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Prediction of Conditional Variance under GARCH Model Based on Bootstrap Methods
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 Title & Authors
Prediction of Conditional Variance under GARCH Model Based on Bootstrap Methods
Kim, Hee-Young; Park, Man-Sik;
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In terms of generalized autoregressive conditional heteroscedastic(GARCH) model, estimation of prediction interval based on likelihood is quite sensitive to distribution of error. Moveover, it is not an easy job to construct prediction interval for conditional variance. Recent studies show that the bootstrap method can be one of the alternatives for solving the problems. In this paper, we introduced the bootstrap approach proposed by Pascual et al. (2006). We employed it to Korean stock price data set.
Bootstrap;GARCH;conditional variance;
 Cited by
박만식, 김나영, 김희영 (2008). Clustering Korean stock return data based on GARCH model, <한국통계학회논문집>, 15, 925-937

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