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Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/74536

Type: Journal article
Title: Viterbi-based estimation for Markov switching GARCH model
Author: Elliott, R.
Lau, J.
Miao, H.
Siu, T.
Citation: Applied Mathematical Finance, 2012; 19(3):219-231
Publisher: Routledge
Issue Date: 2012
ISSN: 1350-486X
1350-486X
Statement of
Responsibility: 
Robert J. Elliott, John W. Lau, Hong Miao & Tak Kuen Siu
Abstract: We outline a two-stage estimation method for a Markov-switching Generalized Autoregressive Conditional Heteroscedastic (GARCH) model modulated by a hidden Markov chain. The first stage involves the estimation of a hidden Markov chain using the Vitberi algorithm given the model parameters. The second stage uses the maximum likelihood method to estimate the model parameters given the estimated hidden Markov chain. Applications to financial risk management are discussed through simulated data.
Keywords: volatility; regime switching; GARCH; Viterbi algorithm; reference probability; filter; maximum likelihood estimation; value at risk
Rights: ©2012 Taylor & Francis
RMID: 0020122402
DOI: 10.1080/1350486X.2011.620396
Appears in Collections:Mathematical Sciences publications
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