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In contrast to the traditional time series analysis, which focuses on the modeling based on the first two moments, the nonlinear GARCH models specifically take the effect of the higher moments into modeling consideration. This helps to explain and model volatility especially in financial time series. The GARCH models are able to capture financial characteristics such as volatility clustering, heavy tails and asymmetry. In much of the literature available for the GARCH models, the methods of estimating parameters include the MLE,GMM and LSE which have distributional and optimality limitations. In this book, the Optimal Estimating Function(EF) based techniques are derived for the GARCH models. The EF incorporate the Skewness and the Kurtosis moments which are common in financial data. It is shown using simulations that the Estimating Function (EF) method competes reasonably well with the MLE method especially for the non-normal data and hence provides an alternative estimation technique.Financial analysts, Econometricians and Time series scholars will find this book important in teaching and in risk computation.
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Dr. Jesse Mwangi Lectures at Egerton University, Mathematics Dept., Kenya. His research interests are in Time series analysis and Sample surveys.He has authored articles in peer reviewed journals and has co-authored a book 'statistical methods for informational analysis(An introduction)'.He has many years of teaching experience at University level.
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Non-Linear Time Series Models
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LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mwangi JesseDr. Jesse Mwangi Lectures at Egerton University, Mathematics Dept., Kenya. His research interests are in Time series analysis and Sample surveys.He has authored articles in peer reviewed journals and has co-authored a boo. Codice articolo 5146950
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Non-Linear Time Series Models
Editore:
LAP LAMBERT Academic Publishing Nov 2012, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In contrast to the traditional time series analysis, which focuses on the modeling based on the first two moments, the nonlinear GARCH models specifically take the effect of the higher moments into modeling consideration. This helps to explain and model volatility especially in financial time series. The GARCH models are able to capture financial characteristics such as volatility clustering, heavy tails and asymmetry. In much of the literature available for the GARCH models, the methods of estimating parameters include the MLE,GMM and LSE which have distributional and optimality limitations. In this book, the Optimal Estimating Function(EF) based techniques are derived for the GARCH models. The EF incorporate the Skewness and the Kurtosis moments which are common in financial data. It is shown using simulations that the Estimating Function (EF) method competes reasonably well with the MLE method especially for the non-normal data and hence provides an alternative estimation technique.Financial analysts, Econometricians and Time series scholars will find this book important in teaching and in risk computation. 120 pp. Englisch. Codice articolo 9783659302015
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Non-Linear Time Series Models : Parametric Estimation Using Estimating Functions
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In contrast to the traditional time series analysis, which focuses on the modeling based on the first two moments, the nonlinear GARCH models specifically take the effect of the higher moments into modeling consideration. This helps to explain and model volatility especially in financial time series. The GARCH models are able to capture financial characteristics such as volatility clustering, heavy tails and asymmetry. In much of the literature available for the GARCH models, the methods of estimating parameters include the MLE,GMM and LSE which have distributional and optimality limitations. In this book, the Optimal Estimating Function(EF) based techniques are derived for the GARCH models. The EF incorporate the Skewness and the Kurtosis moments which are common in financial data. It is shown using simulations that the Estimating Function (EF) method competes reasonably well with the MLE method especially for the non-normal data and hence provides an alternative estimation technique.Financial analysts, Econometricians and Time series scholars will find this book important in teaching and in risk computation. Codice articolo 9783659302015
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Non-Linear Time Series Models
Editore:
LAP LAMBERT Academic Publishing Nov 2012, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -In contrast to the traditional time series analysis, which focuses on the modeling based on the first two moments, the nonlinear GARCH models specifically take the effect of the higher moments into modeling consideration. This helps to explain and model volatility especially in financial time series. The GARCH models are able to capture financial characteristics such as volatility clustering, heavy tails and asymmetry. In much of the literature available for the GARCH models, the methods of estimating parameters include the MLE,GMM and LSE which have distributional and optimality limitations. In this book, the Optimal Estimating Function(EF) based techniques are derived for the GARCH models. The EF incorporate the Skewness and the Kurtosis moments which are common in financial data. It is shown using simulations that the Estimating Function (EF) method competes reasonably well with the MLE method especially for the non-normal data and hence provides an alternative estimation technique.Financial analysts, Econometricians and Time series scholars will find this book important in teaching and in risk computation.Books on Demand GmbH, Überseering 33, 22297 Hamburg 120 pp. Englisch. Codice articolo 9783659302015
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Non-Linear Time Series Models
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Da: Books Puddle, New York, NY, U.S.A.
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Condizione: New. pp. 120. Codice articolo 26128832219
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Non-Linear Time Series Models
Editore:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Da: Majestic Books, Hounslow, Regno Unito
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Condizione: New. Print on Demand pp. 120 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Codice articolo 131755268
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Non-Linear Time Series Models
Editore:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Da: Biblios, Frankfurt am main, HESSE, Germania
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Condizione: New. PRINT ON DEMAND pp. 120. Codice articolo 18128832209
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Non-Linear Time Series Models: Parametric Estimation Using Estimating Functions
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659302015
ISBN 13: 9783659302015
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Da: Mispah books, Redhill, SURRE, Regno Unito
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Paperback. Condizione: Like New. Like New. book. Codice articolo ERICA79636593020156
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