There are 9 repositories under backtester topic.
QTPyLib, Pythonic Algorithmic Trading
Python Crypto Bot (PyCryptoBot)
Backtesting and Trading Bots Made Easy for Crypto, Stocks, Options, Futures, FOREX and more
Low-latency algorithmic trading platform written in Rust
A stream-based approach to algorithmic trading and backtesting in Node.js
Find your trading, investing edge using the most advanced web app for technical and fundamental research combined with real time sentiment analysis.
Batch backtest, import and strategy params optimalization for Gekko Trading Bot. With one command you will run any number of backtests.
Option and stock backtester / live trader
Gekko Trading Bot dataset dumps. Ready to use and download history files in SQLite format.
Quantitative systematic trading strategy development and backtesting in Julia
Simple backtesting software for options
Algorithmic trading infrastructure in Python.
Python based open source quantitative trading platform development framework
Professional Backtesting Engine for crypto, stocks and forex
Fast and efficient method for testing Uniswap V3 LP Strategies
In this repository, an event-driven backtester is implemented based on QuantStart articles. The backtester is programmed in Python featuring numerous improvements, in terms of coding structure, data handling, and simple trading strategies.
Financial Time Series Price forecast using Keras for Tensorflow. RNN LSTM
tiny backtester to backtest generated signals
All-in-one. Trading terminal with generic gateway implementation, tick backtester, charting, and performance evaluator for trading strategies.
Stock trading strategy back-tester
A trading bot for Bybit utilising APScheduler
You can do Backtest for indicators of Tradingview using this python script.
Stock market backtesting tool written entirely in Python. Currently using the yfinance API library as the primary data source, pandas/numpy for data manipulation, and matplotlib for visualization.
AlgoTrading101 Blankly – Python Backtesting Guide
Custom framework to be used for the development, testing, optimization, and live implementation of systematic trading strategies.