Monte Carlo Simulation for Trading Strategy
It's early morning. Your algorithm just captured a move on ES futures while you were still asleep. But when you review your backtest results, you see a ...
Monte Carlo simulation trading is an essential topic for every trader looking to improve their futures trading. It's early morning. Your algorithm just captured a move on ES futures while you were still asleep. But when you review your backtest results, you see a 25% maximum drawdown—a figure that seems manageable. Then you run a Monte Carlo simulation and discover that in 15% of scenarios, your drawdown exceeded 50%. This gap between backtest confidence and reality is the critical problem Monte Carlo simulations solve. Monte Carlo simulation trading transforms your strategy validation from a single-point exercise into a probabilistic assessment. It reveals what your strategy might deliver under a range of possible market conditions, not just one historical path. This approach is essential for serious traders who want to move beyond the false precision of traditional backtesting. Moreover, traditional backtesting has a fundamental flaw: it tells you how your strategy performed in one specific historical scenario. This creates several problems that Monte Carlo simulations directly address. For example, first, there is the sequence dependency problem.