for customized analysis tailored to specific market conditions and trading styles.
Core Components:
Regression Techniques:
Users can choose one of three regression methods:
1 - Linear Regression: Provides a straightforward trend line, suitable for steady markets.
2 - Ridge Regression: Offers a more stable trend estimation in volatile markets by introducing a regularization parameter (lambda).
3 - LOESS (Locally Estimated Scatterplot Smoothing): Adapts to non-linear trends, useful for complex market behaviors.
Each regression method calculates a trend line that serves as the basis for trading decisions.
Risk Management Measures:
The strategy includes nine different volatility and trend strength measures. Users select one to define the trading bands:
1 - ATR (Average True Range)
2 - Standard Deviation
3 - Bollinger Bands Width
4 - Keltner Channel Width
5 - Chaikin Volatility
6 - Historical Volatility
7 - Ulcer Index
8 - ATRP (ATR Percentage)
9 - KAMA Efficiency Ratio
The chosen measure determines the width of the bands around the regression line, adapting to market volatility.
How It Works:
Regression Calculation:
The selected regression method (Linear, Ridge, or LOESS) calculates the main trend line.
For Ridge Regression, users can adjust the lambda parameter for regularization.
LOESS allows customization of the point span, adaptiveness, and exponent for local weighting.
Risk Band Calculation:
The chosen risk measure is calculated and normalized.
A user-defined risk multiplier is applied to adjust the sensitivity.
Upper and lower bounds are created around the regression line based on this risk measure.
Trading Signals:
Long entries are triggered when the price crosses above the regression line.
Short entries occur when the price crosses below the regression line.
Optional stop-loss and take-profit mechanisms use the calculated risk bands.
Customization and Flexibility:
Users can switch between regression methods to adapt to different market trends (linear, regularized, or non-linear).
The choice of risk measure allows adaptation to various market volatility conditions.
Adjustable parameters (e.g., regression length, risk multiplier) enable fine-tuning of the strategy.
Unique Aspects:
Comprehensive Regression Options:
Unlike many indicators that rely on a single regression method, MRS offers three distinct techniques, each suitable for different market conditions.
Diverse Risk Measures: The strategy incorporates a wide range of volatility and trend strength measures, going beyond traditional indicators to provide a more nuanced view of market dynamics.
Unified Framework:
By combining advanced regression techniques with various risk measures, MRS offers a cohesive approach to trend identification and risk management.
Adaptability:
The strategy can be easily adjusted to suit different trading styles, timeframes, and market conditions through its various input options.
How to Use:
Select a regression method based on your analysis of the current market trend (linear, need for regularization, or non-linear).
Choose a risk measure that aligns with your trading style and the market's current volatility characteristics.
Adjust the length parameter to match your preferred timeframe for analysis.
Fine-tune the risk multiplier to set the desired sensitivity of the trading bands.
Optionally enable stop-loss and take-profit mechanisms using the calculated risk bands.
Monitor the regression line for potential trend changes and the risk bands for entry/exit signals.
By offering this level of customization within a unified framework, the Multi-Regression Strategy provides traders with a powerful tool for market analysis and trading decision support. It combines the robustness of regression analysis with the adaptability of various risk measures, allowing for a more comprehensive and flexible approach to technical trading.
[SGM Geometric Brownian Motion]Description:
This indicator uses Geometric Brownian Motion (GBM) simulations to predict possible price trajectories of a financial asset. It helps traders visualize potential price movements, assess risks, and make informed decisions.
Geometric Brownian Motion:
Geometric Brownian Motion is an extension of standard Brownian motion (or Wiener process) used to model the random behavior of particles in physics. In finance, this concept is used to model the evolution of asset prices over time in a continuous manner. The basic idea is that the price of an asset does not only change randomly but also exponentially depending on certain parameters.
Basic formula
The formula for the evolution of the price of an asset S(t) under MBG is given by the following stochastic differential equation:
𝑑𝑆(𝑡) = 𝜇𝑆(𝑡)𝑑𝑡 + 𝜎𝑆(𝑡)𝑑𝑊(𝑡)
where:
S(t) is the price of the asset at time
μ is the expected growth rate (or drift).
σ is the volatility of the price of the asset.
dW(t) represents the noise term, i.e. the standard Brownian motion.
Explanations of the terms
Expected growth rate (μ):
This is the expected average return on the asset. If you think your asset will grow by 5% per year,
μ will be 0.05.
Volatility (σ):
It is a measure of the uncertainty or risk associated with the asset. If the asset price varies a lot, σ will be high.
Noise term (dW(t)):
It represents the randomness of the price change, modeled by a Wiener process.
Features:
Customizable number of simulations: Choose the number of price trajectories to simulate to get a better estimate of future movements.
Adjustable simulation length: Set the duration of the simulations in number of periods to adapt the indicator to your trading horizons.
Trajectory display: Visualize the simulated price trajectories directly on the chart to better understand possible future scenarios.
Dispersion calculations: Display the distribution of simulated final prices to assess dispersion and potential variations.
Sharpe ratio distribution: Analyze the risk-adjusted performance of simulations using the Sharpe ratio distribution.
Risk Statistics: Get key risk metrics like maximum drawdown, average return, and Value at Risk (VaR) at different confidence levels.
User Inputs:
Number of Simulations: 200 by default.
Simulation Length: 10 periods by default.
Brownian Motion Transparency: Adjust the transparency of simulated lines for better visualization.
Brownian Motion Display: Enable or disable the display of simulated paths.
Brownian Dispersion Display: Display the distribution of simulated final prices.
Sharpe Dispersion Display: Display the distribution of Sharpe ratios.
Customizable Colors: Choose colors for lines and tables.
Usage:
Configure Settings: Adjust the number of simulations, simulation length, and display preferences to suit your needs.
Analyze Simulated Paths: Simulated path lines appear on the chart, representing possible price developments.
Review Dispersion Charts: Review the charts to understand the distribution of final prices and Sharpe ratios, as well as key risk statistics. This indicator is ideal for traders looking to anticipate future price movements and assess the associated risks. With its detailed simulations and dispersion analyses, it provides valuable insight into the financial markets.
Daily Liquidity Peaks and Troughs [ST]Daily Liquidity Peaks and Troughs
Description in English:
This indicator identifies peaks and troughs of highest liquidity on a daily timeframe by analyzing volume data. It helps traders visualize key points of high buying or selling pressure, which could indicate potential reversal or continuation areas.
Detailed Explanation:
Configuration:
Lookback Length: This input defines the period over which the highest high and lowest low are calculated. The default value is 14. This means the script will look at the past 14 bars to determine if the current high or low is a pivot point.
Volume Threshold Multiplier: This input defines the multiplier for the average volume. For example, a multiplier of 1.5 means the volume needs to be 1.5 times the average volume to be considered a significant peak or trough.
Peak Color: This input sets the color for liquidity peaks. The default color is red.
Trough Color: This input sets the color for liquidity troughs. The default color is green.
Volume Calculation:
Average Volume: The script calculates the simple moving average (SMA) of the volume over the lookback period. This helps to identify periods of significantly higher volume.
Volume Threshold: The threshold is determined by multiplying the average volume by the volume threshold multiplier. Only volumes exceeding this threshold are considered significant.
Identifying Peaks and Troughs:
Liquidity Peak: A peak is identified when the current high is the highest high over the lookback period and the current volume exceeds the volume threshold. This indicates a potential area of strong selling pressure.
Liquidity Trough: A trough is identified when the current low is the lowest low over the lookback period and the current volume exceeds the volume threshold. This indicates a potential area of strong buying pressure.
These peaks and troughs are marked on the chart with labels and shapes for easy visualization.
Plotting Peaks and Troughs:
Labels: The script uses labels to mark peaks and troughs on the chart. Peaks are marked with a red label and troughs with a green label.
Shapes: The script plots triangles above peaks and below troughs to highlight these areas visually.
Indicator Benefits:
Liquidity Identification: Helps traders identify key areas of high liquidity, indicating strong buying or selling pressure.
Visual Cues: Provides clear visual signals for potential reversal or continuation points, aiding in making informed trading decisions.
Customizable Parameters: Allows traders to adjust the lookback length and volume threshold to suit different trading strategies and market conditions.
Justification of Component Combination:
Peaks and Troughs Identification: Combining pivot points with volume analysis provides a robust method to identify significant liquidity areas. This helps in detecting potential market reversals or continuations.
Volume Analysis: Utilizing average volume and volume threshold ensures that only significant volume spikes are considered, enhancing the accuracy of identified peaks and troughs.
How Components Work Together:
The script first calculates the average volume over the specified lookback period.
It then checks each bar to see if it qualifies as a liquidity peak or trough based on the highest high, lowest low, and volume threshold.
When a peak or trough is identified, it is marked on the chart with a label and a shape, providing clear visual cues for traders.
Título: Picos e Fundos de Liquidez Diários
Descrição em Português:
Este indicador identifica picos e fundos de maior liquidez no gráfico diário, analisando os dados de volume. Ele ajuda os traders a visualizar pontos-chave de alta pressão de compra ou venda, o que pode indicar áreas potenciais de reversão ou continuação.
Explicação Detalhada:
Configuração:
Comprimento de Retrocesso: Este input define o período sobre o qual a máxima e mínima são calculadas. O valor padrão é 14. Isso significa que o script analisará os últimos 14 candles para determinar se a máxima ou mínima atual é um ponto de pivô.
Multiplicador de Limite de Volume: Este input define o multiplicador para o volume médio. Por exemplo, um multiplicador de 1.5 significa que o volume precisa ser 1.5 vezes o volume médio para ser considerado um pico ou fundo significativo.
Cor do Pico: Este input define a cor para os picos de liquidez. A cor padrão é vermelha.
Cor do Fundo: Este input define a cor para os fundos de liquidez. A cor padrão é verde.
Cálculo do Volume:
Volume Médio: O script calcula a média móvel simples (SMA) do volume ao longo do período de retrocesso. Isso ajuda a identificar períodos de volume significativamente mais alto.
Limite de Volume: O limite é determinado multiplicando o volume médio pelo multiplicador de limite de volume. Apenas volumes que excedem esse limite são considerados significativos.
Identificação de Picos e Fundos:
Pico de Liquidez: Um pico é identificado quando a máxima atual é a máxima mais alta no período de retrocesso e o volume atual excede o limite de volume. Isso indica uma potencial área de forte pressão de venda.
Fundo de Liquidez: Um fundo é identificado quando a mínima atual é a mínima mais baixa no período de retrocesso e o volume atual excede o limite de volume. Isso indica uma potencial área de forte pressão de compra.
Esses picos e fundos são marcados no gráfico com etiquetas e formas para fácil visualização.
Plotagem de Picos e Fundos:
Etiquetas: O script usa etiquetas para marcar picos e fundos no gráfico. Os picos são marcados com uma etiqueta vermelha e os fundos com uma etiqueta verde.
Formas: O script plota triângulos acima dos picos e abaixo dos fundos para destacar essas áreas visualmente.
Benefícios do Indicador:
Identificação de Liquidez: Ajuda os traders a identificar áreas-chave de alta liquidez, indicando forte pressão de compra ou venda.
Cues Visuais: Fornece sinais visuais claros para pontos potenciais de reversão ou continuação, auxiliando na tomada de decisões informadas.
Parâmetros Personalizáveis: Permite que os traders ajustem o comprimento de retrocesso e o limite de volume para se adequar a diferentes estratégias de negociação e condições de mercado.
Justificação da Combinação de Componentes:
Identificação de Picos e Fundos: A combinação de pontos de pivô com análise de volume fornece um método robusto para identificar áreas significativas de liquidez. Isso ajuda na detecção de potenciais reversões ou continuações de mercado.
Análise de Volume: Utilizar o volume médio e o limite de volume garante que apenas picos de volume significativos sejam considerados, aumentando a precisão dos picos e fundos identificados.
Como os Componentes Funcionam Juntos:
O script primeiro calcula o volume médio ao longo do período especificado de retrocesso.
Em seguida, verifica cada barra para ver se ela se qualifica como um pico ou fundo de liquidez com base
Chieu - Bollinger Bands SMA 50 StrategyOverview
The Custom Bollinger Bands Indicator is a versatile tool designed to help traders identify potential market reversals and optimize their trading strategies. This indicator combines Bollinger Bands with an ATR-based stop-loss mechanism, configurable take-profit levels, and dynamic position sizing to manage risk effectively. By highlighting key market conditions and providing clear visual cues, it enables traders to make informed decisions and execute trades with precision.
Key Features
Bollinger Bands Calculation:
The indicator calculates Bollinger Bands based on a configurable Simple Moving Average (SMA) length.
Standard deviation multiplier is adjustable, allowing traders to fine-tune the width of the bands.
Candlestick Highlighting:
Candles that touch the upper or lower Bollinger Bands are highlighted, indicating potential overbought or oversold conditions.
Reversal candles are identified and highlighted based on specific criteria:
The candle must touch the Bollinger Bands for two consecutive periods.
The reversal candle must have a body at least twice the size of the previous candle's body.
The reversal candle must close in the opposite direction to the previous candle (e.g., a bullish candle following a bearish one).
Stop-Loss and Take-Profit Levels:
Stop-loss levels are calculated using the ATR (Average True Range) indicator, ensuring they are dynamically adjusted based on market volatility.
Two configurable take-profit levels (1R and 2R) are plotted based on the initial risk (distance between entry and stop-loss).
Take-profit and stop-loss lines are visually represented on the chart for easy reference.
Position Sizing and Risk Management:
The indicator includes configurable inputs for account balance, leverage, and risk percentage.
It calculates the nominal value (position size without leverage) and cost value (position size with leverage) based on the specified risk parameters.
Combined labels display SL, TP, nominal value, and cost value, replacing the default "Reversal" text for clear, concise information.
Customization Options:
Users can configure the length of the take-profit lines.
The option to toggle the highlighting of candles touching the Bollinger Bands on or off, while always highlighting the identified reversal candles.
How to Use
Configuration:
Set the desired SMA length and Bollinger Bands multiplier in the input settings.
Configure the ATR length for accurate stop-loss calculations.
Adjust the risk-reward ratio and take-profit line length according to your trading strategy.
Specify your account balance, leverage, and risk percentage for precise position sizing.
Chart Analysis:
Monitor the chart for candles touching the upper or lower Bollinger Bands. These highlights indicate potential overbought or oversold conditions.
Look for highlighted reversal candles, which meet the specified criteria and suggest a potential market reversal.
Use the plotted stop-loss and take-profit lines to manage your trades effectively. The combined labels provide all necessary information (SL, TP, nominal value, and cost value) for quick decision-making.
Execution and Risk Management:
Enter trades based on the reversal candle signals.
Set your stop-loss at the indicated level using the ATR calculation.
Take partial profits at the first take-profit level (1R) and adjust your stop-loss to the entry point to secure the remaining position.
Exit the trade entirely at the second take-profit level (2R) or if the price returns to the adjusted stop-loss level.
Rolling Price Activity Heatmap [AlgoAlpha]📈 Rolling Price Activity Heatmap 🔥
Enhance your trading experience with the Rolling Price Activity Heatmap , designed by AlgoAlpha to provide a dynamic view of price activity over a rolling lookback period. This indicator overlays a heatmap on your chart, highlighting areas of significant price activity, allowing traders to spot key price levels at a glance.
🌟 Key Features
📊 Rolling Heatmap: Visualize historical price activity intensity over a user-defined lookback period.
🔄 Customizable Lookback: Adjust the heatmap lookback period to suit your trading style.
🌫️ Transparency Filter: Fine-tune the heatmap’s transparency to filter out less significant areas.
🎨 Color Customization: Choose colors for up, down, and highlight areas to fit your chart’s theme.
🔄 Inverse Heatmap Option: Flip the heatmap to highlight less active areas if needed.
🛠 Add the Indicator: Add the Indicator to favorites. Customize settings like lookback period, transparency filter, and colors to fit your trading style.
📊 Market Analysis: Watch for areas of high price activity indicated by the heatmap to identify potential support and resistance levels.
🔧 How it Works
This script calculates the highest and lowest prices within a specified lookback period and divides the price range into 15 segments. It counts the number of candles that fall within each segment to determine areas of high and low price activity. The script then plots the heatmap on the chart, using varying levels of transparency to indicate the strength of price activity in each segment, providing a clear visual representation of where significant trading occurs.
Stay ahead of the market with this powerful visualization tool and make informed trading decisions! 📈💼
Harmonic Trading Tachometer [Pinescriptlabs]Key Features:
Visual Tachometer:
Represents market harmony through a speedometer on the chart.
The tachometer displays a range of harmony from "Highly Bearish" to "Highly Bullish."
Harmony Calculation:
Harmony Score: Based on ATR (Average True Range) range calculations for short, medium, and long periods. The harmony score is a weighted combination of these scores.
Interpretation: Harmony is translated into an interpretive category that can be "Highly Bearish," "Bearish," "Neutral," "Bullish," or "Highly Bullish."
Price Projection:
Estimates future price movement considering the current trend and the weight of each trend period (short, medium, and long).
Harmonic Change Detection:
Identifies significant changes in market harmony and adjusts sensitivity with predefined thresholds.
Confirmation and Divergence Signals:
Detects bullish or bearish confirmation signals as well as divergences, based on market harmony and price projection.
Additional Visualization:
Includes an optional market pentagram chart to visualize harmony on a broader scale.
Provides detailed information in a table about harmony, price projection, and harmonic changes.
How the Script Works:
Initial Calculations:
Ranges and Scores: Calculates ATR ranges for different periods (short, medium, and long). Then, evaluates the harmony score using the given formula.
Harmony: Obtained through the weighted combination of short, medium, and long-term scores.
Price Projection:
The projection is adjusted based on the difference between the current closing price and the exponential moving averages (EMAs) for different periods, weighted by the defined factors.
How to Use :
Tachometer Interpretation:
Observe the needle's position on the tachometer to assess the current market harmony.
Use the colors and labels to quickly interpret the market's state.
Projection and Changes:
Use the price projection to identify potential support or resistance levels.
Monitor harmonic changes and their strengths to adjust your trading strategies.
Confirmations and Divergences:
Pay attention to confirmation and divergence signals to decide on potential entries or exits.
Customization:
Adjust the indicator parameters, such as base length, harmony factor, change detection period, and trend weights, to fit your trading style and timeframe.
Español:
**Tacómetro Visual:
- Representa la armonía del mercado mediante un velocímetro en el gráfico.
- El tacómetro muestra un rango de armonía desde "Altamente Bajista" hasta "Altamente Alcista."
Cálculo de Armonía:
- Puntuación de Armonía:** Basada en los cálculos del rango ATR (Average True Range) para períodos cortos, medios y largos. La puntuación de armonía es una combinación ponderada de estas puntuaciones.
- Interpretación: La armonía se traduce en una categoría interpretativa que puede ser "Altamente Bajista," "Bajista," "Neutral," "Alcista," o "Altamente Alcista."
**Proyección de Precios:
- Estima el movimiento futuro de los precios considerando la tendencia actual y el peso de cada período de tendencia (corto, medio y largo).
**Detección de Cambios Armonicos:
- Identifica cambios significativos en la armonía del mercado y ajusta la sensibilidad con umbrales predefinidos.
**Señales de Confirmación y Divergencia:
- Detecta señales de confirmación alcista o bajista, así como divergencias, basadas en la armonía del mercado y la proyección de precios.
**Visualización Adicional:**
- Incluye un gráfico opcional de un pentagrama de mercado para visualizar la armonía en una escala más amplia.
- Proporciona información detallada en una tabla sobre la armonía, la proyección de precios y los cambios armónicos.
**Cómo Funciona el Script:**
Cálculos Iniciales:
- **Rangos y Puntuaciones:** Calcula los rangos del ATR para diferentes períodos (corto, medio y largo). Luego, evalúa la puntuación de armonía utilizando la fórmula dada.
- **Armonía:** Se obtiene a través de la combinación ponderada de las puntuaciones de corto, medio y largo plazo.
**Proyección de Precios:**
- La proyección se ajusta según la diferencia entre el precio de cierre actual y las medias móviles exponenciales (EMA) para diferentes períodos, ponderadas por los factores definidos.
**Cómo Usar:**
**Interpretación del Tacómetro:**
- Observa la posición de la aguja en el tacómetro para evaluar la armonía actual del mercado.
- Usa los colores y las etiquetas para interpretar rápidamente el estado del mercado.
**Proyección y Cambios:**
- Usa la proyección de precios para identificar posibles niveles de soporte o resistencia.
- Monitorea los cambios armónicos y sus fortalezas para ajustar tus estrategias de trading.
**Confirmaciones y Divergencias:**
- Presta atención a las señales de confirmación y divergencia para decidir posibles entradas o salidas.
**Personalización:**
- Ajusta los parámetros del indicador, como la longitud base, el factor de armonía, el período de detección de cambios y los pesos de tendencia, para adaptarlo a tu estilo de trading y marco de tiempo.
CoT Trend Change MomentumI discovered that whenever there's huge change in long IO or short IO there will be a momentum shift. So, I created this indicator to spot massive explosive volume changes for commercials and non commercials activity. Using standard deviation 2 and -2 as extreme point. Whatever crossing above standard deviation 2 indicating positions are added regardless whether it is long or shorts, whatever crossing below standard deviation -2 means positions are closed.
This is how I use this indicator:
1) In this example , i use only the commercials long and shorts. Whenever the longs exceed stdeviation +2, means that long volume flow in massively, for me this can be indicating potential to the upside. Whenever longs fall below stdeviation-2, for me this can be indicating that commercials are either taking profits for the short positions or accumulating for another bull price.
2) For shorts same logic applied here, when it exceeds stdeviation +2, mean commercials shorts position increase massively, when it exceeds stdeviation-2, means that commercials closed their short positions.
For this script, I use 13 weeks period as lookback, u guys may directly modify the period in the script to set the period that u want.
I've added for non-commercials as well, to ease people who emphasizes on non-commercials positioning analysis process.
I'm still trying to incorporate this with Open Interest Analysis. Hopefully u guys find this indicator useful. Feel free to modify it, to understand it more, my suggestions are u compare date by date the positions, to see the extreme points. The indicator only works in weekly chart, it is non repainted only in weekly chart, meaning that the indicator shows the histogram just as the week open.
Alpha-Sutte Multi-Price Indicator [CHE] Overview
The AlphaSutte MultiPrice Indicator is a powerful tool for forecasting market movements and generating trading signals. At its core is the AlphaSutte Model, which stands out for its innovative approach to predicting future price movements.
Inspired by the () on TradingView, this indicator enhances the original concept by integrating it with the T3 smoothing technique to improve trend identification and signal reliability.
The AlphaSutte Model
The AlphaSutte Model is a mathematical method for forecasting prices based on the analysis of historical price data. It is applied to various price components such as High, Low, Open, and Close. The model predicts future values using differences and weighted averages of previous periods. Here are the key steps and components of the AlphaSutte Model:
1. Data Extraction:
The model extracts historical values at specified intervals. For example, it uses the values from the last four periods for calculations.
2. Difference Calculations:
Differences between successive historical values are calculated:
Delta_x: Difference between the first and fourth values.
Delta_y: Difference between the second and first values.
Delta_z: Difference between the third and second values.
3. Weighted Average Calculation:
These differences are then integrated into a weighted average to forecast the future value:
The weighted average combines the historical values and their differences to calculate the forecasted value, referred to as a_t.
4. Application to Price Components:
The AlphaSutte Model can be applied to various price components:
High: Forecasting the future high price.
Low: Forecasting the future low price.
Open: Forecasting the future opening price.
Close: Forecasting the future closing price.
5. Averaging AlphaSutte Values:
If multiple price components are used for calculation, an average of the AlphaSutte values is computed. This average serves as the basis for generating trading signals.
Trading Signals and Directional Change
The AlphaSutte Model is used to generate long and short trading signals. These signals are confirmed by the directional change of the T3 Indicator to enhance reliability:
Long Signals:
A long signal is generated when the average value of the AlphaSutte Model is positive, and the T3 indicator previously showed a downtrend.
These signals are displayed with green labels and lines on the chart.
Short Signals:
A short signal is generated when the average value of the AlphaSutte Model is negative, and the T3 indicator previously showed an uptrend.
These signals are displayed with red labels and lines on the chart.
StepbyStep Explanation of the Script
The AlphaSutte MultiPrice Indicator script in TradingView is designed to provide comprehensive market trend analysis and trading signal generation. Here is a stepbystep explanation of how the script operates:
1. Input Parameters:
The script begins by defining several input parameters for the T3 indicator and AlphaSutte Model, including:
`t3Length`: The length of the T3 moving average.
`t3VolumeFactor`: The volume factor used in T3 smoothing.
Boolean inputs to determine which price components (High, Low, Open, Close) should use the AlphaSutte Model.
`numLastLabels`: The number of last labels to display for recent signals.
2. T3 Smoothing Function:
The `t3Smoothing` function calculates the T3 smoothed value for the specified source price using a series of exponential moving averages (EMAs):
It calculates six sequential EMAs of the source price.
It then combines these EMAs using specific coefficients to obtain the T3 value.
3. AlphaSutte Calculation Function:
The `get_alpha_sutte` function forecasts future values based on historical price data:
It extracts historical price values at specific intervals.
It calculates the differences (deltas) between these values.
It computes a weighted average of these deltas to obtain the AlphaSutte value.
4. Calculating AlphaSutte Components:
The script calculates the AlphaSutte values for the selected price components (High, Low, Open, Close) based on user input.
It then averages these values if multiple components are selected.
5. Generating Long and Short Conditions:
The script defines conditions for generating long and short signals based on the AlphaSutte average:
`long_condition`: True if the AlphaSutte average is positive.
`short_condition`: True if the AlphaSutte average is negative.
6. Tracking T3 Trend Direction:
The script updates state variables to track whether the T3 line is in an uptrend or downtrend:
`t3_uptrend`: True if the T3 value is higher than the previous T3 value.
`t3_downtrend`: True if the T3 value is lower than the previous T3 value.
7. Generating and Managing Labels and Lines:
The script generates labels and lines on the chart to visualize long and short signals:
For long signals, green labels and lines are created when the long condition is met, and the T3 was previously in a downtrend.
For short signals, red labels and lines are created when the short condition is met, and the T3 was previously in an uptrend.
Old labels and lines are deleted to keep the chart clean and relevant.
8. Updating Lines to Current Candle:
The script dynamically updates the end points of the lines to the current candle to reflect the latest market data.
9. Highlighting Movements:
The script optionally highlights the T3 line based on its direction to visually emphasize the trend:
Green for an uptrend and red for a downtrend.
10. Plotting the T3 Line:
Finally, the T3 line is plotted on the chart with the specified color and line width to provide a clear visualization of the trend.
Conclusion
The primary focus of the AlphaSutte MultiPrice Indicator is on the forecasting capabilities of the AlphaSutte Model. This model's forecasts are the most critical part of the indicator, providing the essential signals for potential market movements. The T3 indicator serves as a confirmation tool, validating these forecasts by indicating the direction of the trend. This combination enhances the reliability of the trading signals, making the AlphaSutte MultiPrice Indicator a valuable asset for traders looking to make informed decisions based on robust market analysis.
Best regards Chervolino
Buffett Valuation Indicator [TradeDots]The Buffett Valuation Indicator (also known as the Buffett Index or Buffett Ratio) measures the ratio of the total United States stock market to GDP.
This indicator helps determine whether the valuation changes in US stocks are justified by the GDP level.
For example, the ratio is calculated based on the standard deviations from the historical trend line. If the value exceeds +2 standard deviations, it suggests that the stock market is overvalued relative to GDP, and vice versa.
This "Buffett Valuation Indicator" is an enhanced version of the original indicator. It applies a Bollinger Band over the Valuation/GDP ratio to identify overvaluation and undervaluation across different timeframes, making it efficient for use in smaller timeframes, e.g. daily or even hourly intervals.
HOW DOES IT WORK
The Buffett Valuation Indicator measures the ratio between US stock valuation and US GDP, evaluating whether stock valuations are overvalued or undervalued in GDP terms.
In this version, the total valuation of the US stock market is represented by considering the top 10 market capitalization stocks.
Users can customize this list to include other stocks for a more balanced valuation ratio. Alternatively, users may use S&P 500 ETFs, such as SPY or VOO, as inputs.
The ratio is plotted as a line chart in a separate panel below the main chart. A Bollinger Band with a default 100-period and multiples of 1 and 2 is used to identify overvaluation and undervaluation.
For instance, if the ratio line moves above the +2 standard deviation line, it indicates that stocks are overvalued, signaling a potential selling opportunity.
APPLICATION
When the indicator is applied to a chart, we observe the ratio line's movements relative to the standard deviation lines. The further the line deviates from the standard deviation lines, the more extreme the overvaluation or undervaluation.
We look for buying opportunities when the Buffett Index moves below the first and second standard deviation lines and sell opportunities when it moves above these lines. This indicator is used as a microeconomic confirmation tool, in combination with other indicators, to achieve higher win-rate setups.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
No Lag SupertrendNo Lag Supertrend indicator improves upon the original supertrend by incorporating calculation methods that enhance responsiveness and accuracy. Traditional supertrend indicators often suffer from lag, which can delay signals and affect trading decisions. No Lag Supertrend addresses this issue through the use of KAMA (Kaufman’s Adaptive Moving Average) and Hull ATR (Average True Range) calculations.
Goals of No Lag Supertrend:
- Lag reduction: one of the main issues with traditional supertrend indicators is their lag, which can result in delayed entry and exit signals. By integrating KAMA and Hull ATR, the no lag supertrend minimizes this delay, providing more timely signals.
- Market Noise Filtering: The combined use of KAMA and Hull ATR effectively filters out market noise, ensuring that signals are based on significant price movements rather than minor fluctuations.
- Consistency Across Different Market Conditions: The adaptive nature of KAMA and the smooth responsiveness of Hull ATR ensure that the No Lag Supertrend performs consistently across various market conditions, from trending to volatile markets.
Credits: This code is based on the TradingView supertrend but improved the ATR calculations.
Auto Fitting GARCH OscillatorOverview
The Auto Fitting GARCH Oscillator is a sophisticated volatility indicator that dynamically fits GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models to the price data. It optimizes the parameters of the GARCH model to provide a reliable measure of volatility, which is then normalized to fit within a 0-100 range, making it easy to interpret as an oscillator. This indicator helps traders identify periods of high and low volatility, which can be crucial for making informed trading decisions.
Key Features
Dynamic GARCH(p, q) Fitting: Automatically optimizes the GARCH model parameters for the best fit.
Volatility Oscillator: Normalizes the volatility measure to a 0-100 range, indicating overbought and oversold conditions.
Customizable Timeframes: Adapts to various chart timeframes, from intraday to monthly data.
Projected Volatility: Provides options for projecting future volatility based on the optimized GARCH model.
User-friendly Visualization: Displays the oscillator with clear overbought and oversold levels.
Concepts Underlying the Calculations
The indicator leverages the GARCH model, which is widely used in financial time series analysis to model volatility clustering. The GARCH model considers past variances and returns to predict future volatility. This indicator dynamically adjusts the p and q parameters of the GARCH model within a specified range to find the optimal fit, minimizing the sum of squared errors (SSE).
How It Works
Data Preparation: Calculates the logarithmic returns and lagged variances from the price data.
SSE Optimization: Iterates through different p and q values to find the best GARCH parameters that minimize the SSE.
GARCH Calculation: Uses the optimized parameters to calculate the GARCH-based volatility.
Normalization: Normalizes the calculated volatility to a 0-100 range to form an oscillator.
Visualization: Plots the oscillator with overbought (70) and oversold (30) levels for easy interpretation.
How Traders Can Use It
Volatility Analysis: Identify periods of high and low volatility to adjust trading strategies accordingly.
Overbought/Oversold Conditions: Use the oscillator levels to identify potential reversal points in the market.
Risk Management: Incorporate volatility measures into risk management strategies to avoid trades during highly volatile periods.
Projection: Use the projected volatility feature to anticipate future market conditions.
Example Usage Instructions
Add the Indicator: Apply the "Auto Fitting GARCH Oscillator" to your chart from the Pine Script editor or TradingView library.
Customize Parameters: Adjust the maxP and maxQ values to set the range for GARCH model optimization.
Select Data Type: Choose between "Projected Variance in %" or "Projected Deviation in %" based on your analysis preference.
Set Projection Periods: Use the perForward input to specify how many periods forward you want to project the volatility.
Interpret the Oscillator: Observe the oscillator line and the overbought/oversold levels to make informed trading decisions.
Custom ATR Trailing StopThis Script creates a custom ATR (Average True Range) trailing stop. It allows traders to set up automated stop-loss levels based on the ATR, which adjusts dynamically to market volatility. The script is designed to support both long and short trades, offering flexibility and precision in trade management.
When loading the indicator to your chart, simply click to set the trade begining time, confirm various settings and you are set.
Check tooltips for more details in the input settigns menu.
User Inputs
Trade Setup: Allows users to set the trade direction (Long or Short), the signal source for entries, and the specific bar time for the trade setup.
ATR Settings: Configurable ATR lookback period, ATR smoothing period, initial ATR multiplier for setting the stop-loss, breakeven ATR multiplier, and a manual breakeven level.
ATR Calculations
Computes the ATR and its moving average.
Determines initial and breakeven stop levels based on the ATR.
Signal Validation
Validates long or short trade signals based on the specified bar time and trade direction.
Triggers alerts when a valid trade signal is detected.
Trailing Stop Logic
For long trades, adjusts the stop-loss level dynamically based on the ATR.
For short trades, performs similar adjustments in the opposite direction.
Updates the trailing stop level to ensure it follows the price, moving closer as the price moves favorably.
Resets the trade state when the stop-loss is hit, triggering an alert.
Plotting
Plots the trailing stop levels on the chart.
Uses green for stop levels indicating profit and red for stop levels indicating a loss.
T3 [RATE OF CHANGE] by SKiNNiEHDeveloped by Tim Tillson, the Tilson Moving Average (T3) is a trend indicator with the advantage of having less lag than other ones. That is, a faster moving average. The T3 moving average is an "indicator of an indicator" as it includes several EMAs of another EMA. Unlike other moving averages, the t3 adds the so-called volume factor, a value between 0 and 1.
The T3 RATE OF CHANGE by SKiNNiEH is a unique indicator that integrates the T3 moving average with a normalized Rate of Change (RoC) calculation. Unlike traditional T3 moving averages, this indicator provides additional smoothing modes (SINGLE, DOUBLE & TRIPLE) for the T3, whilst enhancing visual feedback of the plotted line by generating a dynamic line thickness, a dynamic line color & brightness and trade entry bars, offering traders a more dynamic view of market conditions without going "overboard" with settings.
How It Works
Visualization
The T3 line varies in thickness and color based on the RoC values, giving traders visual cues about market strength and direction.
Thicker and brighter lines indicate stronger trends, while thinner and duller lines suggest weaker trends.
Rate of Change Filte r
This filter refines trend detection by using the line thickness measurement.
Adjustable from 0 (disabled) to 4, where higher settings only consider stronger trends for signals.
The T3 line turns gray when the filter is triggered or when the RoC is extremely low, signaling a weak or neutral market.
T3 Calculation (mode)
SINGLE
The T3 calculation is applied once to the closing price.
This mode has the least smoothing effect and the least lag. It reacts more quickly to price changes but is less smooth.
DOUBLE
The T3 calculation is applied twice sequentially.
The first T3 calculation smooths the closing price.
The second T3 calculation smooths the result of the first T3 calculation.
This mode provides more smoothing and introduces more lag compared to SINGLE mode. It is smoother but reacts slower to price changes.
TRIPLE
The T3 calculation is applied three times sequentially.
The first T3 calculation smooths the closing price.
The second T3 calculation smooths the result of the first T3 calculation.
The third T3 calculation smooths the result of the second T3 calculation.
This mode provides the most smoothing and introduces the most lag by reacting the slowest to price changes.
Rate of Change (RoC) Calculation
The script calculates the Rate of Change (RoC) for the T3 values based on the selected mode (SINGLE, DOUBLE, TRIPLE). The RoC measures the percentage change between the most recent value and a value in the past. The measurement is then normalized in three different ranges.
Normalization 5: Determines T3 line thickness on a scale from 0 - 5
Normalization 10: Determines T3 color brightness on a scale from 0 - 10
Normalization 100: Determines Rate of Change percentage
Rate of Change Filter
The script uses the RoC filter to refine the trend detection logic. By using the line thickness measurement, a filter can be enabled by setting this input on 1 - 4. As an example, setting this to 4 means that only a line thickness of 5 would be considered for a trade signal. Setting this to 0 disables the filter. The T3 line will turn gray when the filter is triggered, the T3 line can also turn gray without the filter, when the Rate of Change is extremely low.
Trade Signals
A trade signal is printed as a vertical green or red bar when the following conditions are met:
Long:
Closing price is above the T3 line
Rate of Change percentage is above 0
Previous trade signal was a short signal **
Rate of Change is not filtered
Short:
Closing price is below the T3 line
Rate of Change percentage is below 0
Previous trade signal was a long signal **
Rate of Change is not filtered
** Or this is the very first recorded trade signal
It should be noted that the trade signals in this script are trade entry signals, not trade exit signals. Use at your own risk.
Instructions for Use
Setting Up the Indicator
Apply the indicator to your trading chart.
Choose the desired T3 mode (SINGLE, DOUBLE, TRIPLE) based on your need for smoothing and lag.
Set the desired length (lookback period).
Set the desired factor between 0 and 1 (increments of 0.1)
Choose an overall line thickness and brightness that suits your screen and taste preferences.
Apply the Rate of Change filter. Setting this to 0 will disable the filter
Tip: use the trade entry vertical bars as a visual calibration tool the adjust mode, length, factor and filter.
Interpreting Visual Cues
Observe the T3 line's thickness: thicker lines indicate stronger trends, while thinner lines suggest weaker trends.
Observe the T3 line's color and color brightness: green indicates a more bullish trend, while red indicates a more bearish trend. A brighter color suggest a stronger trend. A gray color means the RoC is very low / neutral, or the RoC filter is active.
Observe the T3 line's location relative to price: below price indicates a more bullish trend, above price indicates a more bearish trend. The T3 line distance from price can also be an indication of trend strength.
Observe vertical bars: a vertical bar is printed green when long conditions are met, a vertical bar is printed red when short conditions are met. See the rules that explain the trigger for this bar above.
Alerts
Go to the settings tab, set the condition to T3.RoC.S + LONG or SHORT.
Enter an alert name and message.
Configure your notification preferences in the notifications tab and create the alert
Notifications-tab: Choose your notification preferences
Create the alert.
