
Tidy Finance with R
by Christoph Scheuch, Stefan Voigt, Patrick Weiss
1st Edition
Publisher: Chapman and Hall/CRC
Book Details
| Print ISBN | 9781032389332 |
| eText ISBN | 9781000858785 |
| Publisher | Chapman and Hall/CRC |
| Publishing Year | 2023 |
| Edition | 1st Edition |
| Language | English |
| Pages | 268 |
Tidy Finance with R, 1st Edition, is a textbook that connects theoretical concepts from finance and econometrics directly to data. The text introduces empirical finance research from scratch using the R programming language and the tidyverse package ecosystem.
Core coverage examines financial data management, empirical asset pricing, econometric modeling, machine learning, and portfolio optimization. The text explains tidy data principles and demonstrates how to assemble open-source and proprietary datasets into an organized database reused across analytical projects.
Designed for university courses and independent research, the volume provides self-contained workflows that support reproducible empirical investigations. Each chapter includes practice exercises derived from university lectures to assist students and instructors.
Table of Contents
Chapter 1: Introduction to Tidy Finance
Chapter 2: Accessing & Managing Financial Data
Chapter 3: WRDS, CRSP, and Compustat
Chapter 4: TRACE and FISD
Chapter 5: Other Data Providers
Chapter 6: Beta Estimation
Chapter 7: Univariate Portfolio Sorts
Chapter 8: Size Sorts and p-Hacking
Chapter 9: Value and Bivariate Sorts
Chapter 10: Replicating Fama and French Factors
Chapter 11: Fama-MacBeth Regressions
Chapter 12: Fixed Effects and Clustered Standard Errors
Chapter 13: Difference in Differences
Chapter 14: Factor Selection via Machine Learning
Chapter 15: Option Pricing via Machine Learning
Chapter 16: Parametric Portfolio Policies
Chapter 17: Constrained Optimization and Backtesting
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