Signal Settings

Overview

The Signal Settings for Lune Aegis allow you to control the generation and behavior of trade entry signals. These settings provide a high degree of customization, letting you fine-tune the strategy’s responsiveness by leveraging an advanced, AI-driven engine. By configuring the analysis windows and adjusting sensitivity, you can tailor the signal logic to fit your specific 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. However, the conceptual approach can be understood as follows:

Lune Aegis uses a sophisticated, multi-dimensional AI model to identify trading opportunities. The strategy analyzes a wide 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 different factors. This score is then adjusted based on the identified market regime and recent strategy performance, allowing the model to adapt to changing conditions. This adaptive approach ensures the signal logic remains effective and relevant. All signals are confirmed on the close of a price bar to ensure 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 - 5.0 Recommended: 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 - 0.99 Recommended: 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 - 0.20 Recommended: 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 - 2000 Recommended: 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 - 2000 Recommended: 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 - 2000 Recommended: 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 and then carefully adjust them based on the specific asset and timeframe you are trading.

• Tune One Thing at a Time: When optimizing the settings, adjust only one parameter at a time. This will help you clearly understand the effect of each change on the strategy's performance during backtesting.