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Money Management
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One way of reducing a system's drawdown and improve its overall performance is to employ money management techniques. Using HistoryMaker, Money Management techniques can be tested independently of the trade entry method.
Successful techniques can be found by implementation of a random entry signal and testing performance over many trials. Using synthetic data in this instance means that valuable actual historical data are not wasted on this phase of system development. By 'wasting' data we mean that the already limited historical data that are available should be used sparingly to avoid curve-fitting.
Curve-fitting results when the optimum system parameters are determined on too little data and the system when actually traded never experiences the same market conditions as existed when it was optimised. This results in it either never raising signals or raising many inappropriate signals rendering it unprofitable.
The conclusion is that by testing the system with synthetic data, a money management strategy can be determined without fear of creating a system that has its money management rules tied to entry rules and, furthermore, it is not curve-fit to historical data.
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