A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python software guides.Read more
- A complete package for finance students that assumes no prior background in econometrics
- The fundamentals have been broadened into two introductory chapters (one covering mathematics and the other basic statistics) to provide a strong foundation for those new to the subject
- Includes full web support for students and instructors, with datasets, additional chapter questions (with answers provided), lecture slides, support for popular statistical software packages and links to sources of financial data and articles
- Includes worked examples on how to conduct events studies and the Fama–MacBeth method, two of the most common empirical approaches in finance, ensuring that students are well-prepared for econometrics in practice
Reviews & endorsements
'Introductory Econometrics for Finance covers a variety of financial applications and illustrates how econometrics methods can be used for each topic. Researchers and practitioners in finance will find this book invaluable. The new fourth edition is expanded with important topics of state space models and extreme value theory. Moreover, a free companion website with various software programs is essential for performing actual empirical analysis. I constantly recommend this text to Masters and undergraduate finance students.' Elena Goldman, Pace University, New YorkSee more reviews
'This is a good book introducing the general field of financial econometrics to students, assuming they have no prior knowledge of econometrics. Undergraduate, as well as beginning graduate, students should find the wide range of topics covered useful for not only getting a good toehold into the literature, but also to be able to apply the methods to data right away.' Prasad V. Bidarkota, Florida International University
'Professor Brooks’ book provides extraordinarily comprehensive treatment of econometric techniques with application to Finance. The unique feature of this book is the presentation of rich real-world case study examples. This is an ideal text book for MS in Finance, MBA with concentration in Finance and Seniors majoring in Finance. It is also an ideal text book for financial professional training and self-study.' George H. K. Wang, George Mason University, Virginia
'Chris Brooks' book is a rather unique offering in the space of financial econometrics because it is specifically targeted to finance students who do not necessarily have prior knowledge of econometric techniques. It's a first yet comprehensive resource to enable students to familiarize with concepts and tackle a broad range of empirical applications.' Walter Distaso, Imperial College London
'This new edition of Introductory Econometrics for Finance manages to give even further strength to its exhaustive, fine blend of contents and delivery, of methods and of interesting, relevant applications. This classical but always lively written textbook manages to make modern econometric approaches accessible to a wide audience of senior undergraduates and of graduate students first approaching econometrics, and at the same time leads a more experienced reader to ponder the power of statistics through a number of detailed case studies. The additional, advanced material on the Kalman filter and extreme value theory makes this textbook an invaluable classroom tool for a first approach to financial econometrics.' Massimo Guidolin, Università Commerciale Luigi Bocconi, Milan
'This is one of the most readable books on financial econometrics. It will be very useful for students of finance and economics. It covers a wide variety of topics that are of interest to researchers and practitioners, in both academia and industry.' Yong Bao, Purdue University, Indiana
21st Sep 2019 by Lynnie233
It is really useful for my study and I apply the content of the book to the real condition.See all reviews
04th Feb 2020 by Gcc13
This book has become a standard reference for introductory empirical finance at the postgraduate level.
Review was not posted due to profanity×
- Edition: 4th Edition
- Date Published: May 2019
- format: Paperback
- isbn: 9781108436823
- length: 724 pages
- dimensions: 246 x 189 x 27 mm
- weight: 1.54kg
- contains: 98 b/w illus. 132 colour illus. 70 tables
- availability: In stock
Table of Contents
Preface to the fourth edition
1. Introduction and mathematical foundations
2. Statistical foundations and dealing with data
3. A brief overview of the classical linear regression
4. Further development of classical linear regression
5. Classical linear regression model assumptions
6. Univariate time-series modelling and forecasting
7. Multivariate models
8. Modelling volatility and correlation
10. Switching and state space models
11. Panel data
12. Limited dependent variable models
13. Simulation methods
14. Additional econometric techniques for financial research
15. Conducting empirical research
Appendix 1. Sources of data used in this book and the accompanying software manuals
Appendix 2. Tables of statistical distributions
- Solutions to end of chapter questions
- Software guides
- Practice questions
- Video lectures
- Excel files
- EViews workfiles
- EViews program files
- Python code
- R Code
- Stata data and program files
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