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Robust multivariate and nonlinear time series models: Application of robust estimators for the vector autoregressive and bilinear time series models - Softcover
Inhaltsangabe
Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables like indices and stock prices and global variables like commodity prices are more tightly coupled than ever before. This translates to the use of multivariate or vector time series models and algorithms in analyzing and understanding the relationships that these variables share with each other. While robustness and time series modeling have been vastly researched individually in the past, application of robust methods to estimate time series models is still quite open. The central goal of this thesis is the study of the S-estimator, a robust estimator, applied to some simple vector and nonlinear time series models. In each case, we will look at the important aspect of stationarity of the model and analyze the asymptotic behavior of the S-estimator.
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Reseña del editor
Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables like indices and stock prices and global variables like commodity prices are more tightly coupled than ever before. This translates to the use of multivariate or vector time series models and algorithms in analyzing and understanding the relationships that these variables share with each other. While robustness and time series modeling have been vastly researched individually in the past, application of robust methods to estimate time series models is still quite open. The central goal of this thesis is the study of the S-estimator, a robust estimator, applied to some simple vector and nonlinear time series models. In each case, we will look at the important aspect of stationarity of the model and analyze the asymptotic behavior of the S-estimator.
Biografía del autor
Dr. Ravi Ramakrishnan completed his Ph.D in Mathematics from the Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland. Presently, he works with Banque Cantonale Vaudoise (BCV), Lausanne, Switzerland, as a Quantitative Investment manager where he builds trading strategies using quantitative techniques.
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Robust multivariate and nonlinear time series models: Application of robust estimators for the vector autoregressive and bilinear time series models
Verlag:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843357811
ISBN 13: 9783843357814
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Softcover
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Robust multivariate and nonlinear time series models
Verlag:
LAP LAMBERT Academic Publishing Okt 2010, 2010
ISBN 10: 3843357811
ISBN 13: 9783843357814
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Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables like indices and stock prices and global variables like commodity prices are more tightly coupled than ever before. This translates to the use of multivariate or vector time series models and algorithms in analyzing and understanding the relationships that these variables share with each other. While robustness and time series modeling have been vastly researched individually in the past, application of robust methods to estimate time series models is still quite open. The central goal of this thesis is the study of the S-estimator, a robust estimator, applied to some simple vector and nonlinear time series models. In each case, we will look at the important aspect of stationarity of the model and analyze the asymptotic behavior of the S-estimator.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch. Artikel-Nr. 9783843357814
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