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493dc59 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 | # 🧠 AI-Powered Trading Intelligence System
**A complete, modular AI trading system with market prediction, risk modeling, trader behavior analysis, and decision intelligence.**
## Architecture
```
┌─────────────────────────────────────────────────────────────────┐
│ TRADING INTELLIGENCE SYSTEM │
│ │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────────────┐ │
│ │ Feature │ │ Sentiment │ │ Portfolio │ │
│ │ Engine │ │ Engine │ │ Encoder │ │
│ │ (69 feats) │ │ (NLP) │ │ (Positions+Account) │ │
│ └──────┬───────┘ └──────┬───────┘ └──────────┬───────────┘ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌──────────────────────────────┐ ┌─────────────────────────┐ │
│ │ PREDICTION MODEL │ │ RISK MODEL │ │
│ │ (PatchTST + iTransformer) │ │ (Portfolio-aware) │ │
│ │ • Direction probability │ │ • Risk score │ │
│ │ • Expected return │ │ • Position sizing │ │
│ │ • Uncertainty estimation │ │ • SL/TP levels │ │
│ │ • Multi-horizon (1/5/20d) │ │ • Drawdown probs │ │
│ └──────────────┬───────────────┘ └───────────┬─────────────┘ │
│ │ │ │
│ │ ┌───────────────────────┐ │ │
│ │ │ PERSONALIZATION LAYER │ │ │
│ │ │ • Trader profiling │ │ │
│ │ │ • Behavior alerts │ │ │
│ │ │ • Strategy adaptation │ │ │
│ │ └───────────┬───────────┘ │ │
│ │ │ │ │
│ ▼ ▼ ▼ │
│ ┌─────────────────────────────────────────┐ │
│ │ DECISION ENGINE │ │
│ │ BUY / SELL / HOLD + Confidence Score │ │
│ └─────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
```
## Research Foundation
| Paper | Key Contribution | How We Use It |
|-------|-----------------|---------------|
| **PatchTST** (ICLR 2023) | Channel-independent patch-based Transformer | Core architecture: patch embedding, channel-independence |
| **Chronos** (Amazon 2024) | Language model paradigm for time series | Probabilistic prediction heads |
| **Kronos** (2025) | Financial K-line tokenization | OHLCVA candlestick encoding, hierarchical loss |
| **iTransformer** (2024) | Inverted attention across variates | ChannelMixer cross-feature attention |
| **FinMultiTime** (2025) | Multi-modal financial dataset | Multi-modal fusion design |
## 5 Components
1. **Feature Engine** - 69 features: price, technical indicators (RSI, MACD, ATR, EMA, Bollinger), volatility (Garman-Klass, Parkinson), volume (OBV, VWAP, MFI), market regime detection
2. **Prediction Model** - PatchTST-based Transformer with multi-task heads for direction, return, and uncertainty
3. **Risk Model** - Portfolio-aware with position encoding, behavior analysis, VaR estimation
4. **Personalization** - Trader profiling (5 archetypes), behavior alerts (overtrading, revenge trading)
5. **Decision Engine** - Combines all signals into BUY/SELL/HOLD with confidence scores
## Quick Start
```python
from trading_intelligence.feature_engine import FeatureEngine
from trading_intelligence.prediction_model import TradingTransformer
from trading_intelligence.decision_engine import DecisionEngine
# Compute features
fe = FeatureEngine(lookback_window=60, prediction_horizons=[1, 5, 20])
features = fe.compute_all_features(ohlcv_df)
# Create model
model = TradingTransformer(num_channels=69, seq_len=60, d_model=128, n_heads=8, n_layers=3)
# Get decision
engine = DecisionEngine(prediction_model=model)
decision = engine.make_decision(features, current_atr=0.015)
print(decision.signal) # BUY / SELL / HOLD
```
## Evaluation Metrics
| Metric | 1-Day | 5-Day | 20-Day |
|--------|-------|-------|--------|
| Direction Accuracy | 50.2% | 47.8% | 46.4% |
| Information Coefficient | -0.07 | 0.01 | 0.36 |
| Sharpe Ratio | -0.18 | 0.53 | -1.69 |
| Profit Factor | 0.97 | 1.09 | 0.80 |
## Training
- Multi-task loss: BCE (direction) + Gaussian NLL (returns) + Sharpe penalty (risk)
- Uncertainty-weighted task combination (Kendall et al. 2018)
- Walk-forward temporal split (no look-ahead bias)
- CosineAnnealing LR schedule with warm restarts
## Disclaimer
For research and educational purposes only. Not financial advice.
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