Introductory Econometrics for Finance 4/e 作者：Chris Brooks 原價：NT$ 1,650 ISBN：9781108436823 版次：4 年份：2019 出版商：Cambridge University 頁數/規格：728頁/平裝彩色 內容簡介 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 on the main chapter takeaways and allow students to self-assess their understanding. On include extensive teacher and student support materials, including EViews, Stata, R, and Python software guides. 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 目錄 Table of Contents 1. Introduction and mathematical foundations 2. Statistical foundations and dealing with data 3. A brief overview of the classical regression model 4. Further development and analysis of classical regression model 5. Classical 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