Monte Carlo

Monte Carlo simulation is a powerful testing technique that can be used to predetermine the limits of likely future system performance. It is particularly useful for testing non-linear payoffs like those found in mechanical trading systems. HistoryMakerTM is able to generate price data over any date range, past and future. So a Monte Carlo simulation of trading system performance can be obtained as unlimited price path scenarios may be generated and tested against.

The ability to create new data takes walk-forward system testing to a new level; a system can be literally "walked" into the future!

A Monte Carlo simulation involves using today’s price as a seed, then creating many possible future scenarios. These scenarios are then traded by the system under test and appropriate performance measures are made for each scenario. The estimated future result is then determined by calculating the expected value and variance of each performance measure after performing numerous simulations.

The following diagram illustrates the process involved in using generated scenarios to test a trading system's likely future performance.




Scenario:

Generated by HistoryMaker

Result:

Examples;

Annual return (%)
Risk Adjusted Returns
Winning Trades (%)
Average Winning trade / Average Losing Trade ($/$)
Maximum Drawdown ($)
Volatility of returns (%)

Consolidated Result:

For example take the Average, Standard Deviation Minumum or maximum of the individual results.