Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/65542
Title: Markov switching beta-skewed-t EGARCH
Authors: Woraphon Yamaka
Paravee Maneejuk
Songsak Sriboonchitta
Keywords: Computer Science
Mathematics
Issue Date: 1-Jan-2019
Abstract: © Springer Nature Switzerland AG 2019. This study extends the work of Harvey and Sucarrat [15] and present Markov regime-switching (MS) Beta-skewed-t-EGARCH (exponential generalized autoregressive conditional heteroscedasticity) model to predict the volatility. To examine the performance of our model, in-sample point forecast precision and AIC and BIC weights are conducted. We study the volatility of five Exchange Traded Fund returns for period from January 2012 to October 2018. Our proposed model is not found to outperform all the other models. However, the dominance of MS-Beta-skewed-t-EGARCH for SPY, VGT, and AGG may support the application of the MS-Beta-skewed-t-EGARCH model for some financial data series.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85064196834&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/65542
ISSN: 16113349
03029743
Appears in Collections:CMUL: Journal Articles

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