Top 3 BEST AI Trading Indicators on TradingView

Summary

This video introduces three AI-powered indicators on TradingView that utilize machine learning to adapt to real-time market conditions. Unlike traditional indicators that rely on fixed rules, these tools use logistic regression, kernel density estimation, and probabilistic modeling to track support/resistance, momentum, and volume pressure. The video explains how these indicators dynamically adjust, offering more accurate signals by filtering noise and validating levels based on statistical probability. Viewers are shown how to combine these tools for a smarter, adaptive trading system, with all indicators available for free.

Takeaways

• 😀 AI-driven indicators use machine learning to track real-time market behavior, adapting to current conditions instead of relying on historical data.
• 📊 Logistic Regression is used in the support and resistance indicator to dynamically rank levels based on real-time price action and statistical confidence.
• 🔄 The support and resistance model continuously reevaluates levels, adding or removing them based on live price behavior, with customizable thresholds for confidence.
• 📈 The Kernel Optimized RSI replaces traditional overbought/oversold thresholds, using Kernel Density Estimation (KDE) to identify RSI levels that historically led to market reversals.
• 💡 Instead of guessing overbought or oversold conditions, the RSI model provides live probability signals based on past market behavior.
• 🔋 The Supertrend indicator is enhanced with KDE to confirm breakout signals with real volume, filtering out weak moves and ensuring trend changes are backed by real conviction.
• 📉 The volume-optimized Supertrend only flips when the breakout has statistical volume backing it, filtering out false signals.
• 🔧 The system allows full customization of parameters, including sensitivity, bandwidth, and display styles for all three indicators.
• 🧠 The combined use of these indicators offers a full adaptive system, integrating support, resistance, momentum, and volume to filter noise and improve decision-making.
• 🌐 These machine learning-driven indicators operate inside TradingView, providing algorithmic trading strategies to everyday traders without the need for black-box bots.
• 💥 All three AI-driven indicators are free to use and available on TradingView, offering powerful tools for sharper market analysis and smarter entry/exit decisions.

Q & A

What makes these AI-driven indicators different from traditional indicators?

Traditional indicators rely on fixed rules such as moving averages or support/resistance levels based on past data. These AI-driven indicators, on the other hand, use machine learning to track real-time market behavior, adjusting to structure, momentum, and volume pressure.

How does the Support and Resistance Logistic Regression model work?

This model uses logistic regression to track pivot highs and lows, then logs key statistics like RSI, candle size, and how many times price has respected the level. It calculates the probability of price reacting to that level again, and only plots levels with high confidence, constantly updating in real-time.

Why is the traditional RSI method insufficient in live markets?

Traditional RSI indicators rely on fixed thresholds (like 70 for overbought and 30 for oversold), which doesn't account for the fact that price can stay overbought or oversold for extended periods, or reverse before hitting those thresholds. The AI-driven RSI uses Kernel Density Estimation to assess statistically significant RSI levels that have historically led to market pivots.

What is Kernel Density Estimation (KDE) and how is it applied in the indicators?

Kernel Density Estimation is a statistical technique used to estimate the probability distribution of a dataset. In these indicators, it models the likelihood of a reversal based on past RSI values that led to pivots. This allows the system to dynamically assess whether an RSI reading is significant for a potential market reversal.

How does the Supertrend model differ from traditional Supertrend indicators?

Traditional Supertrend indicators flip when price crosses a certain threshold, but this can be unreliable in low-volume or choppy markets. The AI Supertrend incorporates volume data, using KDE to assess the strength of volume behind price moves. If the volume doesn't meet a statistical threshold, the trend doesn't flip, reducing false signals.

What is the advantage of using these AI tools in trading?

These AI tools are adaptive, continuously evaluating market conditions in real-time, and they filter out noise. Instead of relying on static rules or arbitrary thresholds, they use machine learning to track market structure, momentum, and volume, providing more accurate and context-aware signals for traders.

How do the indicators combine to create a full trading system?

When used together, the indicators form a complete system: the Support and Resistance model sets the structural context, the Kernel Optimized RSI provides momentum signals based on historical data, and the Supertrend with volume confirmation ensures that trend changes are valid and backed by real volume. This multi-stage process helps filter out noise and increases the reliability of trading signals.

Can you adjust the sensitivity of the indicators?

Yes, each indicator offers customization options. You can adjust settings like the retest count and probability threshold for the Support and Resistance model, kernel type and bandwidth for the RSI, and sensitivity and volume confirmation for the Supertrend, giving you full control over the behavior of the system.

How does the AI model handle false signals or noise in the market?

The AI models are designed to filter out noise by asking key questions about each potential signal: Is the level valid? Is the momentum meaningful? Is the volume sufficient for confirmation? By continuously evaluating these factors in real-time, the models ensure that only statistically significant signals are acted upon.

What are the benefits of using these AI indicators in TradingView?

These AI indicators run natively in TradingView, allowing you to take advantage of advanced machine learning models without needing external bots or complex setups. They offer real-time learning, are fully customizable, and are available for free, making them accessible to all traders on the platform.