This textbook Tidy Finance with R demonstrates how to effectively apply theoretical concepts from finance and econometrics to real-world data. Emphasizing coding and data analysis with R, it guides readers through the journey of conducting empirical finance research from the ground up. We begin with essential concepts such as tidy data and coding principles, utilizing the tidyverse collection of R packages. The ebook includes comprehensive code to prepare both common open-source and proprietary financial data sources (such as CRSP, Compustat, Mergent FISD, and TRACE) and organizes them into a cohesive database. These data sets are consistently referenced throughout subsequent chapters, which are designed to be as self-sufficient as possible.
The empirical applications span critical concepts in asset pricing (like beta estimation, portfolio sorting, and performance analysis, including Fama-French factors) to sophisticated modeling and machine learning techniques (such as fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, and neural networks), and portfolio optimization methods.
Key Highlights:
– Comprehensive chapters focused on the most significant applications and methodologies in finance, readily applicable for the reader’s own research or as reference material for empirical finance courses.
– Each chapter is fully reproducible, allowing readers to effortlessly replicate every figure, table, or statistic merely by copying and pasting the provided code.
– A thorough introduction to machine learning using tidymodels based on tidy principles, illustrating how factor selection and option pricing can be enhanced through machine learning techniques.
– Chapter 2 offers guidance on accessing and managing financial data, detailing how to source and prepare essential datasets for financial economics, namely CRSP and Compustat, while explaining their critical characteristics.
– Each chapter includes exercises based on established lectures and classes, encouraging students to explore deeper into the material. These exercises are perfect for self-study or can spark ideas for teaching activities.
978-1032389332, 978-1000858785, 978-1003347538, 978-1032389349, 978-1000858716, 9781003347538, 9781032389349, 9781000858716
NOTE: This only includes Tidy Finance with R, 1st Edition, in original PDF and will also be emailed within 24 hours of payment. No access codes or other media included.
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