Author: Tim Peter Bollerslev
Publisher:
ISBN:
Category :
Languages : en
Pages : 124
Book Description
Generalized Autoregressive Conditional Heteroskedasticity with Applications in Finance
Author: Tim Peter Bollerslev
Publisher:
ISBN:
Category :
Languages : en
Pages : 124
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 124
Book Description
Generalized Autoregressive Conditional Heteroskedasticity with Applications in Finance
Author: Tim Bollerslev
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 280
Book Description
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 280
Book Description
Bilinear Generalised Autoregressive Conditional Heteroskedasticity
Author: Nicholas Biekpe
Publisher:
ISBN:
Category : Heteroscedasticity
Languages : en
Pages : 26
Book Description
Publisher:
ISBN:
Category : Heteroscedasticity
Languages : en
Pages : 26
Book Description
Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity
Author: Richard T. Baillie
Publisher:
ISBN:
Category :
Languages : en
Pages : 24
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 24
Book Description
GARCH Models
Author: Christian Francq
Publisher: John Wiley & Sons
ISBN: 1119957397
Category : Mathematics
Languages : en
Pages : 469
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.
Publisher: John Wiley & Sons
ISBN: 1119957397
Category : Mathematics
Languages : en
Pages : 469
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.
Dynamic Models for Volatility and Heavy Tails
Author: Andrew C. Harvey
Publisher: Cambridge University Press
ISBN: 1107034728
Category : Business & Economics
Languages : en
Pages : 281
Book Description
The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.
Publisher: Cambridge University Press
ISBN: 1107034728
Category : Business & Economics
Languages : en
Pages : 281
Book Description
The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.
ARCH Models for Financial Applications
Author: Evdokia Xekalaki
Publisher: John Wiley & Sons
ISBN: 9780470688021
Category : Mathematics
Languages : en
Pages : 558
Book Description
Autoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to model asset price volatility over time. This book introduces both the theory and applications of ARCH models and provides the basic theoretical and empirical background, before proceeding to more advanced issues and applications. The Authors provide coverage of the recent developments in ARCH modelling which can be implemented using econometric software, model construction, fitting and forecasting and model evaluation and selection. Key Features: Presents a comprehensive overview of both the theory and the practical applications of ARCH, an increasingly popular financial modelling technique. Assumes no prior knowledge of ARCH models; the basics such as model construction are introduced, before proceeding to more complex applications such as value-at-risk, option pricing and model evaluation. Uses empirical examples to demonstrate how the recent developments in ARCH can be implemented. Provides step-by-step instructive examples, using econometric software, such as Econometric Views and the G@RCH module for the Ox software package, used in Estimating and Forecasting ARCH Models. Accompanied by a CD-ROM containing links to the software as well as the datasets used in the examples. Aimed at readers wishing to gain an aptitude in the applications of financial econometric modelling with a focus on practical implementation, via applications to real data and via examples worked with econometrics packages.
Publisher: John Wiley & Sons
ISBN: 9780470688021
Category : Mathematics
Languages : en
Pages : 558
Book Description
Autoregressive Conditional Heteroskedastic (ARCH) processes are used in finance to model asset price volatility over time. This book introduces both the theory and applications of ARCH models and provides the basic theoretical and empirical background, before proceeding to more advanced issues and applications. The Authors provide coverage of the recent developments in ARCH modelling which can be implemented using econometric software, model construction, fitting and forecasting and model evaluation and selection. Key Features: Presents a comprehensive overview of both the theory and the practical applications of ARCH, an increasingly popular financial modelling technique. Assumes no prior knowledge of ARCH models; the basics such as model construction are introduced, before proceeding to more complex applications such as value-at-risk, option pricing and model evaluation. Uses empirical examples to demonstrate how the recent developments in ARCH can be implemented. Provides step-by-step instructive examples, using econometric software, such as Econometric Views and the G@RCH module for the Ox software package, used in Estimating and Forecasting ARCH Models. Accompanied by a CD-ROM containing links to the software as well as the datasets used in the examples. Aimed at readers wishing to gain an aptitude in the applications of financial econometric modelling with a focus on practical implementation, via applications to real data and via examples worked with econometrics packages.
Time Series Econometrics
Author: Klaus Neusser
Publisher: Springer
ISBN: 331932862X
Category : Business & Economics
Languages : en
Pages : 421
Book Description
This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.
Publisher: Springer
ISBN: 331932862X
Category : Business & Economics
Languages : en
Pages : 421
Book Description
This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.
Generalized Autoregressive Conditional Heteroscedastic Modeling in Finance
Author: See Tong Lim
Publisher:
ISBN:
Category :
Languages : en
Pages : 182
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 182
Book Description
Handbook of Financial Time Series
Author: Torben Gustav Andersen
Publisher: Springer Science & Business Media
ISBN: 3540712976
Category : Business & Economics
Languages : en
Pages : 1045
Book Description
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Publisher: Springer Science & Business Media
ISBN: 3540712976
Category : Business & Economics
Languages : en
Pages : 1045
Book Description
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.