How to Reverse Engineer a Closed Source TradingView Indicator with AI (IT WORKS)

How to Reconstruct TradingView Indicators Using AI

Introduction to Indicator Reconstruction

• The speaker introduces a method for reconstructing TradingView indicators without access to their code, utilizing AI and smart prompting.

• Emphasizes the importance of having the indicator's code for creating automated trading strategies and evaluating their performance metrics (KPIs).

• Encourages viewers to watch the entire video for valuable insights and tips on this process.

Overview of Indicators Discussed

• Lists the indicators being reconstructed: Money Line, Ann's Ribbons, and MOST indicator.

• Mentions that these are type three indicators with no trading alerts or accessible code, addressing viewer requests for solutions.

Steps to Reconstruct an Indicator

Preparing Your Chart

• Advises cleaning up the chart by displaying only the desired indicator for clarity during reconstruction.

• Suggests creating a new layout in TradingView specifically for this purpose.

Adjusting Indicator Settings

• Instructs users to modify settings so that only relevant lines are visible, eliminating unnecessary data that could confuse AI processing.

Exporting Data from TradingView

• Stresses the need to load sufficient historical data before exporting it, ensuring comprehensive information is available for AI analysis.

• Explains what exported data includes (timestamp, open, high, low, close), emphasizing its relevance in reconstructing indicators.

Utilizing AI for Reconstruction

Crafting Prompts for AI

• Introduces a specific prompt format tailored for reconstructing indicators based on exported CSV data.

Choosing an AI Model

• Recommends using Claude.ai as a powerful tool and suggests starting with Sonnet 4.5 due to token limitations before switching to Opus 4.1 if necessary.

Practical Example: Money Line Indicator

Reconstruction Process

• Describes how after receiving Pine Script code from AI, users can implement it in TradingView’s Pine editor.

Verification of Results

• Confirms successful reconstruction by comparing original and recreated indicators visually on TradingView.

Additional Examples: Ann's Ribbons & MOST Indicator

Ann's Ribbons Reconstruction

• Highlights challenges faced due to lack of source code but emphasizes potential benefits once reconstructed.

MOST Indicator Challenges

• Discusses issues encountered previously with this indicator and reiterates its importance in understanding KPIs before trading decisions.

Performance Comparison of Indicators

Evaluating Strategies

• Compares performance metrics across all reconstructed strategies starting from January 1st, 2018:

• Money Line: 1,100% profit with 46% max drawdown.

• Ann's Ribbons: Higher profit at 1,700%, but increased drawdown at 57%.

• MOST: Lower performance at 836% profit with a drawdown of 54%.

Conclusion on Strategy Effectiveness

Importance of KPIs

• Reinforces that understanding KPIs is crucial when evaluating any trading strategy or indicator’s effectiveness over time.

Limitations & Considerations

Conditions for Successful Reconstruction

• Outlines prerequisites such as needing access to the indicator on TradingView and having a premium subscription to export data effectively.

This structured approach provides clear guidance through each step involved in reconstructing TradingView indicators while highlighting key insights about their performance evaluation.