Options strategy playground

Most options tools show one strategy at a time and assume you already know which one you want. The real question is the reverse: given a view like "$X in N days", which structure fits it, and what are you giving up with each one? Answering that by hand means re-pricing every leg for every scenario.

You set a target price, a horizon, and optionally an implied-volatility shift. The engine prices 19 strategy templates, from single legs and spreads to condors, butterflies, calendars, and covered positions, and shows them in one sortable table: P&L at the target, max profit and loss, breakevens, probability of profit, expected P&L under your view, and net Greeks. Every strike, quantity, and premium can be edited. Typing in your own premium back-solves the implied vol, so the Greeks and the curves before expiry stay consistent with the price you entered.

1. 01Price view + horizon
2. 02Strategy templates → legs
3. 03Black-Scholes pricing on a price × time grid
4. 04Side-by-side comparison + charts

• EnginePython · NumPy
• APIFastAPI
• AppReact + TypeScript · Plotly
• DeployVercel · Playwright + pytest in CI

• Every strategy re-priced in a single vectorized request
• Pricing checked against textbook values, put-call parity, and finite-difference Greeks
• Engine is a plain Python package the next stage (forecasting and strategy selection) can import directly