#Pairs-trading
Showing 15 of 15 repositories tagged #pairs-trading, ranked by stars
Quantitative analysis, strategies and backtests
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.
A curated list of awesome algorithmic trading frameworks, libraries, software and resources
This project involves using a combination of statistics along with financial thoery to demonstrate a popular trading strategy used in equity markets: Pairs Trading.
📈This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com
A stock backtesting engine written in Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model
😲🤑Method for Investors and Traders to make Buying and Selling Decisions. 😄Fundamental hare Market Analysis is about using Real data to evaluate a Stock's Value📊 📈 📉
Pair Trading View - .NET application for visual analysis of synthetic financial instruments based on statistical models.
A quantitative trading strategy backtester with an interactive dashboard. Enables users to implement, test, and visualise trading strategies using historical market data, featuring customisable parameters and key performance metrics. Developed with Python and Polars.
Design your own Trading Strategy
A pairs trade is a market neutral trading strategy enabling traders to profit from virtually any market conditions. This strategy is categorized as a statistical arbitrage and convergence trading strategy.
Built a pairs trading strategy in emerging markets using a rolling Kalman-filter beta and spread half-life, with z-score position sizing, and comprehensive back-testing with liquidity adjustments and transaction cost analysis for enhanced risk management
A collection of algorithmic trading strategies implemented in Python. Ideal for backtesting and refining trading ideas, this repository serves as a resource for quantitative traders and developers interest