Single Market Factor №3 Maximum Drawdown 

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Single Market Factor №3 Maximum Drawdown

One of the key variables that most traders focus on when considering a system to trade a particular market is referred to as the "maximum drawdown." This value represents the biggest decline in equity from any peak to the subsequent trough. It basically tells you how bad things would have gotten had you started trading at exactly the worst possible time. For example, consider the following scenario: A system trading the Japanese Yen accumulates $15,000 in profits. It then loses $10,000 before gaining another $15,000 in trading profits. In analyzing these results, we would say that the net profit was $20,000 and that the maximum drawdown was $10,000. In other words, if you had started trading at the worst possible moment (just after the first $15,000 in profits had been made), you would have had to sit through—and continue to trade through—a loss of $10,000 before getting back into the black. This is a critical piece of information. If you know there is no way you would continue to keep trading in the face of a $10,000 drawdown, then you should not trade this particular market using this particular approach.

One important attribute of the maximum drawdown value is that it is specific to the trading method that you are using. As a result it provides another useful piece of information in determining how much capital you realistically need in order to trade a given market using the method you have chosen.

One word of warning regarding maximum drawdown analysis: Previous records are made to be broken. Just because the trading method above has so far experienced a maximum drawdown of $10,000, this in no way implies that it will not experience an even larger drawdown in the future. This is especially true if you are analyzing highly optimistic hypothetical results. However, because the future is unknowable we have little choice but to use past results as a proxy for the future. In this case we are at least making some attempt to acknowledge the worst case scenario experienced to date and to factor that into our trading capital requirements.

One Caveat to Analyzing Trading System Results

In chapter Lake of Trading Plane we touched upon the dangers of "over-optimizing" a trading system. If you use enough indicators and filters and data and crunch enough parameter values you can arrive at a system that shows phenomenal results when back-tested over historical data, and that has almost no chance of working in the real world. Just because a given set of indicators and values fit past data well, it does not mean that it will fit future data well. Likewise if you are using the results of a highly curve fit, over-optimized system to determine capital requirements the results are easy to predict—low recommended capital requirements and huge real-time drawdowns far in excess of what was expected.

When developing a trading system it is recommended that you use part of your database to develop the system and then test the system over different data that was not included in the original development process. This is referred to as "out-of-sample" testing. While still not the same as real live trading, testing using out-of-sample data is one way to estimate how your system might perform when you start to trade it with real money. Also, because the trading results are almost always less using out-of-sample data than when using data included in the optimization process, out-of-sample data is much more useful for determining realistic trading capital requirements.

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