An Interactive Guide to the T-Test for Trading
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.
Purpose & Analogy
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?
Key Assumption
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.
Independent Samples T-Test
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.