Multivariate Stochastic Variance Models.
Changes in variance, or volatility, over time can be modeled using the approach based on autoregressive conditional heteroscedasticity. Another approach is to model variance as an unobserved stochastic process. Although it is not easy to obtain the exact likelihood function for such stochastic varia...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
1994
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| _version_ | 1797064407395598336 |
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| author | Harvey, A Ruiz, E Shephard, N |
| author_facet | Harvey, A Ruiz, E Shephard, N |
| author_sort | Harvey, A |
| collection | OXFORD |
| description | Changes in variance, or volatility, over time can be modeled using the approach based on autoregressive conditional heteroscedasticity. Another approach is to model variance as an unobserved stochastic process. Although it is not easy to obtain the exact likelihood function for such stochastic variance models, they tie in closely with developments in finance theory and have certain statistical attractions. This article sets up a multivariate model, discusses its statistical treatment, and shows how it can be modified to capture common movements in volatility in a very natural way. The model is then fitted to daily observations on exchange rates. |
| first_indexed | 2024-03-06T21:13:51Z |
| format | Journal article |
| id | oxford-uuid:3f1798ec-73d9-417b-99ac-c68c49147de3 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T21:13:51Z |
| publishDate | 1994 |
| record_format | dspace |
| spelling | oxford-uuid:3f1798ec-73d9-417b-99ac-c68c49147de32022-03-26T14:29:46ZMultivariate Stochastic Variance Models.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:3f1798ec-73d9-417b-99ac-c68c49147de3EnglishDepartment of Economics - ePrints1994Harvey, ARuiz, EShephard, NChanges in variance, or volatility, over time can be modeled using the approach based on autoregressive conditional heteroscedasticity. Another approach is to model variance as an unobserved stochastic process. Although it is not easy to obtain the exact likelihood function for such stochastic variance models, they tie in closely with developments in finance theory and have certain statistical attractions. This article sets up a multivariate model, discusses its statistical treatment, and shows how it can be modified to capture common movements in volatility in a very natural way. The model is then fitted to daily observations on exchange rates. |
| spellingShingle | Harvey, A Ruiz, E Shephard, N Multivariate Stochastic Variance Models. |
| title | Multivariate Stochastic Variance Models. |
| title_full | Multivariate Stochastic Variance Models. |
| title_fullStr | Multivariate Stochastic Variance Models. |
| title_full_unstemmed | Multivariate Stochastic Variance Models. |
| title_short | Multivariate Stochastic Variance Models. |
| title_sort | multivariate stochastic variance models |
| work_keys_str_mv | AT harveya multivariatestochasticvariancemodels AT ruize multivariatestochasticvariancemodels AT shephardn multivariatestochasticvariancemodels |