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Simulation study reveals that machine learning option pricing models tolerate volatility noise but fail under price distortion, indicating data quality supersedes dataset size.
Quickly apply original, key PMR-published papers with Snapshots—a short article companion that distills PMR research into compressed, digestible takeaways, so you can put the paper’s core ideas to work in your investment process—fast. This Snapshot article is based on research arguing that in simulated Black–Scholes option pricing, data quality matters more than sample size: ML models tolerate substantial volatility noise but are highly sensitive to distorted option prices, which larger datasets generally cannot overcome.
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