There are 19 repositories under backtesting-frameworks topic.
🔎 📈 🐍 💰 Backtest trading strategies in Python.
Open-source Rust framework for building event-driven live-trading & backtesting systems
A nimble options backtesting library for Python
Modular Python library that provides an advanced event driven backtester and a set of high quality tools for quantitative finance. Integrated with various data vendors and brokers, supports Crypto, Stocks and Futures.
event-driven backtesting framework written in golang
High-frequency statistical arbitrage
These are the code snippets used in the Backtrader for backtesting guide on the AlgoTrading101 website
Backtesting toolbox for trading strategies
backtrader documentation
A fast and simple backtest implementation for algorithmic trading in golang
Trading strategy backtesting framework supporting multiple concurrent sessions, complex exit strategies, and multi-exchange data sources with simple Python implementation
Backtest and run stock trading CFD strategies tick by tick
High-Performance Quantitative Backtesting Engine
Back Testing strategies fast in Python
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.
DataTrader è una piattaforma open-source di backtesting basato sugli eventi da utilizzare nei mercati azionari. La maggior parte delle strategie descritte nel sito TradingQuant.it (www.tradingquant.it) utilizza DataTrader come framework per il backtest.
Backgommon is a backtesting and simulation framework for trading strategies, written in pure go. It aims to be fast, flexible and easy to use.
Explore and leverage the correlation between oil price movements, energy sector, and transportation sector. This repository houses quantitative research findings and trading strategies that exploit this correlation to generate robust signals.
Built a practical Multi-Factor Backtesting Framework from scratch based on Huatai Security's(One of China's largest sell side) financial engineering report. Steps include factor data collection and preprocessing, factor combination, portfolio optimization and risk return analysis.
Framework open-source in python progettato per l'investitore. Permette di effettuare simulazioni di strategie di asset allocation per portafogli di azioni ed ETF. Descritto ed utilizzato su TradingQuant.it (www.tradingquant.it)
A Python script to classify companies based on financial metrics like Piotroski F-Score and Stock Valuation, using CSV financial data for analysis and output.
Comprehensive GitHub repository showcasing proficient utilization of the backtesting.py library, illustrating code implementations and insightful learnings in quantitative financial backtesting strategies.
Framework that allows you to test long position trading algorithms on historical data with a time frame in mind.
A better, faster, simple to implement and extendable Python backtesting framework for stock trading algorithm evaluation.
Python Backtesting library for trading strategies