Financial Econometrics: From Basics to Advanced Modeling Techniques
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BeschreibungFinancial econometrics combines mathematical and statistical theory and techniques to understand and solve problems in financial economics. Modeling and forecasting financial time series, such as prices, returns, interest rates, financial ratios, and defaults, are important parts of this field.
In Financial Econometrics, you'll be introduced to this growing discipline and the concepts associated with it--from background material on probability theory and statistics to information regarding the properties of specific models and their estimation procedures.
With this book as your guide, you'll become familiar with:
* Autoregressive conditional heteroskedasticity (ARCH) and GARCH modeling
* Principal components analysis (PCA) and factor analysis
* Stable processes and ARMA and GARCH models with fat-tailed errors
* Robust estimation methods
* Vector autoregressive and cointegrated processes, including advanced estimation methods for cointegrated systems
* And much more
The experienced author team of Svetlozar Rachev, Stefan Mittnik, Frank Fabozzi, Sergio Focardi, and Teo Jasic not only presents you with an abundant amount of information on financial econometrics, but they also walk you through a wide array of examples to solidify your understanding of the issues discussed.
Filled with in-depth insights and expert advice, Financial Econometrics provides comprehensive coverage of this discipline and clear explanations of how the models associated with it fit into today's investment management process.
Abbreviations and Acronyms.
About the Authors.
CHAPTER 1: Financial Econometrics: Scope and Methods.
CHAPTER 2: Review of Probability and Statistics.
CHAPTER 3: Regression Analysis: Theory and Estimation.
CHAPTER 4: Selected Topics in Regression Analysis.
CHAPTER 5: Regression Applications in Finance.
CHAPTER 6: Modeling Univariate Time Series.
CHAPTER 7: Approaches to ARIMA Modeling and Forecasting.
CHAPTER 8: Autoregressive Conditional Heteroskedastic Models.
CHAPTER 9: Vector Autoregressive Models I.
CHAPTER 10: Vector Autoregressive Models II.
CHAPTER 11: Cointegration and State Space Models.
CHAPTER 12: Robust Estimation.
CHAPTER 13: Principal Components Analysis and Factor Analysis.
CHAPTER 14: Heavy-Tailed and Stable Distributions in Financial Econometrics.
CHAPTER 15: ARMA and ARCH Models with Infinite-Variance Innovations.
APPENDIX: Monthly Returns for 20 Stocks: December 2000-November 2005.
PortraitSvetlozar T. Rachev, PhD, is Chair-Professor at the University of Karlsruhe in the School of Economics and Business Engineering, Professor Emeritus at the University of California, Santa Barbara, and Chief Scientist of FinAnalytica.
Stefan Mittnik is Professor of Financial Econometrics at the University of Munich, Research Director at the Ifo Institute for Economic Research in Munich, and Director of the Risk Management Program at the Center for Financial Studies in Frankfurt, Germany.
Frank J. Fabozzi, PhD, CFA, CFP, is an Adjunct Professor of Finance at Yale University's School of Management and the Editor of the Journal of Portfolio Management.
Sergio M. Focardi is a founding partner of the Paris-based consulting firm, The Intertek Group.
Teo Jasic, PhD, is a senior manager with a leading international management consultancy firm in Frankfurt, Germany, and a Post-Doctoral Research Fellow at the Chair of Statistics, Econometrics, and Mathematical Finance at the University of Karlsruhe, Germany.
Untertitel: From Basics to Advanced Modeling Techniques. 'Frank J. Fabozzi'. New. Sprache: Englisch.
Verlag: JOHN WILEY & SONS INC
Erscheinungsdatum: Januar 2007
Seitenanzahl: 576 Seiten