QuantLab, part 1 of 6
Foundations.
What quantitative research is, the loop it runs in, and how a result fools you.
5 articles, about 37 minutes in order. Foundational first, then applied, then advanced.
- 01
What quantitative research actually is
Quantitative research is a repeatable procedure from question to evidence, not a pattern found once in a spreadsheet. Here is the difference.
- 02
The research loop, end to end
Quant research moves through eight dependent stages, from universe to evidence. Skip one and its risk does not disappear — it moves downstream.
- 03
Signal versus noise: what a result has to survive
A good-looking Sharpe ratio is not evidence by itself. It has to survive the number of things tried to find it, and a comparison against doing nothing.
- 04
Reading a backtest without fooling yourself
A backtest report has a correct reading order. Read the worst fold and the cost sensitivity before the headline Sharpe ratio, not after.
- 05
Common failure modes in retail quant research
The same six mistakes account for most inflated backtests in independent quant research. Each one is easy to make and easy to check for.
Other parts of QuantLab
- 02Data and featuresPreparing financial time series, building features without leakage, choosing a benchmark.
- 03ModelsModel families and when to use them, linear against trees, hyperparameters, forecasting.
- 04ValidationChronological splits, purging and embargoing, walk-forward folds, the naive baseline, overfitting.
- 05Portfolio and riskOptimisation from first principles, risk metrics that matter, stress testing, explainability.
- 06PracticeReproducibility, checkable reports, re-runnable workflows, presenting work, teaching a term.
Read it here, then run it in the workspace.
Every article links to the platform page that implements the idea. Beta access is free and opens by cohort.