Run 10,000+ simulations to test your trading strategy robustness with advanced probability analysis and risk modeling.
Monte Carlo simulation reveals that a 60% win rate with 1.5:1 reward-to-risk ratio has a 78% probability of positive returns over 100 trades.
Example: A trader with 60% win rate, $150 average win, $100 average loss, and 2% risk per trade on a $100K account has a 78% chance of profit and 15% chance of 20%+ returns.
Configure your strategy parameters and click "Run Monte Carlo Simulation" to see detailed probability analysis.
Input win rate, average win/loss amounts, risk per trade, and number of trades to simulate
The simulator creates thousands of random trading sequences based on your statistical parameters
Each simulation tracks final balance, maximum drawdown, and return percentage
Results show probability of success, risk metrics, and potential return ranges
A:Monte Carlo simulation runs thousands of random trading scenarios to test strategy robustness, helping traders understand probability distributions of potential outcomes and risk levels.
A:Our calculator runs 10,000+ simulations for statistically significant results. More simulations provide better accuracy but require more processing time.
A:Probability of success shows the percentage of simulated scenarios where you achieve your profit target without hitting drawdown limits, based on your trading parameters.
A:Maximum drawdown shows the worst-case loss scenario, while Value at Risk (VaR) indicates potential losses at different confidence levels (95%, 99%).
A:Yes, the Monte Carlo simulator works with any trading strategy. Input your win rate, average win/loss, and risk parameters to test strategy viability.
A:Backtesting uses historical data, while Monte Carlo simulation generates random scenarios based on your statistical parameters, providing broader risk assessment.