Signal Settings

Overview#

The Signal Settings for Lune Aegis let you control the generation and behavior of trade entry signals. These settings provide a high degree of customization. You can fine-tune the strategy's responsiveness using an AI-driven engine. By configuring the analysis windows and adjusting sensitivity, you can tailor the signal logic to fit your trading style and the market you are analyzing.

Signal Generation Logic#

To protect our proprietary algorithms, the exact mechanics of the signal logic are not disclosed. You can understand the conceptual approach as follows:

Lune Aegis uses a multi-dimensional AI model to identify trading opportunities. The strategy analyzes a range of market characteristics, such as price momentum, volatility, and market efficiency, across multiple time horizons. It then classifies the market into distinct regimes (e.g., trending, ranging, high volatility) to better understand the current environment.

The AI calculates a composite signal score based on the agreement of these factors. This score is then adjusted based on the identified market regime and recent strategy performance, so the model can adapt to changing conditions. All signals are confirmed on the close of a price bar so they do not repaint.

Settings#

The following settings control the core logic of the signal engine.

General Settings#

Setting	Description
Long Trades	Enables or disables the generation of long (buy) signals.
Short Trades	Enables or disables the generation of short (sell) signals.

AI & Sensitivity#

These settings define how the AI analyzes the market and its overall responsiveness.

Setting	Description	Range / Recommended
Signal Sensitivity	Controls the overall responsiveness and frequency of signals. Lower values are more sensitive and produce more signals, while higher values provide stronger filtering for fewer, higher-quality signals.	Range: 0.1 - 5.0Recommended: 1.0 - 3.0
Signal Confidence Threshold	The minimum required signal confidence for a trade entry. A higher value requires stronger confirmation from the AI before a signal is generated.	Range: 0.01 - 0.99Recommended: 0.6 - 0.8
Learning Rate	Controls how quickly the AI model adapts to new market data. Lower values result in slower, more stable adaptation.	Range: 0.01 - 0.20Recommended: 0.03 - 0.10
Analysis Lookback Window	Sets the size of the sliding data window the AI model uses for its analysis. A shorter window adapts faster to recent market changes.	Range: 5 - 2000Recommended: 300 - 800
Regime Detection Lookback	Sets the lookback window for market regime analysis and classification. A lower value is more responsive to regime changes.	Range: 5 - 2000Recommended: 30 - 100
Volatility Lookback	Sets the lookback window for volatility calculations and analysis. A lower value is more responsive to short-term volatility changes.	Range: 5 - 2000Recommended: 15 - 50

Best Practices & Usage#

• Balance Sensitivity and Confirmation: Lowering Signal Sensitivity will generate more signals but may also increase the number of false positives. Higher values provide stronger confirmation but may result in fewer trading opportunities. Find a balance that suits your risk tolerance.
• Adjust Lookbacks for Your Timeframe: If you are trading on a lower timeframe, consider using shorter Lookback periods to make the strategy more responsive. For higher timeframes, longer Lookback periods can provide more stable and reliable signals.
• Start with Recommended Values: The recommended values provide a solid starting point for most markets. Use them as a baseline, then carefully adjust them based on the asset and timeframe you are trading.
• Tune One Thing at a Time: When optimizing the settings, adjust only one parameter at a time. This helps you clearly understand the effect of each change on the strategy's performance during backtesting.