Practice quant research the way professional teams structure it: rigorous hypotheses, point-in-time data, factor-aware testing, validation, peer review and decision memos.
Duration10 weeks
LevelAdvanced
Modules10
Lessons40
This course brings together research design, statistics and engineering into a complete, institutional-style research workflow. You will move from literature review and hypothesis design through point-in-time data preparation, factor-aware testing, robust validation, portfolio integration and peer review. The capstone is a full research study, written up as a decision memo that a review committee could evaluate on its merits and limitations.
10 modules · 40 lessons · 10 weeks. Curriculum preview; the final syllabus may change before enrollment opens.
Write a research proposal with literature review, hypotheses and a pre-registered test plan
Run a factor-aware signal study with point-in-time data and robust validation
Complete a capstone research study and present it as a decision memo for peer review
Quantzivo certificates are completion credentials issued by Quantzivo, not accredited qualifications. Courses teach technical and research skills; they do not promise investment returns or provide investment advice.
8 weeks8 modulesResearch, construct and evaluate factor models using cross-sectional regressions, portfolio sorts and risk attribution, with careful handling of biases and multiple testing.
10 weeks10 modulesEngineer a professional-grade algorithmic research platform with versioned data, experiment tracking, scalable backtesting, validation gates and review workflows.
12 weeks12 modulesComplete an end-to-end quantitative research project on historical data, from hypothesis and backtest to robustness testing, peer review and a reproducible write-up.
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