New volatility models under a Bayesian perspective: a case study
In this paper, we present a brief description of ARCH, GARCH and EGARCH models. Usually, their parameter estimates are obtained using maximum likelihood methods. Considering new methodological processes to model the volatilities of time series, we need to use other inference approach to get estimate...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Portuguese |
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Universidade de São Paulo
2014-06-01
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| Series: | Economia Aplicada |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-80502014000200001&lng=en&tlng=en |
| _version_ | 1818841037517357056 |
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| author | Edilberto Cepeda Cuervo Jorge Alberto Achcar Milton Barossi-Filho |
| author_facet | Edilberto Cepeda Cuervo Jorge Alberto Achcar Milton Barossi-Filho |
| author_sort | Edilberto Cepeda Cuervo |
| collection | DOAJ |
| description | In this paper, we present a brief description of ARCH, GARCH and EGARCH models. Usually, their parameter estimates are obtained using maximum likelihood methods. Considering new methodological processes to model the volatilities of time series, we need to use other inference approach to get estimates for the parameters of the models, since we can encouter great difficulties in obtaining the maximum likelihood estimates due to the complexity of the likelihood function. In this way, we obtain the inferences for the volatilities of time series under a Bayesian approach, especially using popular simulation algorithms such as the Markov Chain Monte Carlo (MCMC) methods. As an application to illustrate the proposed methodology, we analyze a financial time series of the Gillette Company ranging from January, 1999 to May, 2003. |
| first_indexed | 2024-12-19T04:19:43Z |
| format | Article |
| id | doaj.art-4c58e5e3e2f54ac7bb99e882359f29a9 |
| institution | Directory Open Access Journal |
| issn | 1980-5330 |
| language | Portuguese |
| last_indexed | 2024-12-19T04:19:43Z |
| publishDate | 2014-06-01 |
| publisher | Universidade de São Paulo |
| record_format | Article |
| series | Economia Aplicada |
| spelling | doaj.art-4c58e5e3e2f54ac7bb99e882359f29a92022-12-21T20:36:12ZporUniversidade de São PauloEconomia Aplicada1980-53302014-06-0118217919710.1590/1413-8050/ea91S1413-80502014000200001New volatility models under a Bayesian perspective: a case studyEdilberto Cepeda Cuervo0Jorge Alberto Achcar1Milton Barossi-Filho2Universidad Nacional de ColombiaUniversidade de São PauloUniversidade de São PauloIn this paper, we present a brief description of ARCH, GARCH and EGARCH models. Usually, their parameter estimates are obtained using maximum likelihood methods. Considering new methodological processes to model the volatilities of time series, we need to use other inference approach to get estimates for the parameters of the models, since we can encouter great difficulties in obtaining the maximum likelihood estimates due to the complexity of the likelihood function. In this way, we obtain the inferences for the volatilities of time series under a Bayesian approach, especially using popular simulation algorithms such as the Markov Chain Monte Carlo (MCMC) methods. As an application to illustrate the proposed methodology, we analyze a financial time series of the Gillette Company ranging from January, 1999 to May, 2003.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-80502014000200001&lng=en&tlng=enARCHGARCHEGARCHModelos de Volatilidade EstocásticaSeries de tempo FinancierasMétodos BayesianosMétodos de MCMC |
| spellingShingle | Edilberto Cepeda Cuervo Jorge Alberto Achcar Milton Barossi-Filho New volatility models under a Bayesian perspective: a case study Economia Aplicada ARCH GARCH EGARCH Modelos de Volatilidade Estocástica Series de tempo Financieras Métodos Bayesianos Métodos de MCMC |
| title | New volatility models under a Bayesian perspective: a case study |
| title_full | New volatility models under a Bayesian perspective: a case study |
| title_fullStr | New volatility models under a Bayesian perspective: a case study |
| title_full_unstemmed | New volatility models under a Bayesian perspective: a case study |
| title_short | New volatility models under a Bayesian perspective: a case study |
| title_sort | new volatility models under a bayesian perspective a case study |
| topic | ARCH GARCH EGARCH Modelos de Volatilidade Estocástica Series de tempo Financieras Métodos Bayesianos Métodos de MCMC |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-80502014000200001&lng=en&tlng=en |
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