7 POWERFUL Artificial Intelligence Indicators on TradingView ( SAVE THEM )

Introduction

This tutorial provides a comprehensive overview of seven powerful artificial intelligence indicators available on TradingView. These indicators are designed to enhance your trading strategy by leveraging machine learning technology to deliver accurate market predictions. By understanding and utilizing these tools, you can improve your winning ratio and make more informed trading decisions.

Step 1: Implement Machine Learning Multiple Logistic Regression

• Overview: This indicator uses various technical indicators as input variables to predict market outcomes.
• Key Features:
  • Normalizes indicators like RSI, CCI, DMI, and others for consistency.
  • Outputs values closer to one for bullish signals and closer to zero for bearish signals.
• Customization Tips:
  • Set the Z-score length to 100 for fewer but more accurate signals.
  • Stick with default input variables for optimal performance.
• Practical Use:
  • Ignore signals with low momentum scores to enhance trade quality.

Step 2: Utilize AI Adaptive Money Flow Index

• Overview: This indicator combines traditional money flow index analysis with advanced clustering techniques.
• Key Features:
  • Adapts to market conditions better than conventional indicators.
  • Dynamically adjusts overbought and oversold levels.
• Practical Use:
  • Use it for nuanced market trend analysis and volume insights.

Step 3: Apply Machine Learning VWAP

• Overview: This indicator uses machine learning to identify optimal anchor points for the volume-weighted average price (VWAP).
• Key Features:
  • Acts as a trend identifier based on price position relative to the VWAP.
  • Provides entry signals for long and short trades.
• Trading Strategy:
  • Long Trade:
    1. Ensure the VWAP color is green.
    2. Confirm a pullback to the basis line.
    3. Look for a green triangle below the candle bar.
  • Set a stop loss at the lower VWAP band and target profits at the upper band.

Step 4: Explore Simple Neural Network Transformed RSI

• Overview: A modified version of the traditional RSI that uses neural network smoothing.
• Key Features:
  • Effective for low time frame trading, reducing market noise.
  • Offers customization in visualization options.
• Customization Tips:
  • Adjust the NNT smoothing length and standard deviation for optimal performance.

Step 5: Implement Volume Super Trend AI

• Overview: This advanced indicator combines traditional Super Trend calculations with AI techniques.
• Key Features:
  • Uses K Nearest Neighbors (KNN) to analyze historical data for price trend predictions.
• Trading Strategy:
  • Buy when:
    1. The channel is ascending.
    2. The super trend AI gives a buy signal.
  • Use the super trend line as a trailing stop-loss.

Step 6: Use Machine Learning Optimal RSI

• Overview: An advanced RSI that calculates optimal lengths for improved accuracy.
• Key Features:
  • Determines the most profitable RSI lengths through machine learning.
• Trading Strategy:
  • Look for RSI to be oversold before a bullish cross or overbought before a bearish cross for valid trade signals.

Step 7: Implement Machine Learning Lorenzian Classification

• Overview: A complex machine learning algorithm that provides valuable trading signals.
• Key Features:
  • Highly rated by traders for its effectiveness.
• Trading Strategy:
  • Enable EM and ADX filters for high-quality signals.
  • Open trades based on buy alerts and close when the candlestick closes below the moving average.

Conclusion

Incorporating these seven powerful artificial intelligence indicators can significantly enhance your trading strategy on TradingView. Each indicator offers unique features and customizable options that cater to different trading styles and market conditions. Experiment with these tools, combine them with your existing strategies, and continually refine your approach to improve your trading outcomes. Happy trading!