Guides
Plain-language explainers on telling a real edge from a lucky backtest — the methods behind the calculators, written for working systematic and algorithmic traders.
Walk-Forward Optimization in Pure Python
Rolling and anchored walk-forward without a vendor platform: train/test windows, parameter stability, and why a full-sample grid Sharpe is not an out-of-sample edge — with attributed teaching numbers and rewritten code.
Read the guide →Backtest Overfitting
How a worthless strategy can post a great Sharpe by chance, three real failure cases from hands-on research, and the validation toolkit — Deflated Sharpe Ratio, PBO, purged walk-forward and CPCV — that separates a genuine edge from the best of many tries.
Read the guide →Guides vs. the course
These guides are the long-form, deep-dive companions to our free Learn course, where the same ideas are taught from scratch, in order, with diagrams and worked examples. If you're new to systematic trading, start with the course; come here when you want the fuller treatment of a single topic.
The flagship guide above takes apart backtest overfitting — why a worthless strategy can post a brilliant Sharpe ratio by chance, and the toolkit that catches it: the Deflated Sharpe Ratio, out-of-sample testing, and walk-forward validation. You can see that toolkit applied to real published strategies in our strategy teardowns, and the same ground covered step by step in Module 5 of the course. More guides are on the way.