Introductory Econometrics for Finance 4/e
作者:Chris Brooks
原價:NT$ 1,650
內容介紹
目錄
作者介紹
Description
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.
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A complete package for finance students that assumes no prior background in econometrics
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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
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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
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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
Table of Contents
1. Introduction and mathematical foundations
2. Statistical foundations and dealing with data
3. A brief overview of the classical linear regression model
4. Further development and analysis of classical linear regression model
5. Classical linear regression model assumptions and diagnostic tests
6. Univariate time-series modelling and forecasting
7. Multivariate models
8. Modelling long-run relationships in finance
9.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 or doing a project or dissertation in finance
Appendix 1. Sources of data used in this book and the accompanying software manuals
Appendix 2. Tables of statistical distributions
Chris Brooks, University of Reading
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