How To: Monte Carlo Simulation

https://quantpad.ai/waitlist Your backtest is just one realization of a stochastic process. Trade ordering matters, and the exact same distribution of returns can produce wildly different equity curves depending on the sequence. That's path dependence, and it's why your "profitable" backtest fell apart live. In this video, I break down three methods of Monte Carlo simulation that every serious trader should be using before risking real capital: basic reshuffling, regime-switching, and parametric Monte Carlo. I show you exactly how each works, when to use them, and when they break down, including how to build transition matrices for regime-aware resampling and why a single backtest should never be your basis for deploying a strategy. If you can't distinguish your strategy from a random, edgeless process with 90% confidence, you don't have a strategy. You have a coin flip with extra steps. 🔬 Topics covered: path dependence, stochastic processes, Monte Carlo resampling with replacement, regime-switching models, transition matrices, parametric distribution fitting, confidence intervals, risk of ruin, drawdown distributions, and prop firm account modeling. --- 0:00 Why Backtests Fall Apart Live 0:31 Path Dependence Explained 1:10 The 3 Monte Carlo Methods 1:41 Why Monte Carlo Matters 2:13 Reshuffling Monte Carlo 4:15 Regime-Switching Monte Carlo 9:08 Parametric Monte Carlo 11:03 Why One Backtest Is Never Enough 12:15 Monte Carlo for Prop Firms 12:59 Full Recap 14:02 Why Serious Traders Need This #montecarlo #trading #backtesting #quantitativetrading #pathdependence #riskmanagement #algotrading #tradingstrategy #regimeswitching #expectedvalue #montecarlomethods #propfirm #tradingmath #retailtrading #equitycurve