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Modelling stock market volatility = bridging the gap to continuous time /

紀錄類型:	書目-電子資源 : 單行本
正題名/作者:	Modelling stock market volatility/ edited by Peter E. Rossi.
其他題名:	bridging the gap to continuous time /
其他作者:	Rossi, Peter E.
出版者:	San Diego :Academic Press, : c1996.,
面頁冊數:	1 online resource (xviii, 485 p.) :ill. :
附註:	Description based on print version record.
標題:	Stocks - Prices -
電子資源:	An electronic book accessible through the World Wide Web; click for information
ISBN:	9780080511870 (electronic bk.)

Modelling stock market volatility = bridging the gap to continuous time /
Modelling stock market volatilitybridging the gap to continuous time /[electronic resource] :edited by Peter E. Rossi. - San Diego :Academic Press,c1996. - 1 online resource (xviii, 485 p.) :ill.

Description based on print version record.

Includes bibliographical references and index.

Modelling Stock Market Volatility Changes -- Stationarity and Persistence in the GARCH(I,I) Model -- Conditional Heteroskedasticity in Asset Returns: A New Approach -- Good News, Bad News, Volatility, and Betas -- ARCH Models as Diffusion Approximations -- Filtering and Forecasting with Misspecified ARCH Models I: Getting the Right Variance with the Wrong Model -- Filtering and Forecasting with Misspecified ARCH Models II: Making the Right Forecast with the Wrong Model -- Asymptotic Filtering Theory for Univariate ARCH Models -- Asymptotic Filtering Theory for Multivariate ARCH Models -- Continuous Record Asymptotics for Rolling Sample Variance Estimators -- Estimating Diffusion Models of Stochastic Volatility -- Specification Analysis of Continuous Time Models in Finance -- Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes -- Nonparametric Pricing of Interest Rate Derivative Securities -- Index.

This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH) models and applications. For the first time, Modelling Stock Market Volatility provides new insights about the links between these two models and new work on practical estimation methods for continuous time models. Featuring the pioneering scholarship of Daniel Nelson, the text presents research about the discrete time model, continuous time limits and optimal filtering of ARCH models, and the specification and estimation of continuous time processes. This work will lead to a rapid growth in their empirical application as they are increasingly subjected to routine specification testing. Key Features * Provides for the first time new insights on the links between continuous time and ARCH models * Collects seminal scholarship by some of the most renowned researchers in finance and econometrics * Captures complex arguments underlying the approximation and proper statistical modelling of continuous time volatility dynamics.

ISBN: 9780080511870 (electronic bk.)Subjects--Topical Terms:

131705
Stocks
--PricesIndex Terms--Genre/Form:

96803
Electronic books.

LC Class. No.: HG4636 / .M63 1996eb

Dewey Class. No.: 332.63/222

Modelling stock market volatility = bridging the gap to continuous time /
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245 0 0 $a Modelling stock market volatility $h [electronic resource] : $b bridging the gap to continuous time / $c edited by Peter E. Rossi.
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500 $a Description based on print version record.
504 $a Includes bibliographical references and index.
505 0 $a Modelling Stock Market Volatility Changes -- Stationarity and Persistence in the GARCH(I,I) Model -- Conditional Heteroskedasticity in Asset Returns: A New Approach -- Good News, Bad News, Volatility, and Betas -- ARCH Models as Diffusion Approximations -- Filtering and Forecasting with Misspecified ARCH Models I: Getting the Right Variance with the Wrong Model -- Filtering and Forecasting with Misspecified ARCH Models II: Making the Right Forecast with the Wrong Model -- Asymptotic Filtering Theory for Univariate ARCH Models -- Asymptotic Filtering Theory for Multivariate ARCH Models -- Continuous Record Asymptotics for Rolling Sample Variance Estimators -- Estimating Diffusion Models of Stochastic Volatility -- Specification Analysis of Continuous Time Models in Finance -- Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes -- Nonparametric Pricing of Interest Rate Derivative Securities -- Index.
520 $a This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH) models and applications. For the first time, Modelling Stock Market Volatility provides new insights about the links between these two models and new work on practical estimation methods for continuous time models. Featuring the pioneering scholarship of Daniel Nelson, the text presents research about the discrete time model, continuous time limits and optimal filtering of ARCH models, and the specification and estimation of continuous time processes. This work will lead to a rapid growth in their empirical application as they are increasingly subjected to routine specification testing. Key Features * Provides for the first time new insights on the links between continuous time and ARCH models * Collects seminal scholarship by some of the most renowned researchers in finance and econometrics * Captures complex arguments underlying the approximation and proper statistical modelling of continuous time volatility dynamics.
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