options-strategy

Backtest multi-leg option strategies and synthesize Black-Scholes prices from underlying series.

Updated Apr 10, 2026
One-click install
npx skills add https://github.com/ebrahim-sani/trading-automation --skill options-strategy-ebrahim-sani
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: options-strategy
Source: https://github.com/ebrahim-sani/trading-automation/tree/main/vibe-trading/agent/src/skills/options-strategy
Command: npx skills add https://github.com/ebrahim-sani/trading-automation --skill options-strategy-ebrahim-sani

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill simplifies building and backtesting multi-leg options strategies by synthesizing theoretical option prices using the Black-Scholes model from underlying price series, then simulating portfolio PnL, Greeks exposure, and expiration outcomes without requiring market option quotes.

Core Features & Use Cases

  • Black-Scholes pricing: Compute European call and put theoretical prices using historical volatility as an implied-volatility proxy.
  • Multi-leg backtesting: Support for covered calls, protective puts, straddles, strangles, iron condors, butterflies, and calendar spreads with trade-level open/close/expire handling.
  • Portfolio Greeks and reporting: Aggregate daily delta, gamma, theta, and vega and emit artifacts such as equity.csv, trades.csv, greeks.csv, metrics.csv, and raw OHLCV per code for analysis.
  • Use Case: Run a calendar spread or iron condor backtest on an equity or crypto underlying to measure PnL, time decay, and volatility sensitivity across multiple expiries.

Quick Start

Use the options-strategy skill to backtest an iron condor on 000300.SH from 2020-01-01 to 2024-12-31 using historical IV and a 0.05 risk-free rate.

Frequently Asked Questions about options-strategy

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

FAQPage Schema
How do I backtest multi-leg options strategies without market quotes?

Backtest multi-leg options strategies by synthesizing theoretical option prices using the Black-Scholes model from underlying price series. This simulates portfolio PnL, Greeks exposure, and expiration outcomes without requiring actual market option quotes.

Can I backtest iron condors and calendar spreads on cryptocurrencies?

Yes, you can backtest iron condors and calendar spreads on cryptocurrencies. The engine supports multi-leg options on both equities and cryptocurrencies for hedging, volatility, and spread strategies.

What outputs do I get when backtesting options portfolios?

Backtesting options portfolios generates trade-level PnL, portfolio Greeks, expiry handling, and output artifacts including equity.csv, trades.csv, greeks.csv, and metrics.csv for detailed performance analysis.

How does the Black-Scholes model calculate implied volatility for backtesting?

The Black-Scholes model calculates European call and put theoretical prices using historical volatility as an implied-volatility proxy. You configure this behavior using the iv_source parameter in your options_config.

What configuration is needed to run an options backtest locally?

Running an options backtest requires a config.json file with the engine set to options and options_config parameters like risk_free_rate, iv_source, and contract_multiplier to define the simulation environment.

Does the backtester support delta, gamma, theta, and vega aggregation?

Yes, the backtester supports portfolio Greeks aggregation. It calculates and aggregates daily delta, gamma, theta, and vega exposure across multi-leg positions and outputs the results to greeks.csv.