options-pricing
[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo, implied volatility surfaces, and Greeks for crypto options
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/agiprolabs/claude-trading-skills --skill options-pricing- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads options-pricing automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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:
Pricing Models
| Model | Option Style | Use Case |
|---|---|---|
| Black-Scholes | European | Vanilla calls/puts, quick Greeks |
| Binomial Tree | American | Early exercise, dividend-paying assets |
| Monte Carlo | Exotic | Path-dependent, barrier, Asian options |
| Black-76 | Futures | Futures options on crypto perpetuals |
Greeks
| Greek | Measures | Formula Basis |
|---|---|---|
| Delta | Price sensitivity to underlying | dC/dS |
| Gamma | Delta sensitivity to underlying | d²C/dS² |
| Theta | Time decay per day | dC/dT |
| Vega | Sensitivity to volatility | dC/dσ |
| Rho | Sensitivity to interest rates | dC/dr |
Implied Volatility
- Newton-Raphson and bisection IV solvers
- Volatility smile and skew analysis
- IV surface construction (strike x expiry)
- IV term structure analysis
- Vol-of-vol estimation
Crypto Options Platforms
| Platform | Chain | Assets | Style |
|---|---|---|---|
| Deribit | Off-chain | BTC, ETH | European |
| Lyra | Optimism/Arbitrum | ETH, BTC | European |
| Aevo | Ethereum L2 | BTC, ETH, alts | European |
| Zeta Markets | Solana | SOL, BTC | European |
| PsyOptions | Solana | SOL, various | American |
Structured Products
- Covered calls and protective puts
- Straddles and strangles for volatility trading
- Vertical spreads for directional exposure
- Iron condors for range-bound markets
- Calendar spreads for term structure trades
Prerequisites
# Core (for full implementation)
uv pip install numpy scipy
# Optional (for visualization)
uv pip install matplotlib
The included scripts/black_scholes.py uses only the Python standard library (math module) and runs without any dependencies.
Use Cases
Hedging
Compute delta-neutral hedge ratios for crypto spot positions using options. Calculate the number of put contracts needed to protect a portfolio against downside moves.
Volatility Trading
Compare implied volatility to realized volatility to identify over/underpriced options. When IV significantly exceeds realized vol, selling premium may be favorable (and vice versa).
Structured Products
Price structured products that combine options at different strikes and expirations. Analyze payoff profiles and breakeven points before execution.
Risk Assessment
Use Greeks to understand portfolio-level exposure to price moves (delta), acceleration (gamma), time decay (theta), and volatility changes (vega).
Quick Reference: Black-Scholes Formulas
Call price:
C = S * N(d1) - K * e^(-rT) * N(d2)
Put price:
P = K * e^(-rT) * N(-d2) - S * N(-d1)
Where:
d1 = [ln(S/K) + (r + σ²/2) * T] / (σ * √T)
d2 = d1 - σ * √T
Put-call parity:
C - P = S - K * e^(-rT)
Files
| File | Description |
|---|---|
references/planned_features.md | Planned features, formulas, data sources, and implementation priorities |
scripts/black_scholes.py | Black-Scholes calculator with Greeks and implied vol solver |
Contributing
This skill is a stub awaiting full implementation. To contribute:
- Implement binomial tree pricing for American-style options
- Add Monte Carlo simulation for exotic payoffs
- Build IV surface construction from market quotes
- Integrate Deribit API for live options chain data
- Add portfolio Greeks aggregation
See references/planned_features.md for the full feature list and implementation priorities.
This skill provides analytical tools and mathematical models for informational purposes only. It does not constitute financial advice. Options trading involves substantial risk of loss.
FAQ
What does the options-pricing skill do?
[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo, implied volatility surfaces, and Greeks for crypto options
How do I install options-pricing?
Run npx skills add https://github.com/agiprolabs/claude-trading-skills --skill options-pricing in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/options-pricing/ (personal) or .claude/skills/options-pricing/ (project).
Which AI agents can use options-pricing?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is options-pricing safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains options-pricing?
It is published by agiprolabs in agiprolabs/claude-trading-skills. It has 487 recorded installs.
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