What Is a Monte Carlo Simulation? Why Can a Positive-Expectancy Strategy Still Lose Consecutively?
In cryptocurrency trading, even if a strategy has been backtested and has a positive expected return, that doesn’t mean it will perform smoothly in live trading. A string of losses or a maximum drawdown greater than expected could cause a trader to abandon an otherwise effective strategy too soon. A Monte Carlo simulation is one way to help us study these risks.
First, what is a Monte Carlo simulation?
It generates a large number of possible trading outcomes and examines the distribution of returns, the number of consecutive losses, and the maximum drawdown under different scenarios. For example, repeatedly shuffling the profit and loss results of historical trades lets us see how the equity curve might change when the same trades occur in a different order.
Second, why can a positive expectancy still come with consecutive losses?
Expected return describes the long-term average outcome; it doesn’t determine the result of the next trade. Suppose a strategy has a 50% win rate. Five consecutive losses are still entirely possible. If the position size is too large, a string of losses could lead to a severe drawdown or even trigger liquidation.
Third, what can a simulation tell us?
Traders can examine the maximum drawdown, the longest losing streak, and the likelihood of the account falling below a risk threshold across different simulated paths. This can help them assess whether their current position sizes are too aggressive.
Fourth, what should we keep in mind?
Simulation results depend on the input data and assumptions. Randomly shuffling historical trades cannot fully account for changes in market conditions, correlations between trade outcomes, wider slippage, or sudden drops in liquidity. So simulations can’t guarantee future results or replace an assessment of real trading costs.
Good risk management means asking not only how much a strategy can earn on average, but also: if results turn against me for a while, can my account withstand it?
Coming next: What Is the Sharpe Ratio? Why Isn’t a Strategy With Higher Returns Necessarily the Better Choice?
In cryptocurrency trading, even if a strategy has been backtested and has a positive expected return, that doesn’t mean it will perform smoothly in live trading. A string of losses or a maximum drawdown greater than expected could cause a trader to abandon an otherwise effective strategy too soon. A Monte Carlo simulation is one way to help us study these risks.
First, what is a Monte Carlo simulation?
It generates a large number of possible trading outcomes and examines the distribution of returns, the number of consecutive losses, and the maximum drawdown under different scenarios. For example, repeatedly shuffling the profit and loss results of historical trades lets us see how the equity curve might change when the same trades occur in a different order.
Second, why can a positive expectancy still come with consecutive losses?
Expected return describes the long-term average outcome; it doesn’t determine the result of the next trade. Suppose a strategy has a 50% win rate. Five consecutive losses are still entirely possible. If the position size is too large, a string of losses could lead to a severe drawdown or even trigger liquidation.
Third, what can a simulation tell us?
Traders can examine the maximum drawdown, the longest losing streak, and the likelihood of the account falling below a risk threshold across different simulated paths. This can help them assess whether their current position sizes are too aggressive.
Fourth, what should we keep in mind?
Simulation results depend on the input data and assumptions. Randomly shuffling historical trades cannot fully account for changes in market conditions, correlations between trade outcomes, wider slippage, or sudden drops in liquidity. So simulations can’t guarantee future results or replace an assessment of real trading costs.
Good risk management means asking not only how much a strategy can earn on average, but also: if results turn against me for a while, can my account withstand it?
Coming next: What Is the Sharpe Ratio? Why Isn’t a Strategy With Higher Returns Necessarily the Better Choice?