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.