Py Vollib Options Pricingv0.3.3

Quantitative traders can price A-share equity options using BSM/Black models while calculating delta, gamma, and other Greeks. Continuous dividend yield adjustments improve accuracy for Chinese stocks.

Backtest options strategies like covered calls or protective puts using historical data. The pipeline integrates data collection, factor computation, and execution simulation for A-share markets.

Developers can set up Sphinx documentation for the py_vollib library, generating consistent API docs and code examples. This reduces onboarding time for new quant team members.

Beyond A-shares, the skill supports HK and crypto option pricing. Traders can apply the same models across markets with minor adjustments for local conventions (e.g., settlement currency).

Combine technical indicators (e.g., MACD) with option Greeks to generate trading signals. Transformers compute signals before accumulators, ensuring no look-ahead bias in A-share backtests.

Offer a cloud-based platform that provides pricing and Greeks via APIs, targeting hedge funds and prop trading desks. Revenue from subscription tiers based on request volume and market coverage.

Use the skill to build custom backtesting and trading strategies for clients. Deliver automated pipelines integrating py_vollib and ZVT, charging project-based fees plus maintenance retainer.

Create online courses teaching options pricing and Greeks using py_vollib. Include hands-on exercises with ZVT backtesting, generating revenue from course sales and certifications.