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@@ -277,7 +277,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [xts](https://github.com/joshuaulrich/xts) - eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
- [data.table](https://github.com/Rdatatable/data.table) - Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.
- [sparseEigen](https://github.com/dppalomar/sparseEigen) - Sparse pricipal component analysis.
- [sparseEigen](https://github.com/dppalomar/sparseEigen) - Sparse principal component analysis.
- [TSdbi](http://tsdbi.r-forge.r-project.org/) - Provides a common interface to time series databases.
- [tseries](https://cran.r-project.org/web/packages/tseries/index.html) - Time Series Analysis and Computational Finance.
- [zoo](https://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).
@@ -498,7 +498,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [Quantitative-Notebooks](https://github.com/LongOnly/Quantitative-Notebooks) - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
- [QuantEcon](https://quantecon.org/) - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks
- [FinanceHub](https://github.com/Finance-Hub/FinanceHub) - Resources for Quantitative Finance
- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
- [Python_Option_Pricing](https://github.com/dedwards25/Python_Option_Pricing) - An library to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
- [python-training](https://github.com/jpmorganchase/python-training) - J.P. Morgan's Python training for business analysts and traders.
- [Stock_Analysis_For_Quant](https://github.com/LastAncientOne/Stock_Analysis_For_Quant) - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.
- [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - Source code for Algorithmic Trading with Python (2020) by Chris Conlan.
@@ -535,4 +535,4 @@ A curated list of insanely awesome libraries, packages and resources for Quants
- [book_irds3](https://github.com/attack68/book_irds3) - Code repository for Pricing and Trading Interest Rate Derivatives.
- [Autoencoder-Asset-Pricing-Models](https://github.com/RichardS0268/Autoencoder-Asset-Pricing-Models) - Reimplementation of Autoencoder Asset Pricing Models ([GKX, 2019](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3335536)).
- [Finance](https://github.com/shashankvemuri/Finance) - 150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data.
- [101_formulaic_alphas](https://github.com/ram-ki/101_formulaic_alphas) - Implemention of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader.
- [101_formulaic_alphas](https://github.com/ram-ki/101_formulaic_alphas) - Implementation of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader.