Formal validation of generated hypotheses

Determine whether the trading strategy hypotheses generated by QuantEvolve’s hypothesis-driven research agent are grounded in established market theories or instead constitute post-hoc rationalizations of data-mined patterns by developing and applying formal external validation procedures (e.g., literature comparison, expert review, or causal inference).

Background

QuantEvolve employs a hypothesis-driven multi-agent system to generate and evolve trading strategies, but the epistemic validity of these hypotheses has not been formally established.

Ensuring that hypotheses reflect genuine market-theoretic principles rather than retrospective justifications for patterns found in data is critical for trustworthiness and generalization, motivating explicit external validation mechanisms such as literature comparison, expert review, and causal inference frameworks.