option-pricing

Price European and exotic options and compute Greeks via automatic differentiation in Python with JAX.

1|Updated Jan 16, 2026
One-click install
npx skills add https://github.com/yonesuke/skills --skill option-pricing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: option-pricing
Source: https://github.com/yonesuke/skills/tree/main/option_pricing
Command: npx skills add https://github.com/yonesuke/skills --skill option-pricing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jax, jaxlib, and includes scripts (resource) components.

What problem does it solve?

Pricing financial derivatives and computing risk metrics with automations for Black-Scholes, Greeks, and exotic options.

Core Features & Use Cases

  • Analytical pricing & greeks: Black-Scholes, Greeks via auto-diff.
  • Exotic options support: Path- and event-based pricing references.
  • Use Case: Model fair values and hedging metrics for European and exotic options in Python/JAX.

Quick Start

Run the provided example to price a European call and compute greeks using the included scripts.

Frequently Asked Questions about option-pricing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute option Greeks using automatic differentiation in Python?▼

You can compute option Greeks via auto-diff using JAX in Python. This Skill implements Black-Scholes pricing and calculates Greeks automatically, providing accurate hedging metrics for European options without manual gradient derivations.

Can I price exotic options with Black-Scholes and JAX?▼

Yes, you can price exotic options using JAX. This Skill provides path- and event-based pricing references for exotic options alongside standard Black-Scholes analytical pricing, supporting fair value modeling for non-standard derivative structures.

What is the best way to calculate European call option prices and hedging metrics?▼

The best way to calculate European call option prices and hedging metrics is using auto-differentiation with JAX. This approach implements Black-Scholes formulas and computes Greeks simultaneously, providing both fair values and risk metrics through included scripts.

Do I need JAX to run automatic differentiation for option pricing?▼

Yes, you need JAX and jaxlib installed to run automatic differentiation for option pricing. These dependencies provide the auto-diff framework required to compute Black-Scholes Greeks and model exotic options in Python.

How does automatic differentiation improve Greeks calculation for derivatives?▼

Automatic differentiation improves Greeks calculation by computing exact derivatives programmatically through JAX, eliminating manual symbolic differentiation errors. This method calculates Black-Scholes risk metrics like delta and gamma directly from the pricing function with high numerical accuracy.