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@@ -158,6 +158,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [Hikyuu](https://github.com/fasiondog/hikyuu) - A base on Python/C++ open source high-performance quant framework for faster analysis and backtesting, contains the complete trading system components for reuse and combination.
- [rust_bt](https://github.com/jensnesten/rust_bt) - A high performance, low-latency backtesting engine for testing quantitative trading strategies on historical and live data in Rust.
- [Gunbot Quant](https://github.com/GuntharDeNiro/gunbot-quant) - Toolkit for quantitative trading analysis. It integrates an advanced market screener, a multi-strategy, multi-asset backtesting engine. Use with built-in GUI or through CLI.
- [StrateQueue](https://github.com/StrateQueue/StrateQueue) - An open‑source, broker‑agnostic Python library that lets you seamlessly deploy strategies from any major backtesting engine to live (or paper) trading with zero code changes and built‑in safety controls.
### Risk Analysis
@@ -215,6 +216,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
### Data Sources
- [yfinance](https://github.com/ranaroussi/yfinance) - Yahoo! Finance market data downloader (+faster Pandas Datareader)
- [defeatbeta-api](https://github.com/defeat-beta/defeatbeta-api) - An open-source alternative to Yahoo Finance's market data APIs with higher reliability.
- [findatapy](https://github.com/cuemacro/findatapy) - Python library to download market data via Bloomberg, Quandl, Yahoo etc.
- [googlefinance](https://github.com/hongtaocai/googlefinance) - Python module to get real-time stock data from Google Finance API.
- [yahoo-finance](https://github.com/lukaszbanasiak/yahoo-finance) - Python module to get stock data from Yahoo! Finance.
@@ -573,3 +575,4 @@ date conversion, scaling factor values, and filtering by the specified date.
- [Tidy Finance](https://www.tidy-finance.org/) - An opinionated approach to empirical research in financial economics - a fully transparent, open-source code base in multiple programming languages (Python and R) to enable the reproducible implementation of financial research projects for students and practitioners.
- [RoughVolatilityWorkshop](https://github.com/jgatheral/RoughVolatilityWorkshop) - 2024 QuantMind's Rough Volatility Workshop lectures.
- [AFML](https://github.com/boyboi86/AFML) - All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
- [AlgoTradingLib](https://github.com/usdaud/algotradinglib.github.io) - A catalog of algorithmic trading libraries, frameworks, strategies, and educational materials.