From TradersList Editors
From TradersList Editors
Enhance your trading decisions by utilizing multi-timeframe analysis with Logistic Regression to predict asset movement probabilities.
Enhance your trading decisions by utilizing multi-timeframe analysis with Logistic Regression to predict asset movement probabilities.
Machine Learning Logistic Regression Indicator for TradingView: Probabilistic Price Direction Prediction
Machine Learning Logistic Regression Indicator for TradingView: Probabilistic Price Direction Prediction

by capissimo on TradingView

by capissimo on TradingView
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Machine Learning: Logistic Regression
Machine Learning: Logistic Regression
Machine Learning: Logistic Regression is a TradingView indicator that uses the classic logistic regression predict the probability of future price paths. Includes multi-timeframe functionality.
Machine Learning: Logistic Regression is a TradingView indicator that uses the classic logistic regression predict the probability of future price paths. Includes multi-timeframe functionality.

Get on TradingView
This indicator is available on TradingView web charting platform. Signing up for a free account is required, no downloads.

Get on TradingView
This indicator is available on TradingView web charting platform. Signing up for a free account is required, no downloads.
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Open Source
Listing has publically available source code that can be audited and modified as needed.
🔑
Open Source
Listing has publically available source code that can be audited and modified as needed.
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Free Access
All features of this listing are fully free to use with no pricing tiers. Simply start using.
💸
Free Access
All features of this listing are fully free to use with no pricing tiers. Simply start using.
✅
Robust Theory
Concepts and theories mentioned in listing are based on generally approved and well established notions.
✅
Robust Theory
Concepts and theories mentioned in listing are based on generally approved and well established notions.
🌐
Popular Topic
Concepts and theories mentioned in listing are popular topics in web search
🌐
Popular Topic
Concepts and theories mentioned in listing are popular topics in web search
Published by capissimo on TradingView
Published by capissimo on TradingView
Probabilistic Price Direction Prediction
This indicator applies the logistic regression algorithm - a foundational machine learning technique - to predict the probability that price will move up or down. Rather than giving a binary signal, it outputs a probability score, letting traders assess confidence levels before making a trade decision based on the model's forecast.
How Logistic Regression Works in Trading
Logistic regression analyzes historical relationships between input features and binary outcomes. In this case, it processes price data to estimate the likelihood of the next move being bullish or bearish. The output is a value between 0 and 1 - a reading near 0.8, for example, suggests an 80% probability of an upward move based on the model.
Probabilistic Price Direction Prediction
This indicator applies the logistic regression algorithm - a foundational machine learning technique - to predict the probability that price will move up or down. Rather than giving a binary signal, it outputs a probability score, letting traders assess confidence levels before making a trade decision based on the model's forecast.
How Logistic Regression Works in Trading
Logistic regression analyzes historical relationships between input features and binary outcomes. In this case, it processes price data to estimate the likelihood of the next move being bullish or bearish. The output is a value between 0 and 1 - a reading near 0.8, for example, suggests an 80% probability of an upward move based on the model.
Multi-Timeframe Functionality
The indicator includes multi-timeframe capabilities, allowing the model to consider data from higher timeframes when generating predictions. This is important because a bullish signal on a 15-minute chart that aligns with a bullish probability on the 4-hour chart carries significantly more weight than a signal on a single timeframe alone.
Strengths and Limitations of ML in Markets
Machine learning models can detect patterns that human analysis might miss, but they are not infallible. Market regimes change, and a model trained on trending data may underperform in ranging markets. Traders should treat the probability output as one input among several, combining it with price action and risk management for best results.
Multi-Timeframe Functionality
The indicator includes multi-timeframe capabilities, allowing the model to consider data from higher timeframes when generating predictions. This is important because a bullish signal on a 15-minute chart that aligns with a bullish probability on the 4-hour chart carries significantly more weight than a signal on a single timeframe alone.
Strengths and Limitations of ML in Markets
Machine learning models can detect patterns that human analysis might miss, but they are not infallible. Market regimes change, and a model trained on trending data may underperform in ranging markets. Traders should treat the probability output as one input among several, combining it with price action and risk management for best results.
Machine learning based trend shift signals
Machine learning based trend shift signals
This indicator applies logistic regression to predict the probability of price moving up or down. Rather than binary signals, the output is a probability score between 0 and 1, letting traders assess confidence levels before acting on the model's forecast.
This indicator applies logistic regression to predict the probability of price moving up or down. Rather than binary signals, the output is a probability score between 0 and 1, letting traders assess confidence levels before acting on the model's forecast.
Gain Confluence From Probability Scores
The model outputs probability readings that quantify directional likelihood. A reading near 0.8 suggests strong bullish odds, adding statistical weight to trade decisions.
Detect Trends Using Algorithm Analysis
Logistic regression analyzes historical relationships to estimate directional probabilities. Multi-timeframe functionality aligns short-term signals with longer-term forecasts.
Refine Parameters With Historical Data
Traders can evaluate how the model performed across different market conditions. This data-driven feedback helps optimize settings for specific instruments.
Common Questions About ML-Based Price Prediction
Common Questions About ML-Based Price Prediction
Logistic regression applies statistical modeling to predict price direction probabilities. Here are common questions about using machine learning indicators.
Logistic regression applies statistical modeling to predict price direction probabilities. Here are common questions about using machine learning indicators.
What does the probability output actually mean?
A reading of 0.80 suggests the model estimates an 80% probability of an upward move based on historical patterns. The output is not a guarantee but a statistical assessment. Higher readings indicate stronger model confidence.
Why might the model fail in certain market conditions?
ML models learn from historical data. When market conditions change, patterns the model learned may no longer apply. A model trained on trending data often underperforms in ranging markets. Regime awareness is essential.
How does multi-timeframe functionality improve predictions?
The model can consider data from higher timeframes when generating predictions. A bullish signal on a 15-minute chart that aligns with bullish probability on the 4-hour chart carries more weight than a single timeframe signal.
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Web sentiment
Web sentiment
Opinions online about Machine Learning: Logistic Regression are positive, with users appreciating its effectiveness, customization, reliability, and educational value.
Opinions online about Machine Learning: Logistic Regression are positive, with users appreciating its effectiveness, customization, reliability, and educational value.
Source: Online Discussion
Source: Online Discussion
Source: Online Discussion
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TradersList Reviews (3)
TradersList Reviews (3)
TradersList Community has given this listing three stars, indicating decent trust and value for traders' toolkit. Make sure you understand functionality before using.
TradersList Community has given this listing three stars, indicating decent trust and value for traders' toolkit. Make sure you understand functionality before using.
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Source: TradersList Reviews
Source: TradersList Reviews

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✅
Equity Bond Currency Dashboard is a TradingView Indicator that visualizes demand-flow between equities, bonds and currencies across six countries, allowing track of institutional money flows and visuals for interconnected market dynamics.

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by KioseffTrading

Free
TradingView Indicator
Fundamentals Graphing [Kioseff Trading]
🔑
✅
🏅
Fundamentals Graphing [Kioseff Trading] is a TradingView indicator that displays essential fundamental metrics for up to 40 stocks. It allows users to compare various key financial metrics like earnings and revenue for easy benchmarking.

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by Zeiierman

Free
TradingView Indicator
Day/Week/Month Metrics (Zeiierman)
🔑
🌐
✅
Day/Week/Month Metrics (Zeiierman) is a TradingView indicator that computes daily, weekly and monthly performance. This indicator displays edge metrics, depicting how often an asset is likely to be bullish or bearish in a given time period.

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by KioseffTrading

Free
TradingView Indicator
Monte Carlo Simulation - Your Strategy [Kioseff Trading]
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🌐
✅
🏅
Monte Carlo Simulation - Your Strategy by Kioseff Trading is a free TradingView indicator that leverages Monte Carlo simulations to analyze the variability and potential outcomes of your inputted trading strategies or the assets displayed on your chart. Calculate your luck factor using this indicator.

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by KioseffTrading

Free
TradingView Indicator
The Next Pivot [Kioseff Trading]
🔑
🌐
🏅
The Next Pivot [Kioseff Trading] is a TradingView indicator that employs similarity measures to compare historical price sequences with current data, formulating potential paths for future price action.

🤖
by KioseffTrading

Free
TradingView Indicator
(Quartile Vol.; Vol. Aggregation; Range US Bars; Gaps) [Kioseff]
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🏅
The (Quartile Vol.; Vol. Aggregation; Range US Bars; Gaps) [Kioseff] Indicator is a TradingView tool that analyzes price action and volume by breaking volume into aggregated quartiles for noise filtered price and volume analysis.
![TradingView chart interface displaying the Seasonality [TFO] statistics indicator panel showing average asset performance across daily, monthly and quarterly timeframes based on a 252-day trading calendar.](https://framerusercontent.com/images/nvPXFfuC5h7lkcLmxaOhlHbStb8.png?width=4098&height=2304)
🤖
by tradeforopp

Free
TradingView Indicator
Seasonality [TFO]
🔑
🌐
✅
🏅
Seasonality [TFO] is a TradingView indicator that analyzes an asset's average performance across daily, monthly, and quarterly timeframes. It uses a 252-trading day calendar, aggregating daily data into 21-day months and 63-day quarters for gauging seasonal trends.

🤖
by KioseffTrading

Free
TradingView Indicator
Crypto Terminal [Kioseff Trading]
🔑
🌐
🏅
Crypto Terminal [Kioseff Trading] is a TradingView indicator that uses on-chain data to provide real-time cryptocurrency statistics directly on your Tradingview charts.
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Disclaimer
Our goal is to achieve greater transparency, guidance and safety in trading and investing by providing means to discover, research and discuss trading/investing related sites/services.
Content provided on this site is not financial advice, meant for educational purposes only. TradersList does not endorse or guarantee any result for listed sites/services. Do your own research.
Read full disclaimer
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Discover trading edge
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Disclaimer
Our goal is to achieve greater transparency, guidance and safety in trading and investing by providing means to discover, research and discuss trading/investing related sites/services.
Content provided on this site is not financial advice, meant for educational purposes only. TradersList does not endorse or guarantee any result for listed sites/services. Do your own research.
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