# PyPatel/Options-Trading-Strategies-in-Python

Developing Options Trading Strategies using Technical Indicators and Quantitative Methods

Repository: https://github.com/PyPatel/Options-Trading-Strategies-in-Python
Canonical: https://ross.abutalabs.com/products/options-trading-strategies-in-python
Language: Python
License Family: other
Topics: options-trading, quantitative-finance, quantitative-trading, indicators, machine-learning, machine-learning-algorithms, python, python3, quantitative, quantitative-investment, quantitative-strategies, options-trading-strategies, technical-indicators
Last push: 2024-04-22T20:12:29+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3290, "days_push": 863, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1061, forks 252 (observed 2026-08-28T04:03:25.971151+00:00)

## What it is
A collection of Python scripts implementing options trading strategies based on technical indicators such as VIX, Put/Call Ratio, TRIN, and Turtle Trading, plus Monte Carlo option pricing in C++. It also explores LSTM-based prediction for improving strategy accuracy.

## Use cases
- backtest options trading strategies based on VIX
- implement a put/call ratio trading strategy in python
- price options with monte carlo simulation
- learn turtle trading strategy code
- predict option prices with LSTM neural networks
- explore quantitative trading strategies with technical indicators

## When to choose
- you want reference code for indicator-based options strategies
- you are learning quantitative finance concepts in python
- you need a starting point for LSTM-based price prediction experiments

## When to avoid
- you need production-ready, licensed trading software
- you require maintained, tested, or documented code
- you need a full backtesting framework or broker integration

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, data-science, trading
- domain: fintech, data-science
- platform: python
- tags: options-trading, quantitative-finance, technical-indicators, monte-carlo-simulation, black-scholes, lstm, vix, put-call-ratio, turtle-trading, no-license, cryptocurrency, algorithms

## Member repositories
- PyPatel/Options-Trading-Strategies-in-Python (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:25.971151+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:56:48.412735+00:00, confidence not recorded.
  - readme: https://github.com/PyPatel/Options-Trading-Strategies-in-Python (fetched 2026-08-28T04:03:25.971151+00:00, sha 167f61105fea)
- Data as of 2026-08-30T08:39:29.467469+00:00.