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Written to complement the second edition of best-selling textbook Introductory Econometrics for Finance, this book provides a comprehensive introduction to the use of the Regression Analysis of Time Series (RATS) software for modelling in finance and beyond. It provides numerous worked examples with carefully annotated code and detailed explanations of the outputs, giving readers the knowledge and confidence to use the software for their own research and to interpret their own results. A wide variety of important modelling approaches are covered, including such topics as time-series analysis and forecasting, volatility modelling, limited dependent variable and panel methods, switching models and simulations methods. The book is supported by an accompanying website containing freely downloadable data and RATS instructions.Read more
- Provides instructions for writing RATS code with detailed annotation allowing readers to follow commands and modify them to apply to their own data and research questions
- Screen captures show how to use menus and fill in wizards
- Includes detailed discussions of outputs from the RATS package giving readers the knowledge and confidence to interpret their own results
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- Date Published: December 2008
- format: Paperback
- isbn: 9780521721684
- length: 213 pages
- dimensions: 246 x 189 x 14 mm
- weight: 0.48kg
- contains: 11 b/w illus.
- availability: In stock
Table of Contents
2. The classical linear regression model
3. Further development and analysis of the classical linear regression model
4. Diagnostic testing
5. Formulating and estimating ARMA models
6. Multivariate models
7. Modelling long-run relationships
8. Modelling volatility and correlation
9. Switching models
10. Panel data
11. Limited dependent variable models
12. Simulations methods
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Instructors have used or reviewed this title for the following courses
- Appled Econometrics for Financial Markets
- Applied Econometrics for Financial Markets
- Behavioral and Quantitative Finance
- Econometrics of Finance
- Time Series Econometrics
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