A Hypothesis-First Framework for Systematic Trading Research
Summary
The document presents a systematic trading course organized around identifying a plausible market edge before building or optimizing a backtest. It describes a research sequence that starts with a hypothesis, then examines data and tests the idea, alongside a framework for judging whether a strategy is useful. The course says it develops four strategies across equities, bonds, crypto, and volatility, and teaches how markets work and why some edges may persist. Its central lesson is that a profitable backtest alone does not establish a durable strategy; traders should understand the economic or structural reason an edge might exist. The author illustrates this with an account of mistaking an early profitable result for skill, then recognizing it could have been luck. The material is educational and self-paced, with some coding encouraged but not presented as the main lesson. It does not provide performance evidence for the strategies, and explicitly offers no guarantee that any trading edge will succeed.
Key ideas
- Begin research with a market hypothesis before selecting data or running a backtest.
- A profitable historical test can reflect luck and does not by itself establish a durable edge.
- Assess trading ideas by asking why the market behavior could persist and who has reason to take the other side.
- The course describes strategies spanning equities, bonds, crypto, and volatility.
- Basic coding can support independent data analysis, though it is not framed as the core lesson.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.