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Modelling stock market volatility : bridging the gap to continuous time /
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 pract...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
San Diego :
Academic Press,
©1996.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 245 | 0 | 0 | |a Modelling stock market volatility : |b bridging the gap to continuous time / |c edited by Peter E. Rossi. |
| 260 | |a San Diego : |b Academic Press, |c ©1996. | ||
| 300 | |a 1 online resource (xviii, 485 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 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. | ||
| 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. | |
| 588 | 0 | |a Print version record. | |
| 590 | |a eBooks on EBSCOhost |b EBSCO eBook Subscription Academic Collection - Worldwide | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Stocks |x Prices |x Mathematical models. | |
| 650 | 6 | |a Actions (Titres de société) |x Prix |x Modèles mathématiques. | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Investments & Securities |x Stocks. |2 bisacsh | |
| 650 | 7 | |a Stocks |x Prices |x Mathematical models |2 fast | |
| 650 | 1 | 7 | |a Effectenbeurzen. |2 gtt |
| 650 | 1 | 7 | |a Wiskundige modellen. |2 gtt |
| 700 | 1 | |a Rossi, Peter E. |q (Peter Eric), |d 1955- | |
| 776 | 0 | 8 | |i Print version: |t Modelling stock market volatility. |d San Diego : Academic Press, ©1996 |z 9780125982757 |w (DLC) 96026267 |w (OCoLC)34965866 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9780125982757/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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