Generalized EGARCH Random Effect Models Application to Financial Time Series |
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Authors: | Edilberto Cepeda-Cuervo |
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Affiliation: | 1. Departamento de Estadística , Universidad Nacional de Colombia , Bogotá , Colombia ecepedac@unal.edu.co |
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Abstract: | In this article, we propose a simple alternative model to analyze the volatility of the financial time series. In the applications, the performance of this model is compared with the performance of the GARCH type models. Using GARCH, EGARCH, and the proposed models, we analyze the time series of the Bovespa and Dow Jones Industrial Average indexes. In the applications we can see that the proposed models have good performance compared with the usual GARCH type model. |
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Keywords: | Bayesian methodology EGARCH models Financial time series GARCH models MCMC methods Volatility models |
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