//! Machine learning applications in quantitative finance
//!
//! This module provides machine learning models and tools specifically designed for
//! financial applications including pricing, risk management, and portfolio optimization.
//!
//! # Modules
//! - `volatility_forecast`: Volatility prediction models
//! - `portfolio_optim`: ML-enhanced portfolio optimization
//! - `neural_pricing`: Neural network-based derivative pricing

pub mod neural_pricing;
pub mod portfolio_optim;
pub mod volatility_forecast;

// Re-export commonly used items
pub use volatility_forecast::{EWMAModel, GarchModel, HistoricalVolatility, VolatilityForecaster};

// Stub exports (to be implemented)
pub use neural_pricing::NeuralPricer;
pub use portfolio_optim::MLPortfolioOptimizer;

// TODO: Implement common ML utilities for finance
// - Feature engineering for financial time series
// - Market regime detection
// - Anomaly detection for risk management
// - Reinforcement learning for trading strategies
