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gs-quant is a quantitative finance library and financial data analytics toolkit. It serves as a framework for analyzing financial data, developing systematic trading strategies, and managing risk exposure for derivative products in global markets. The project provides tools for quantitative financial analysis, quantitative portfolio modeling, and the development of systematic trading strategies. It enables the calculation of risk for derivative products to structure and hedge positions across markets.
Decentralized Derivatives Trading. Any Market. Anytime. Anywhere.
This repository contains three ways to obtain arbitrage: - Dual Listing Arbitrage - Options Arbitrage - Statistical Arbitrage
A library for financial options pricing written in Python.
I have Created code for Options Trading based on Various Trading Technical Indicators.
The main features of pypatel/options-trading-strategies-in-python are: Trading and Derivatives.
Projects with overlapping indexed features include: goldmansachs/gs-quant — gs-quant is a quantitative finance library and financial data analytics toolkit. It serves as a framework for… injectivelabs/injective-helix-demo — Decentralized Derivatives Trading. Any Market. Anytime. Anywhere. jerbouma/algorithmictrading — This repository contains three ways to obtain arbitrage: - Dual Listing Arbitrage - Options Arbitrage - Statistical… jindaxiang/akshare — AkShare is a Python financial data library and programmatic interface designed for fetching real-time and historical… lumiwealth/lumibot — Backtestable AI trading agents and Python algorithmic trading strategies for stocks, options, crypto, futures, forex,… dbrojas/optlib — A library for financial options pricing written in Python.