I've often seen comments in Forex forums something like this: "I'm not looking for a gold mine -- just a system that makes 10 pips per day". So let's take this 'modest' requirement to its conclusion with some back-of-the-envelope calculations. Come on, admit it, you've done something similar -- I have. In order to buy 1 lot of EURUSD at 200:1 leverage I have to supply $100,000/200 = $500 of margin from my account. 10 pips = $100 profit @ 1 lot. Hey, wait a minute! [scribble, scribble], that means that I can make $100 * 5 days a week * 50 weeks = $25,000 per year or 5,000%, all from a $500 investment!!!! And if I increase the investment over time to 10 lots, I could … I can …….... eyes glaze over, images of palm trees on a tropical beach drift into view.
Past performance is not necessarily indicative of future results
The hard cold reality, of course, is risk, manifested as drawdown. Focusing only on the profitability of a system ignores this critical financial and psychological element, like agreeing to a major medical procedure without knowing how often it has been successful.
Historical, backtested risk is not difficult to calculate. Conversely, obtaining a useful estimate of future risk is (or should be) the single most challenging and elusive task that faces a trading system developer. Here are some ways in which I attempt to assess future risk
- The simplest assessment of risk is a reward:risk ratio calculated from (total profit)/(maximum drawdown). The MetaTrader 4 Strategy Tester reports individually on these, and it's a real pity that it cannot optimise on the combination.
- When people visually assess the smoothness of a backtesting equity curve, they are in effect trying to assess future risk. Calculating the smoothness of equity curves is again absent from the MetaTrader 4 Strategy Tester. That's why I wrote an Extended Strategy Reporter, which among other parameters calculates the Sharpe Ratio and modified Sharpe Ratio, both of which provide a numerical indication of smoothness.
- Once an optimised set of parameters has been found, it is important to verify that these are part of a "rounded hill" of generally low risk values. A set of parameters that has no neighbors is almost certain to be curve-fitted.