There are 13 repositories under backtesting-engine topic.
:mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.
QuantStart.com - QSTrader backtesting simulation engine.
A high-frequency trading and market-making backtesting tool in Python and Rust, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.
Backtesting and Trading Bots Made Easy for Crypto, Stocks, Options, Futures, FOREX and more
A stock backtesting engine written in Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model
Option and stock backtester / live trader
Quantitative systematic trading strategy development and backtesting in Julia
A high-performance WebSocket integration library for streaming public market data. Used as a key dependency of the `barter-rs` project.
Python based open source quantitative trading platform development framework
A Black-Scholes-based options backtesting simulator
backtrader documentation
:crystal_ball::moneybag: Backtesting and execution of algorithmic trading strategies in Node.js
Professional Backtesting Engine for crypto, stocks and forex
Cryptocurrency trading bot, and backtesting framework in julia
A fast and simple backtest implementation for algorithmic trading in golang
A pluggable automated trading system backtesting engine.
Documentation and examples for the SignalTrading framework for .NET 5.0, which can be installed through NuGet.
Create automated crypto bots that trade for you while you sleep
Backtester for market neutral equity trading strategies. The code generates long and short signals for each security and then constructs a neutral portfolio.
A highly customizable framework designed for parallel tuning of trading algorithms by reproducing and simulating the trading history of exchanges and the behaviour of brokers.
A proof-of-concept custom backtester
Trading system that aims to buy stocks when they are low and sell stock when they have risen. The time horizon for trades is 2 - 45 days. The strategy has been successfully backtested in version 0.2. Next step: forward test strategy to ensure that it works in practice. Test RL to see if we can can improve results (currently only ~ 5 % of max.)
Python Trading Strategy Analyzer: Backtesting and Metrics Framework
Framework that allows you to replay the exchange trading history for a single ticker and test your trading strategies
Python's pluggable backtester
Backtesting software for intraday and daily timeframe SARIMAX forecasting model. Capable of forecasting on any asset class with backtesting capability across various parameter sets customizable by the user.
Python Backtesting infrastructure for trading strategies + Dashboard
Quantitative Backtester for algo-trading strategies