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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.

alphalens

Performance analysis of predictive (alpha) stock factors

arbitrage-bot

A bot that makes profit of the best crypto Arbitrage opportunities on the market

arctic

High performance datastore for time series and tick data

arcticdb

ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.

awesome-rl-envs

backtesting.py

:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.

bayesian-neural-networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

best-execution

Application of reinforcement learning to the development of execution algorithms in the field of finance. These algorithms break CARE orders into CHILD orders and exectute them in the market.

betting-against-beta

This project is based upon the paper: Frazzini, A. & Pedersen, L. (2014). Betting against beta.

binance-crypto-triangular-arbitrage

A profitable triangular arbitrage cycles finder.

binance-public-data

Details on how to get Binance public data

binance-triangle-arbitrage

Detect in-market cryptocurrency arbitrage

black-scholes-implied-volatility-calculator

C++ Implied Volatility calculator, which uses the Black-Scholes-Merton model to calculate the Implied Volatility of European call and put options.

blackbird

Blackbird Bitcoin Arbitrage: a long/short market-neutral strategy

blankly

🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package.

btrader

Triangle arbitrage trading bot for Binance

c-binance-future-quant

low-cost, high-efficiency, easy-to-implement

chatgpt_telegram_bot

conditional-wgan-gp

Implementation of a Wasserstein Generative Adversarial Network with Gradient Penalty to enforce lipchitz constraint. The WGAN utilizes the wasserstein loss or critic as its loss function instead of the vanilla GAN loss. It has shown to perform better as is often used as a solution to mode collapse, a common issue in GANs where the generator produce

crypto-arbitrage

Automatic Cryptocurrency Trading Bot using Triangular or Exchange Arbitrages

crypto-arbitrage-framework

A cryptocurrency arbitrage framework implemented with ccxt and cplex. It can be used to monitor multiple exchanges, find a multi-lateral arbitrage path which maximizes rate of return, calculate the optimal trading amount for each pair in the path given flexible constraints, and execute trades with multi-threading implemenation.

crypto-rl

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

crypto-triangular-arbitrage-bot

The algorithm to calculate Triangular Arbitrage with depth on Centralised exchanges.

cryptocurrency-trading-bots-python-beginner-advance

Crypto Trading Bots in Python - Triangular Arbitrage, Beginner & Advanced Cryptocurrency Trading Bots Written in Python

ctc-executioner

Master Thesis: Limit order placement with Reinforcement Learning

cvxportfolio

Portfolio optimization and back-testing.

dash-tradingview

Tradingview Lightweight Charts wrapper for Plotly Dash apps

databento-python

The official Python client library for Databento.