statistical-arbitrage

There are 33 repositories under statistical-arbitrage topic.

  • quant-trading

    je-suis-tm/quant-trading

    Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, Shooting Star, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

    Language:Python6.1k250151.2k
  • letianzj/QuantResearch

    Quantitative analysis, strategies and backtests

    Language:Jupyter Notebook2.3k765476
  • Kismuz/btgym

    Scalable, event-driven, deep-learning-friendly backtesting library

    Language:Python988100130261
  • AlgorithmicTrading

    JerBouma/AlgorithmicTrading

    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.

    Language:Jupyter Notebook897290186
  • bradleyboyuyang/Statistical-Arbitrage

    High-frequency statistical arbitrage

    Language:Jupyter Notebook1556236
  • tibkiss/huba-v1

    Pairs Trading using Statistical Arbitrage

    Language:Python1525013
  • chicago-joe/InteractiveBrokers-PairsTrading-Algo

    A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion in Python

    Language:Python8813327
  • autistic-symposium/blockchain-science-rs

    👾 my onchain research, foundry boilerplates, quant bots, algorithms - rust edition

    Language:Solidity643119
  • Blue-Universe/Time-Series-Analysis-Statistical-Arbitrage

    This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.

    Language:Jupyter Notebook634015
  • Pynaissance

    conquerv0/Pynaissance

    A walk through the frameworks of Python in Finance. The repository is currently in the development phase. The finalized version will include a full-fledged integration and utilization of Quantopian, GS-Quant, WRDS API and their relevant datasets and analytics.

    Language:Jupyter Notebook26409
  • 5ymph0en1x/SAAT

    Identify and trade statistical arbitrage opportunities between cointegrated pairs using Bitfinex API

    Language:Python191010
  • arikaufman/algorithmicTrading

    Experimenting with Algo Trading using Backtrader Python Module. Specifically, statistical arbitrage using cointegration.

    Language:Python15303
  • SergioIommi/Quant-Trading-Dashboards

    Equities Pair Trading/Statistical Arbitrage and Multi-Variable Index Regression

    Language:Jupyter Notebook14114
  • adamd1985/pairs_trading_unsupervised_learning

    The notebook with the experiments to replicate and enhance the stock clustering proposed by Han(2022) for alogtrading, with KMeans Optimization

    Language:Jupyter Notebook11203
  • easyeleven/Statistical-Arbitrage-in-Cryptocurrencies

    The goal of this project is to develop a statistical arbitrage strategy for cryptocurrencies using Python

    Language:Python8104
  • miindisponi99/Statistical-Arbitrage-Emerging-Markets

    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

    Language:Jupyter Notebook8100
  • anthonyli01/Statistical-Arbitrage-Pairs-Trading-Strategy

    On-going project: I will be implementing a combination of pairs trading strategies in attempt to see which type performs best after backtesting. The main ideas involve cointegration, kalman filter, copulas, and machine learning approaches. Since it is a market-neutral strategy, we will analyse the performance on its alpha rather than sharpe ratio.

    Language:Jupyter Notebook7102
  • oldoldjiang/statarber

    statistic arbitrage strategy research tools

    Language:R3103
  • rzhadev1/statarb

    generalized pairs trading and statistical arbitrage in python.

    Language:Jupyter Notebook3102
  • jeffzzzhang/pair_trading

    pair trading(stat arb), July 2017

    Language:Python2104
  • Xavierleeeugene/Trading_Strategies

    This repository features a collection of in-depth quantitative trading strategies, as well as strategies based on technical analysis.

    Language:Jupyter Notebook220
  • axwhyzee/stat-arb-dashboard

    Visualize FX arbitrage portfolios. Form a portfolio by selecting a set instruments and corresponding beta values, using live FX data from OANDA.

    Language:JavaScript1111
  • alichopping/Mid-Frequency-Statistical-Arbitrage

    An exposition of a simple pairs trading strategy on two stocks (Bajaj Finserv and Indian Bank) in the Nifty500, at the one-minute time frequency, in order to demonstrate some of the core ideas of statistical arbitrage strategies.

    Language:Jupyter Notebook0100
  • brianabod/fe_investing

    Iron Investing: Statistical Arbitrage for Portfolio Optimization

    Language:Python0100
  • d-roizman/arbitrage-algorithms

    Statistical arbitrage algorithms implemented in python

    Language:Python0100
  • eualezandre/Field-Project---Pairs-Trading

    Projeto de Field Project na Oráma Investimentos que visa o desenvolvimento de mecanismos de arbitragem estatística com estratégia de pairs trading no mercado de ações.

    Language:Jupyter Notebook0101
  • left-nullspace/cointegration-exploration-python

    This project explores pairs trading as a market-neutral strategy by leveraging statistical relationships between cointegrated assets to exploit mean-reverting behavior. inspired and adapted from the quant trading room

    Language:Jupyter Notebook00
  • achadha5/stat-arb-crypto

    Statistical Arbitrage in Cryptocurrencies Project

    Language:Jupyter Notebook
  • George-Dros/Pair_trading

    A pair-trading algorithm using cointegration, linear regression, and Z-score-based entry/exit rules. The strategy, applied to validated stock pairs, achieved consistent portfolio growth from $24,050 to $25,489.50 over 2 years through trading simulation.

    Language:Jupyter Notebook
  • jonadiazm/momentum_residual_analysis

    Analysis of an investment strategy known as Residual Momentum on the New York Stock Exchange (NYSE) is based on the premise that stock returns exhibit a certain "inertia", which gives rise to the phenomenon known as the "momentum effect".

    Language:Jupyter Notebook
  • ngozzi/statarb

    Official repository for the team "FinNet Folks" at the CNWW 2021 (https://vermontcomplexsystems.org/events/cnww/)

    Language:Jupyter Notebook302
  • sjdKRM/EPAT

    Executive Programme in Algorithmic Trading by QuantInsti