Stocks & Commodities V. 23:3 (22-26): Backtesting And Edgetesting by Damir Wallener

Stocks & Commodities V. 23:3 (22-26): Backtesting And Edgetesting by Damir Wallener
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Stocks & Commodities V. 23:3 (22-26): Backtesting And Edgetesting by Damir Wallener

Anybody with a computer and an Internet connection can evaluate trading strategies. But how do you judge the validity and significance of the results? Here’s a look at some of the pitfalls awaiting the unwary.

The age of program trading for the masses has arrived. Backtesting — the evaluation of strategies against reams of historical data — is easy to do, but useful, trustworthy advice on the validity and significance of backtesting results remains in relatively short supply. In this article I will walk you through the design process of a simple strategy, and leave it up to you to determine validity and significance.


Most backtesters begin with whole-sample testing. Applying a strategy against a large, contiguous mass of data can give you a quick estimation of what has worked in the past. For example, a simple moving average crossover signal tested against 80 years of historical Dow Jones Industrial Average (DJIA) data shows a 5/8 crossover on daily bars produced a loss of 11,000 points. There is no reason to stop there: Because of the availability of data, it is possible to test several parameters. In Figure 1, you see the results of expanding the test to cover all possible moving average crossover combinations between three and 12.

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