Search Results for "backtesting"
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Showing 18 open source projects for "backtesting"
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Qbot
AI-powered Quantitative Investment Research Platform
...For evaluation and analysis, Qbot integrates reporting and visualization (tearsheets, metrics) so you can compare performance across runs and inspect trade-level behavior. It supports multiple strategy runtimes and backtesting engines, is organized for extensibility (strategies live in a dedicated folder). -
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Optopsy
A nimble options backtesting library for Python
Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. -
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GoCryptoTrader
Trading bot and framework supporting multiple exchanges
GoCryptoTrader is a full framework / bot for cryptocurrency trading, written in Go (Golang). It supports multiple exchanges, real-time and historic data, backtesting, handling order books, portfolio management, scripting, and many exchange integration features. It is a trading engine that can be run by users to automate strategies across many exchanges. Licensed under MIT. Support for all exchange fiat and digital currencies, with the ability to individually toggle them on/off. Customisation of HTTP client features including setting a proxy, user agent and adjusting transport settings. ... -
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Barter
Open-source Rust framework for building event-driven systems
Barter is an open-source, Rust-based ecosystem of libraries for building high-performance, event-driven algorithmic trading systems—covering live trading, paper trading, and backtesting. It is designed for safety, speed, and flexibility in quantitative finance workflows. Use mock MarketStream or Execution components to enable back-testing on a near-identical trading system as live-trading. Centralised cache-friendly state management system with O(1) constant lookups using indexed data structures. Robust Order management system - use stand-alone or with Barter. ... -
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NautilusTrader
A high-performance algorithmic trading platform
...NautilusTraders design, architecture and implementation philosophy holds software correctness and safety at the highest level, with the aim of supporting Python native, mission-critical, trading system backtesting and live deployment workloads. -
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Awesome-Quant
A curated list of insanely awesome libraries, packages and resources
awesome-quant is a curated list (“awesome list”) of libraries, packages, articles, and resources for quantitative finance (“quants”). It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards. -
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PyBroker
Algorithmic Trading in Python with Machine Learning
Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance. -
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Superalgos
Free, open-source crypto trading bot, automated bitcoin trading
Free, open-source crypto trading bot, automated bitcoin/cryptocurrency trading software, algorithmic trading bots. Visually design your crypto trading bot, leveraging an integrated charting system, data-mining, backtesting, paper trading, and multi-server crypto bot deployments. Superalgos is not just another open-source project. We are an open and welcoming community nurtured and incentivized with the project's native Superalgos (SA) Token, building an open trading intelligence network. You will notice the difference as soon as you join the Telegram Community Group or the new Discord Server! ... -
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AutoTrader
A Python-based development platform for automated trading systems
AutoTrader is a Python-based platform—now archived—designed to facilitate the full lifecycle of automated trading systems. It provides tools for backtesting, strategy optimization, visualization, and live trading integration. A feature-rich trading simulator, supporting backtesting and paper trading. The 'virtual broker' allows you to test your strategies in a risk-free, simulated environment before going live. Capable of simulating multiple order types, stop-losse,s and take-profits, cross-exchange arbitrage and portfolio strategies, AutoTrader has more than enough to build a profitable trading system. -
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Kalshi-Quant-TeleBot
Kalshi Advanced Quantitative Trading Bot is an enterprise-grade
Kalshi Advanced Quantitative Trading Bot is an enterprise-grade automated trading system designed for the Kalshi event-based prediction market. Built with cutting-edge quantitative algorithms and professional risk management, it provides institutional-quality trading capabilities with user-friendly control The Kalshi Advanced Quantitative Trading Bot is a professional-grade automated trading system designed specifically for event-based markets on the Kalshi platform. This bot leverages... -
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TradingGym
Trading backtesting environment for training reinforcement learning
TradingGym is a toolkit (in Python) for creating trading and backtesting environments, especially for reinforcement learning agents, but also for simpler rule-based algorithms. It follows a design inspired by OpenAI Gym, offering various environments, data formats (tick data and OHLC), and tools to simulate trading with costs, position limits, observation windows etc. Licensed under MIT. This training environment was originally designed for tickdata, but also supports OHLC data format. ... -
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AnyTrading
The most simple, flexible, and comprehensive OpenAI Gym trading
gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex. -
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MarketStore
DataFrame server for financial timeseries data
...You can think of it as an extensible DataFrame service that is accessible from anywhere in your system, at higher scalability. It is designed from the ground up to address scalability issues around handling large amounts of financial market data used in algorithmic trading backtesting, charting, and analyzing price history with data spanning many years, and granularity down to tick-level for the all US equities or the exploding cryptocurrencies space. If you are struggling with managing lots of HDF5 files, this is perfect solution to your problem. The batteries are included with the basic install, you can start pulling crypto price data from GDAX and writing it to the db with a simple plugin configuration. ... -
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ML for Trading
Code for machine learning for algorithmic trading, 2nd edition
On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms, how to extract tradeable signals from financial text data like SEC filings, earnings call transcripts or financial news. Using deep learning models like CNN and RNN with financial and alternative data, and how to generate synthetic data with Generative Adversarial Networks, as well as training a trading agent using deep reinforcement learning. -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. -
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PandoraTrader
C++ Trade Platform for quant developer
PandoraTrader is a high-frequency quantitative trading platform implemented in C++. It interfaces with real-world futures trading desks using Trade APIs and MarketData APIs and includes support for backtesting via simulated market components. We design such a trading platform with various skills given by the designer, but we do not carry wisdom; this wisdom belongs to the strategy designer. We hope that the strategy designer will design excellent strategies to give the trading software enough wisdom to be able to ride the wind and waves in the floating market, hanging sails across the sea. ... -
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PyAlgoTrade
Python Algorithmic Trading Library
PyAlgoTrade is a Python library for backtesting stock trading strategies. -
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QuantComponents
Free Java components for Quantitative Finance and Algorithmic Trading
... * Highly modular: usable as plain java API, OSGi components, or integrated into Eclipse * Standalone or client-server architecture, depending on performance and reliability needs * Integrated with Interactive Brokers through IB Java API * Generic broker API, it can easily be extended to work with other brokers * It works with historical and/or realtime market data * Backtesting facility * Extensible SWT charting library
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