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http://dx.doi.org/10.5351/CKSS.2009.16.2.287

Prediction of Conditional Variance under GARCH Model Based on Bootstrap Methods  

Kim, Hee-Young (Dept. of Biostatistics, Korea Univ.)
Park, Man-Sik (Dept. of Biostatistics, Korea Univ.)
Publication Information
Communications for Statistical Applications and Methods / v.16, no.2, 2009 , pp. 287-297 More about this Journal
Abstract
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.
Keywords
Bootstrap; GARCH; conditional variance;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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