Hypothesis testing is an instrument in the financial market trader's toolbox to help guide investment strategy by statistical means.
The use of charts and historical data is commonplace, but the use of statistical mathematics is rare among private investors.
What is hypothesis testing?
Hypothesis testing is a statistical test (sometimes called a backtest) that uses data gathered from a small sample group to make assumptions about a much larger population – sometimes an entire country.
The test starts with an observation – the "null hypothesis". Results gathered during and after testing will continue to support the null hypothesis until there is sufficient data to support an "alternative hypothesis".
An automated trading strategy generates a number of profitable trades with returns greater than 10%.
The trader establishes the null hypothesis, that over the long run similar results cannot be regularly repeated.
For the test, the same conditions are simulated using data that recreates historical prices, trading conditions – such as volatility and mean returns. The same trading strategy is then applied to this simulation and repeated 10,000 times.
If the trader finds that only 100 of the 10,000 results (1%) produces returns equal to or greater than the original trading strategy, the null hypothesis must be supported with a 99% probability.
If 5,000 of the results produced returns equal to or greater than the original strategy, the trader can accept the alternative hypothesis with a probability of 50%.
Who uses hypothesis testing?
This methodology is used in the finance industry, mainly by quantitative (quant) investment professionals.
Quant traders use many different mathematical models and data analysis to identify trading opportunities – of which hypothesis testing is just one tool.
Trading techniques used by quant traders include high-frequency trading and algorithmic trading.
Ernest Chan, a quantitative trader and expert in statistical models, says: "Hypothesis testing is useful to the extent that if we cannot reject a null hypothesis, we should abandon the strategy. However, just being able to reject a null hypothesis in no way guarantees that the strategy is sound, and will be profitable in live trading."