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...
Otros Autores: | |
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Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
San Diego :
Academic Press
c1996.
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Materias: | |
Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009633568106719 |
Sumario: | 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. |
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Descripción Física: | 1 online resource (xviii, 485 pages) : illustrations |
Bibliografía: | Includes bibliographical references and index. |
ISBN: | 9781282284821 9786612284823 9780080511870 |