# Options Pricing

[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo...

- Repository: https://github.com/agiprolabs/claude-trading-skills (507 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-09-03
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add agiprolabs/claude-trading-skills --skill options-pricing -g -a claude-code -y`
Codex: `npx skills add agiprolabs/claude-trading-skills --skill options-pricing -g -a codex -y`
Cursor: `npx skills add agiprolabs/claude-trading-skills --skill options-pricing -g -a cursor -y`
Gemini CLI: `npx skills add agiprolabs/claude-trading-skills --skill options-pricing -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add agiprolabs/claude-trading-skills`

## Description

[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo, implied volatility surfaces, and Greeks for crypto options

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Options Pricing

> **Status: STUB**, This skill provides a basic Black-Scholes implementation and an overview of planned capabilities. Full implementation is awaiting community contribution.

Options pricing is the quantitative foundation of derivatives trading. For crypto markets, options on BTC and ETH trade actively on Deribit, Lyra, and Aevo, while Solana options are emerging on platforms like Zeta Markets and PsyOptions. Understanding pricing models, implied volatility surfaces, and Greeks is essential for hedging, volatility trading, and constructing structured products.

This skill is informational and analytical only. It does not provide financial advice or trading recommendations.

---

## Current Capabilities

This stub includes a working Black-Scholes calculator with Greeks computation and a basic implied volatility solver. See `scripts/black_scholes.py` for the implementation.

```python
import math
from scipy.stats import norm

def black_scholes_call(S: float, K: float, T: float, r: float, sigma: float) -> float:
    """Price a European call option using Black-Scholes.

    Args:
        S: Current underlying price.
        K: Strike price.
        T: Time to expiration in years.
        r: Risk-free rate (annualized).
        sigma: Volatility (annualized).

    Returns:
        Theoretical call option price.
    """
    d1 = (math.log(S / K) + (r + 0.5 * sigma**2) * T) / (sigma * math.sqrt(T))
    d2 = d1 - sigma * math.sqrt(T)
    return S * norm.cdf(d1) - K * math.exp(-r * T) * norm.cdf(d2)
```

Run the demo:

```bash
python scripts/black_scholes.py --demo
```

---

## Planned Capabilities

When fully implemented, this skill will cover:

### Pricing Models

The rest: https://github.com/agiprolabs/claude-trading-skills/blob/HEAD/skills/options-pricing/SKILL.md