Statistical Inference: Testing Trading Strategies Scientifically

Statistical inference is how quants determine whether a trading edge is real or just luck. In this video, we explore hypothesis testing, confidence intervals, and significance testing—giving you the tools to scientifically validate your strategies and avoid falling for random patterns.
What You'll Learn:

What statistical inference means for trading
Null hypothesis: assuming no edge exists
P-values and statistical significance explained
Type I and Type II errors in strategy testing
Confidence intervals for performance metrics
T-tests for comparing strategy returns
Sample size and statistical power
Multiple testing problem and false discoveries
Bayesian vs frequentist approaches
Bootstrap methods for robust inference
How Athena Quant validates trading signals
Avoiding data mining and overfitting
When statistical significance doesn't mean profitable

Before risking real capital, you need to know if your strategy's performance is statistically meaningful or just noise. This video gives you the framework to make that determination rigorously.
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