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.
THE FIRST STEP
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.