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@@ -21,6 +21,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [numpy](https://www.numpy.org) - NumPy is the fundamental package for scientific computing with Python.
- [scipy](https://www.scipy.org) - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.
- [pandas](https://pandas.pydata.org) - pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
- [polars](https://docs.pola.rs/) - Polars is a blazingly fast DataFrame library for manipulating structured data.
- [quantdsl](https://github.com/johnbywater/quantdsl) - Domain specific language for quantitative analytics in finance and trading.
- [statistics](https://docs.python.org/3/library/statistics.html) - Builtin Python library for all basic statistical calculations.
- [sympy](https://www.sympy.org/) - SymPy is a Python library for symbolic mathematics.
@@ -140,9 +141,12 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [Intelligent Trading Bot](https://github.com/asavinov/intelligent-trading-bot) - Automatically generating signals and trading based on machine learning and feature engineering
- [fastquant](https://github.com/enzoampil/fastquant) - fastquant allows you to easily backtest investment strategies with as few as 3 lines of python code.
- [nautilus_trader](https://github.com/nautechsystems/nautilus_trader) - A high-performance algorithmic trading platform and event-driven backtester.
- [YABTE](https://github.com/bsdz/yabte) - Yet Another (Python) BackTesting Engine.
### Risk Analysis
- [QuantLibRisks](https://github.com/auto-differentiation/QuantLib-Risks-Py) - Fast risks with QuantLib
- [XAD](https://github.com/auto-differentiation/xad-py) - Automatic Differentation (AAD) Library
- [pyfolio](https://github.com/quantopian/pyfolio) - Portfolio and risk analytics in Python.
- [empyrical](https://github.com/quantopian/empyrical) - Common financial risk and performance metrics.
- [fecon235](https://github.com/rsvp/fecon235) - Computational tools for financial economics include: Gaussian Mixture model of leptokurtotic risk, adaptive Boltzmann portfolios.
@@ -445,11 +449,15 @@ A curated list of insanely awesome libraries, packages and resources for Quants
## CPP
- [QuantLib](https://github.com/lballabio/QuantLib) - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.
- [QuantLibRisks](https://github.com/auto-differentiation/QuantLib-Risks-Cpp) - Fast risks with QuantLib in C++
- [XAD](https://github.com/auto-differentiation/xad) - Automatic Differentation (AAD) Library
- [TradeFrame](https://github.com/rburkholder/trade-frame) - C++ 17 based framework/library (with sample applications) for testing options based automated trading ideas using DTN IQ real time data feed and Interactive Brokers (TWS API) for trade execution. Comes with built-in [Option Greeks/IV](https://github.com/rburkholder/trade-frame/tree/master/lib/TFOptions) calculation library.
## Frameworks
- [QuantLib](https://github.com/lballabio/QuantLib) - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.
- QuantLibRisks - Fast risks with QuantLib in [Python](https://pypi.org/project/QuantLib-Risks/) and [C++](https://github.com/auto-differentiation/QuantLib-Risks-Cpp)
- XAD - Automatic Differentiation (AAD) Library in [Python](https://pypi.org/project/xad/) and [C++](https://github.com/auto-differentiation/xad/)
- [JQuantLib](https://github.com/frgomes/jquantlib) - Java port.
- [RQuantLib](https://github.com/eddelbuettel/rquantlib) - R port.
- [QuantLibAddin](https://www.quantlib.org/quantlibaddin/) - Excel support.
@@ -458,11 +466,12 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [PyQL](https://github.com/enthought/pyql) - Python port.
- [QuantLib.jl](https://github.com/pazzo83/QuantLib.jl) - Julia port.
- [QuantLib-Python Documentation](https://quantlib-python-docs.readthedocs.io/) - Documentation for the Python bindings for the QuantLib library
- [QuantLib with Automatic Differention enabled](https://github.com/auto-differentiation/quantlib-xad) - Integration of Automatic Differentiation with the QuantLib library
- [TA-Lib](https://ta-lib.org) - perform technical analysis of financial market data.
- [ta-lib-python](https://github.com/TA-Lib/ta-lib-python)
- [ta-lib](https://github.com/TA-Lib/ta-lib)
- [Portfolio Optimizer](https://portfoliooptimizer.io/) - Portfolio Optimizer is a Web API for portfolio analysis and optimization.
- XAD: Automatic Differentation (AAD) Library for [Python](https://pypi.org/project/xad/) and [C++](https://github.com/auto-differentiation/xad)
## CSharp
@@ -484,6 +493,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
## Reproducing Works, Training & Books
- [Auto-Differentiation Website](https://auto-differentiation.github.io/) - Background and resources on Automatic Differentiation (AD) / Adjoint Algorithmic Differentitation (AAD).
- [Derman Papers](https://github.com/MarcosCarreira/DermanPapers) - Notebooks that replicate original quantitative finance papers from Emanuel Derman.
- [ML-Quant](https://www.ml-quant.com/) - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.
- [volatility-trading](https://github.com/jasonstrimpel/volatility-trading) - A complete set of volatility estimators based on Euan Sinclair's Volatility Trading.