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Introductory Econometrics for Finance by Mr. Brooks, Chris: Used
US $31.48
ApproximatelyRM 133.14
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Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages.
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eBay item number:403944431330
Item specifics
- Condition
- Book Title
- Introductory Econometrics for Finance
- Publication Date
- 2019-03-28
- Edition Number
- 4
- Pages
- 724
- ISBN
- 9781108436823
About this product
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
110843682X
ISBN-13
9781108436823
eBay Product ID (ePID)
22038755346
Product Key Features
Number of Pages
724 Pages
Language
English
Publication Name
Introductory Econometrics for Finance
Subject
Finance / General, Econometrics
Publication Year
2019
Features
Revised
Type
Textbook
Subject Area
Business & Economics
Format
Trade Paperback
Dimensions
Item Height
1.1 in
Item Weight
54.5 Oz
Item Length
9.7 in
Item Width
7.4 in
Additional Product Features
Edition Number
4
Intended Audience
College Audience
LCCN
2018-061692
Dewey Edition
23
Reviews
Advance praise: '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 York
Illustrated
Yes
Dewey Decimal
332.01/5195
Edition Description
Revised edition
Table Of Content
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; Glossary; References; Index.
Synopsis
The only econometrics textbook that requires no prior knowledge of the subject, aimed specifically at students of finance, accountancy, or banking. It includes a broad range of techniques, detailed case studies, and explanations of how to implement the techniques and understand the results from the most popular software packages., 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.
LC Classification Number
HG173.B76 2019
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