OptionsMath AI
You bring the thesis. AI does the math.
OptionsMath AI is a thesis-to-options solver: a language model turns your market thesis into explicit, editable scenario assumptions, then a deterministic options engine prices every candidate structure across those scenarios and ranks them by modeled expected value under the assumptions you can see and change.
The language model handles the thesis. A deterministic engine handles the options math. The model reads your thesis plus the ticker's live spot and returns a constrained scenario schema — it never prices an option, picks a strike, or ranks a structure. From there a compiled engine enumerates candidates across 29 strategy families, calibrates an SSVI volatility surface and the Bates, Heston, Merton jump-diffusion, and Variance Gamma models to the live option chain, prices every leg in every scenario, and ranks what survives by probability-weighted modeled P&L less an assignment-risk penalty and a model-disagreement penalty.
Rankings are model-derived under the assumptions shown. They are hypothetical research outputs, not investment advice, recommendations, or promises of return.