ANOVA (Analysis of Variance) lets you compare the average performance of three or more groups. This guide explains its main types using interactive trading examples.
ANOVA checks if there's a significant difference somewhere among the means of several groups. Think of it as a "group chaperone": instead of doing many t-tests, it first tells you if any group is behaving differently from the others overall.
The data in each group should be approximately normally distributed, and the groups should have roughly equal variances. Also, the data points should be independent of each other (unless using a Repeated Measures ANOVA).
Use this to compare the means of three or more independent groups based on a single factor.
Example: A quant firm wants to compare the average monthly returns of three different algorithms ('Alpha', 'Beta', 'Gamma') when traded on the S&P 500. They run each algorithm independently for 50 months and use a One-Way ANOVA to see if any algorithm significantly outperforms the others.