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@gemchange_ltd: How to Simulate Like a Quant Desk. Every Model, Every Formula,…
@gemchange_ltdbookmarkx
TL;DR. A build-from-scratch tour of quant simulation — coin flip → Monte Carlo → importance sampling — for actually pricing Polymarket contracts instead of vibing on gut probabilities.
Takeaways
- Crude Monte Carlo is worst exactly where it matters: variance peaks at p=0.5, the most-traded contracts on the platform.
- Brier score is the calibration yardstick — under 0.10 is excellent; 538/Economist hit 0.06–0.12 on presidential races. Beat that and you have edge.
- Importance sampling via exponential tilting (γ solves M(γ)=1) cuts variance 100–10,000× on tail-risk contracts — 100 tilted samples beat 1M crude ones.
- Retail's core mistake: treating a contract as a biased coin with one parameter p, ignoring correlation, info flow, order book dynamics, and execution risk.