Likelihood-based estimation of latent generalised ARCH structures.
GARCH models are commonly used as latent processes in econometrics, financial economics and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the calculation of...
| Váldodahkkit: | , , |
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| Materiálatiipa: | Journal article |
| Giella: | English |
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Wiley
2004
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| _version_ | 1826281139553173504 |
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| author | Fiorentini, G Sentana, E Shephard, N |
| author_facet | Fiorentini, G Sentana, E Shephard, N |
| author_sort | Fiorentini, G |
| collection | OXFORD |
| description | GARCH models are commonly used as latent processes in econometrics, financial economics and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a Bayesian solution in O(T) computational operations, where T denotes the sample size. We assess the performance of our proposed algorithm in the context of both artificial examples and an empirical application to 26 UK sectorial stock returns, and compare it to existing approximate solutions. |
| first_indexed | 2024-03-07T00:24:18Z |
| format | Journal article |
| id | oxford-uuid:7d98c66c-8994-438f-a16b-5b31fc46b070 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T00:24:18Z |
| publishDate | 2004 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:7d98c66c-8994-438f-a16b-5b31fc46b0702022-03-26T21:04:42ZLikelihood-based estimation of latent generalised ARCH structures.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:7d98c66c-8994-438f-a16b-5b31fc46b070EnglishDepartment of Economics - ePrintsWiley2004Fiorentini, GSentana, EShephard, NGARCH models are commonly used as latent processes in econometrics, financial economics and macroeconomics. Yet no exact likelihood analysis of these models has been provided so far. In this paper we outline the issues and suggest a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a Bayesian solution in O(T) computational operations, where T denotes the sample size. We assess the performance of our proposed algorithm in the context of both artificial examples and an empirical application to 26 UK sectorial stock returns, and compare it to existing approximate solutions. |
| spellingShingle | Fiorentini, G Sentana, E Shephard, N Likelihood-based estimation of latent generalised ARCH structures. |
| title | Likelihood-based estimation of latent generalised ARCH structures. |
| title_full | Likelihood-based estimation of latent generalised ARCH structures. |
| title_fullStr | Likelihood-based estimation of latent generalised ARCH structures. |
| title_full_unstemmed | Likelihood-based estimation of latent generalised ARCH structures. |
| title_short | Likelihood-based estimation of latent generalised ARCH structures. |
| title_sort | likelihood based estimation of latent generalised arch structures |
| work_keys_str_mv | AT fiorentinig likelihoodbasedestimationoflatentgeneralisedarchstructures AT sentanae likelihoodbasedestimationoflatentgeneralisedarchstructures AT shephardn likelihoodbasedestimationoflatentgeneralisedarchstructures |