Tidy Finance with Python – PDF

Tidy Finance with Python – PDF

This textbook Tidy Finance with Python offers a comprehensive guide to translating theoretical concepts from finance and econometrics into practical data applications. By focusing on coding and data analysis with Python, we demonstrate how to conduct empirical finance research from the ground up. We begin with foundational concepts such as tidy data and coding principles utilizing pandas, numpy, and plotnine. The book includes code designed to prepare both open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and to organize them into a coherent database. These datasets are utilized throughout the chapters, which are written to be as self-sufficient as possible.

The empirical applications cover vital topics in asset pricing—such as beta estimation, portfolio sorting, performance analysis, and Fama-French factors—as well as modeling and machine learning techniques, including fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks, and portfolio optimization strategies.

Key Features include:
– Self-contained chapters addressing essential applications and methodologies in finance that are readily applicable in the reader’s research or serve as helpful references for empirical finance courses.
– Each chapter allows readers to reproduce every figure, table, or data point effortlessly by copying and pasting the provided code.
– An in-depth introduction to machine learning using scikit-learn, grounded in tidy data principles, highlighting how these methods enhance factor selection and option pricing.
– Guidance on retrieving and preparing crucial financial datasets such as CRSP and Compustat, complete with thorough explanations of the key data characteristics.
– Exercises aligned with established lectures and classes that encourage deeper exploration, suitable for both self-study and inspiring teaching activities.

978-1040048719, 978-1032684291, 978-1032684307, 978-1040048610

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