Learn a structured process for designing trading strategies: forming hypotheses, defining rules, choosing data and evaluation criteria, and documenting research honestly.
Duration5 weeks
LevelIntermediate
Modules5
Lessons20
This course teaches strategy design as a research process rather than a search for winning rules. You will learn to form economically motivated hypotheses, specify rules precisely, choose data and test periods, and set evaluation criteria before looking at results. Along the way you will study common strategy families, such as trend, mean reversion and carry, and practice writing research notes that make assumptions and limitations explicit.
5 modules · 20 lessons · 5 weeks. Curriculum preview; the final syllabus may change before enrollment opens.
Write a strategy design document for a trend-following idea, from hypothesis to acceptance criteria
Prototype and test a mean-reversion rule set with a pre-defined evaluation plan
Produce a research note comparing two strategy families on the same universe
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.
6 weeks6 modulesBuild accurate, bias-aware backtesting engines in Python, from vectorized prototypes to event-driven simulators with realistic costs, fills and portfolio accounting.
4 weeks4 modulesLearn how algorithmic trading systems are structured, from market data and signals to orders, risk checks and evaluation, with a clear view of their limits.
7 weeks7 modulesApply rigorous validation methods to trading strategies: walk-forward and cross-validation, overfitting diagnostics, multiple testing control and robust parameter optimization.
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