Tidy Finance with R – PDF

Tidy Finance with R – PDF

This textbook Tidy Finance with R demonstrates how to apply theoretical concepts from finance and econometrics to real-world data. By emphasizing coding and data analysis in R, we guide readers through the process of conducting empirical finance research from the ground up. We begin by introducing the principles of tidy data and essential coding practices using the tidyverse family of R packages. Comprehensive code is provided to prepare various common open-source and proprietary financial data sources—including CRSP, Compustat, Mergent FISD, and TRACE—and organize them into a cohesive database. These datasets are utilized consistently throughout the subsequent chapters, which are designed to be self-contained.

The empirical applications span critical aspects of asset pricing—such as beta estimation, portfolio sorts, and performance analysis involving Fama-French factors—and extend to modeling and machine learning applications including fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic Net, random forests, neural networks, and portfolio optimization techniques.

Key features include:

– Self-contained chapters that cover the most vital applications and methodologies in finance, making them easily applicable for readers’ research or serving as references for empirical finance courses.
– Each chapter is reproducible, allowing readers to replicate every figure, table, or numerical result by simply copying and pasting the provided code.
– A comprehensive introduction to machine learning with tidy models grounded in tidy principles, illustrating how factor selection and option pricing can leverage machine learning techniques.
– Chapter 2 focuses on accessing and managing financial data, detailing how to retrieve and prepare essential datasets in financial economics, specifically CRSP and Compustat, along with thorough explanations of their key data characteristics.
– Each chapter includes exercises based on well-established lectures designed to encourage deeper exploration, serving as valuable resources for self-study or inspiration for educational contexts.

978-1000858785, 978-1003347538, 978-1032389349, 978-1000858716, 978-1032389332

NOTE: This only consists of the eBook Tidy Finance with R, 1st Edition in the original PDF format. No access codes are included.