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One way of reducing a system's drawdown and improving its performance is to
use money management techniques. Using HistoryMakerTM, Money Management techniques can be tested independently of trade entry
rules. Successful techniques can be found by using a random entry and testing performance over many trials. Using synthetic data
here means that valuable actual historical data are not wasted
at 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 when it was optimised. This results in it either never raising signals or raising many
signals in error
The conclusion is that by testing the system with synthetic data, a money management strategy can be
found 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. |
