Options Pricing
[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo...
Install
npx skills add agiprolabs/claude-trading-skills --skill options-pricing -g -a claude-code -y- Repository
- agiprolabs/claude-trading-skills507
- Category
- Engineering
- Updated
- 2mo ago
- License
- MIT
- Context cost
- Lightabout 1,348 tokens
- Runs scripts
- Yes, review before use
What it does
[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo, implied volatility surfaces, and Greeks for crypto options
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.
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:
python scripts/black_scholes.py --demo
Planned Capabilities
When fully implemented, this skill will cover:
