From a70ec69a33350f8f02024547cc371df6d04eb6d7 Mon Sep 17 00:00:00 2001 From: Christoph Frey Date: Mon, 9 Sep 2024 10:13:20 +0200 Subject: [PATCH] Update README.md Add Tidy Finance to Reproducing Works, Training & Books and the tidy finance data stream to R Data Sources. --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index f523ede..4d691a1 100644 --- a/README.md +++ b/README.md @@ -305,6 +305,8 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [rbcb](https://github.com/wilsonfreitas/rbcb) - R interface to Brazilian Central Bank web services. - [rb3](https://github.com/ropensci/rb3) - A bunch of downloaders and parsers for data delivered from B3. - [simfinapi](https://github.com/matthiasgomolka/simfinapi) - Makes 'SimFin' data () easily accessible in R. +- [tidyfinance](https://cran.r-project.org/web/packages/tidyfinance/index.html) - Tidy Finance helper functions to download financial data and process the raw data into a structured Format (tidy data), including +date conversion, scaling factor values, and filtering by the specified date. ### Financial Instruments and Pricing @@ -549,3 +551,4 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [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) - Implementation of [101 formulaic alphas](https://arxiv.org/ftp/arxiv/papers/1601/1601.00991.pdf) using qstrader. +- [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.