Infinity Algo AI System Disclosure

Purpose and Function of the AI System

The "AI Clustering" feature in Infinity Algo is an optimization algorithm, not a predictive one. Its purpose is to help traders adapt to changing market conditions by analyzing recent historical data to find which indicator settings would have performed most effectively in the immediate past.

It functions as an automated strategy tester that runs in the background of your TradingView chart. The system does not engage in "self-learning" or evolve on its own; it simply performs a new, isolated analysis during each cycle.

How the AI System Works

When the "AI Clustering" feature is enabled, the indicator performs the following steps periodically. This recalculation is triggered once every `X` bars, based on the "AI Update Frequency" setting you control (default is 50 bars).

1. Parameter Simulation: The system simulates hundreds of trading strategies by testing different combinations of core indicator settings against recent historical price data (by default, the last 500 bars). The parameters tested include:
   • Sensitivity: Testing periods within user-selected ranges (e.g., "Fast (10-14)", "Balanced (10-20)", etc.).
   • Upper/Lower Thresholds: Testing a predefined set of values for buy and sell thresholds (e.g., Upper: `[66, 68, 70, 74, 76]`, Lower: `[26, 28, 30, 34, 36]`).
2. Performance Scoring: Each simulated combination is scored based on a user-selected performance metric. This allows you to define what "best" means for your trading style. The available metrics are:
   • Profit Factor * Sqrt(Trades)
   • Average Profit
   • Win Rate
   • Total Profit
   • Profit Factor
3. Optimal Configuration Selection: The system identifies the single combination of settings that achieved the highest score on the chosen performance metric over the recent historical data.
4. Signal Adaptation: The indicator then uses this "optimal" configuration to generate the "AI" Buy and Sell signals on your live chart until the next recalculation cycle.

The AI Dashboard on the chart displays the settings that the system has currently identified as optimal. Because this entire process runs locally within TradingView's environment, complex simulations (e.g., low "AI Update Frequency") can increase chart redraw times or cause indicator timeouts. We recommend using this feature on timeframes of 15 minutes or higher for a smoother experience.

Training Data

The AI system does not use external or private data sets. The "training data" consists solely of the historical OHLCV (Open, High, Low, Close, Volume) market data available directly on the user's TradingView chart, typically from the last 500 bars.

Crucially, all computations occur locally in your TradingView environment—no data is ever sent to Infinity Algo servers or any external "black box" model. The system analyzes historical data to find patterns that can inform the optimal indicator settings. No personal user data is ever accessed or used in this process.

Limitations and Risks

It is crucial for users to understand the limitations of this AI system:

Historical Limitation (Past ≠ Future)

• The system's recommendations are based entirely on what would have worked in the past. Past performance is not an indicator or guarantee of future results, and there is no guarantee that the selected "optimal" settings will be profitable in live market conditions.

Non-Predictive Nature

• The AI does not predict future price movements. It is a reactive tool that optimizes settings based on historical analysis. It is not a "self-learning" or continuously evolving model.

Curve-Fitting Dangers

• As with any backtesting, there is a risk that the settings identified as "optimal" are simply "curve-fitted" to past data and may not perform well in the future.

Exclusion of Real-World Costs

• Because the AI's backtests are simulations, they do not include factors like exchange fees, slippage, or network latency. Live trading results may differ materially from the simulated outcomes.

The AI system is a tool for analysis and decision-support, not a replacement for proper risk management and independent judgment. All trading decisions and their outcomes are the sole responsibility of the user. For a full breakdown of risks, please see our Disclaimer.

Recommended Best Practices

To use the AI Clustering feature effectively, we recommend the following risk control measures:

• Validate on a Demo Account: Always test the AI-optimized settings on a paper trading or demo account before deploying them with live capital.
• Use Independent Risk Management: Continue to use standard risk management tools, such as stop-loss orders and appropriate position sizing, regardless of how "optimal" the AI settings appear.
• Re-evaluate Periodically: Market conditions change. Periodically re-evaluate the AI's settings and the lookback window to ensure outdated data is not biasing the results, especially after major market events.

Bias Mitigation and Technical Details

Bias: Because the AI optimizer only evaluates parameter combinations against objective, mathematical performance metrics (e.g., Profit Factor, Win Rate), it is not subject to the demographic, social, or cognitive biases that can affect human-labeled data sets.

Data Integrity: The accuracy of the AI's output depends on the quality of the data feed from TradingView. Data irregularities, such as historical corrections or missing bars, may affect the optimizer's outcomes.

Pine Script Version: The AI Clustering feature is implemented in Pine Script v5. Please ensure your TradingView chart environment is up to date to avoid potential compatibility issues.

Contact

If you have any questions about our AI system, please contact us at [email protected].