Introductory econometrics for finance / Chris Brooks , The ICMA Centre, Henley Business School, University of Reading.
Material type: TextPublisher: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2019Copyright date: ©2019Edition: Fourth editionDescription: xxxi, 696 pages ; 25 cmContent type:- text
- unmediated
- volume
- 1108422535
- 9781108422536
- 110843682X
- 9781108436823
- 332.015195 23
- HG173 .B76 2019
Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Book | City Campus City Campus Main Collection | 332.015195 BRO (Browse shelf(Opens below)) | 1 | Available | A538038B | ||
Book | City Campus City Campus Main Collection | 332.015195 BRO (Browse shelf(Opens below)) | 1 | Available | A550307B |
Includes bibliographical references and index.
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 the 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.
"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" -- Provided by Publisher.
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