AI for Finance

• Time series forecasting: ARIMA, exponential smoothing, Prophet, neural approaches (LSTM, Temporal Fusion Transformer, PatchTST)
• Algorithmic trading: signal generation, execution algorithms (TWAP, VWAP), market microstructure
• Portfolio optimisation: mean-variance (Markowitz), Black-Litterman, RL-based portfolio management
• Risk modelling: Value at Risk (VaR), Expected Shortfall, Monte Carlo simulation, credit scoring
• Fraud detection: anomaly detection, graph-based approaches, real-time streaming
• NLP in finance: sentiment analysis of news/earnings calls, financial document understanding
• Alternative data: satellite imagery, social media, web scraping
• Regulatory and ethical: model explainability (SHAP, LIME), fairness in credit, regulatory compliance