A Study of the Temporal Aggregation of GARCH Model PDF Download
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Author: Binay Kumar Ray
Publisher:
ISBN:
Category :
Languages : en
Pages : 8
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Book Description
Beginning with the mean variance analysis of portfolio and asset returns, volatility has become central to much of modern finance theory. In recent times, empirical work involving high frequency financial time series data has focused on volatility of asset return. It has been observed that the asset returns exhibit changes, which are not independent over time. Rather, large changes tend to followed by large changes of either sign - small changes tend to be followed by small changes. That is, big shocks are clustered together. GARCH models are used to parameterize conditional heteroskedasticity. It is little known about the impact of temporal aggregation upon GARCH process that conditional heteroskedasticity disappears if the sampling time interval increases to infinity (Drost and Nijman (July 1993). Important applications for persistence variance in GARCH (1,1) model are represented by sum of the coefficients lagged squared disturbance and that of past variance coefficients b1.
Author: Binay Kumar Ray
Publisher:
ISBN:
Category :
Languages : en
Pages : 8
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Book Description
Beginning with the mean variance analysis of portfolio and asset returns, volatility has become central to much of modern finance theory. In recent times, empirical work involving high frequency financial time series data has focused on volatility of asset return. It has been observed that the asset returns exhibit changes, which are not independent over time. Rather, large changes tend to followed by large changes of either sign - small changes tend to be followed by small changes. That is, big shocks are clustered together. GARCH models are used to parameterize conditional heteroskedasticity. It is little known about the impact of temporal aggregation upon GARCH process that conditional heteroskedasticity disappears if the sampling time interval increases to infinity (Drost and Nijman (July 1993). Important applications for persistence variance in GARCH (1,1) model are represented by sum of the coefficients lagged squared disturbance and that of past variance coefficients b1.
Author: Feike C. Drost
Publisher:
ISBN:
Category : Heteroscedasticity
Languages : en
Pages : 54
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Book Description
Author: Andrea Silvestrini
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 68
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Book Description
Author: Christian M. Hafner
Publisher:
ISBN:
Category :
Languages : en
Pages : 43
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Book Description
Author: Christian Francq
Publisher: John Wiley & Sons
ISBN: 1119957397
Category : Mathematics
Languages : en
Pages : 469
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Book Description
This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of standard GARCH models is studied in detail as well as statistical inference such as identification, estimation and tests. The book also provides coverage of several extensions such as asymmetric and multivariate models and looks at financial applications. Key features: Provides up-to-date coverage of the current research in the probability, statistics and econometric theory of GARCH models. Numerous illustrations and applications to real financial series are provided. Supporting website featuring R codes, Fortran programs and data sets. Presents a large collection of problems and exercises. This authoritative, state-of-the-art reference is ideal for graduate students, researchers and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models.
Author: Francis X. Diebold
Publisher:
ISBN:
Category : Interest rates
Languages : en
Pages : 34
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Book Description
Author: John Geweke
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 47
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Author: Andrea Silvestrini
Publisher:
ISBN:
Category :
Languages : en
Pages : 88
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Author: William W. S. Wei
Publisher:
ISBN:
Category :
Languages : en
Pages : 342
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Book Description
Author: Timo Teräsvirta
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
