Python Guide to Accompany Introductory Econometrics for Finance
175 Pages Posted: 5 Nov 2019 Last revised: 9 Nov 2021
Date Written: October 25, 2019
This free software guide for Python with freely downloadable datasets brings the econometric techniques to life, showing readers how to implement the approaches presented in Introductory Econometrics for Finance using this highly popular software package. Designed to be used alongside the main textbook, the guide will give readers the confidence and skills to estimate and interpret their own models while the textbook will ensure that they have a thorough understanding of the conceptual underpinnings. guide draws on material from ‘Introductory Econometrics for Finance’, published by Cambridge University Press, Chris Brooks (2019). The Guide is intended to be used alongside the book, and page numbers from the book are given after each section and subsection heading.
Code and data sets are available at https://www.cambridge.org/gb/academic/subjects/economics/finance/introductory-econometrics-finance-4th-edition?format=PB&isbn=9781108422536
Keywords: Python, financial econometrics, education, programming in finance
JEL Classification: C01
Suggested Citation: Suggested Citation