Cryptocurrency trading bot with a graphical user interface with support for simulations, backtests, optimizations, and running live bots.

Coin Trader is a Java-based backend for algorithmically trading cryptocurrencies. It provides data collection and export, complex event processing and triggering, and backtesting - paper trading - live trading.

This is a simple backtesting framework to help you test your crypto currency trading. It includes a way to download and store historical crypto data and to execute a trading strategy.

🤖 Open-source cryptocurrency trading bot designed to perform grid trading strategies using historical data for backtesting

:chart_with_upwards_trend: A live cryptocurrency historical trade data blotter. Download live historical trade data from any cryptoexchange, be it for machine learning, backtesting/visualizing trading strategies or for Quantopian/Zipline.

Cryptocurrency Trading Bot helps to backtest with Machine Learning Models and use it for trading the crypto

Backtest of different trading strategies for cryptocurrencies on historical market data

FundMaker Strategy SDK is a comprehensive toolkit designed for executing trading strategies in cryptocurrency pools using historical data. Built with Node.js and Python, this SDK allows users to backtest strategies, find liquidity pool addresses, fetch spot prices, and simulate options-based hedging.

An automated trader for cryptocurrency implemented in Python for the popular trading platform Robinhood. This automated trader supports live trading, simulated trading on the live market, and even backtesting.

A backtesting platform for cryptocurrency day trading algorithms https://coin-test.github.io/analysis-demo/

Trading strategy backtesting utility and trading robot implementation for Binance and ByBit cryptocurrency exchanges

Repository created by GitHub Project Operator

Repository created by GitHub Project Operator

A powerful, customizable trading bot for KuCoin Futures markets built with Next.js. This application allows you to implement and backtest various trading strategies on cryptocurrency futures markets.

Repository created by GitHub Project Operator

This project was driven by the need to provide our client Mela, a startup focusing on simplifying cryptocurrency investments, with a reliable and scalable platform for backtesting trading strategies. Additionally, leveraging advanced forecasting methods would enhance the platform's capability to predict future price trends with greater accuracy.

A machine learning-driven cryptocurrency trading strategy that leverages advanced models (LSTM, SVM, Random Forest) and Bayesian optimization to achieve returns and risk-adjusted performance. Includes backtesting, rolling correlation analysis, and detailed performance metrics for insights into strategy effectiveness.

Cryptocurrency backtesting library designed for futures trading with Liquidation Handling features

Automated cryptocurrency trading bot with multiple technical analysis algorithms, real-time monitoring, and backtesting capabilities for Hyperliquid exchange.

Trading bot with daily buy and sell signals for both long-short and long-only cryptocurrency strategies with associated backtesting.

OctoQuant is an open-source AI-driven quantitative trading framework designed for both stocks and cryptocurrencies. It provides a unified pipeline for research → backtesting → paper trading → live execution, emphasizing modularity, transparency, and reproducibility.

Repository created by GitHub Project Operator

Machine Learning-driven cryptocurrency trading system with regime detection, backtesting engine, and paper trading. Python research + C++ execution. 1-year backtest: 23.45% return, 1.87 Sharpe ratio. Educational/research project for quantitative finance.

A Freqtrade cryptocurrency trading bot setup for developing, backtesting, and running custom automated trading strategies. This repository contains the Docker configuration, user data, and custom Python strategies for a personal Freqtrade instance.

A Rust-based cryptocurrency trading bot leveraging reinforcement learning with a custom-built, high-frequency market simulator for enhanced backtesting and strategy optimization against real-time order book data via WebSocket streams.

I had to build some models for Algorithmic Trading in Cryptocurrency Market during the Kharagpur Data Science Hackathon 2024. Since then, I have been experimenting with new strategies and comparing their performances through backtesting. This repository contains some of the models I have worked on so far 🧠📊

Our startup, Mela, aims to simplify cryptocurrency trading for everyone and provide reliable investment sources while mitigating risks. We aim to design and build a reliable, large-scale trading data pipeline that can run various backtests and store useful artifacts in a robust data warehouse.

A comprehensive cryptocurrency trading bot built with Freqtrade for strategy development, backtesting, and automated trading.

Cryptocurrency Quantitative Trading & Backtesting Platform (Web): A web-based platform featuring a volume-price database, strategy library, and backtesting engine for cryptocurrency quantitative trading. Develop, test, and deploy your strategies with ease.

Cryptocurrency trading bot in Python. Uses RSI and EMA indicators for automated trading on Binance, with paper trading, backtesting, and Telegram notifications.