High-Frequency Trading Strategy Performance Simulation Framework

Create a sophisticated Monte Carlo simulation framework for evaluating high-frequency trading strategies, incorporating realistic market microstructure, transaction costs, and latency models. Design a modular Python script that can generate synthetic market data, backtest multiple trading algorithms simultaneously, and produce statistically rigorous performance metrics including Sharpe ratio, maximum drawdown, and strategy robustness under different market regimes.