indicator-analysis

name	indicator_analysis
description	Audits indicators, removes contradictions, and simplifies signals to a small coherent set

When to Use

• When trade accuracy is low due to contradictory or noisy indicators
• When simplifying strategies to 3–4 core signals (EMA, RSI, MACD, optional Bollinger Bands)
• When you need comparable confidence scoring across modules

Instructions

1. Identify active indicators and hard gates in:
   • modules/momentum.py
   • modules/mean_reversion.py
   • modules/ai_predictor.py
2. Reduce decision inputs to a coherent set:
   • Trend: EMA spread (fast vs slow)
   • Momentum: MACD histogram
   • Mean reversion: Bollinger Bands + RSI (only when trend is weak)
   • Volatility: ATR (risk sizing / SL/TP)
   • Deep Learning: GRU model in prediction/predict.py consumes raw OHLCV sequences
3. Ensure indicators are computed consistently using shared utilities:
   • utils/indicators.py
4. Preserve module output contract:
   • {"signal": "BUY|SELL|HOLD", "confidence": float, "metadata": dict}