The t-test is a key tool for comparing average returns and performance. This guide uses interactive trading examples to explain the main types of t-tests and help you understand when to use each one.
A t-test checks if the difference between two average returns is statistically significant or just due to random market noise. Think of it as a performance verifier: is Strategy A truly more profitable than Strategy B, or did it just get lucky in this sample?
The main requirement for a t-test is that the data (e.g., daily or monthly returns) should be approximately normally distributed (forming a "bell curve"). This is a critical check before relying on the test's results.
This test compares the means of two separate, unrelated groups. In trading, this is perfect for comparing the performance of two different strategies that are traded independently.
Example: Comparing the average daily returns of a Momentum Strategy vs. a Mean-Reversion Strategy over the last 60 days to see if one is significantly more profitable.