Forecasting Markov-switching dynamic, conditionally heteroscedastic processes

dc.contributor.author	Davidson, James	en_GB
dc.contributor.department	Cardiff Business School (now at University of Exeter)	en_GB
dc.date.accessioned	2008-06-02T09:37:37Z	en_GB
dc.date.accessioned	2011-01-25T10:25:31Z	en_GB
dc.date.accessioned	2013-03-19T15:57:08Z
dc.date.issued	2004-04-22	en_GB
dc.description.abstract	Recursive formulae are derived for the multi-step point forecasts and forecast standard errors of Markov switching models with ARMA(∞,q) dynamics (including the fractionally integrated case) and conditional heteroscedasticity in ARCH(∞) form. Hamilton's dynamic models of switching mean and variance are also treated, in a slightly modified version of the analysis.	en_GB
dc.identifier.citation	Vol. 68 (2), pp. 137-147	en_GB
dc.identifier.doi	10.1016/j.spl.2004.02.004	en_GB
dc.identifier.uri	http://hdl.handle.net/10036/29296	en_GB
dc.language.iso	en	en_GB
dc.publisher	Elsevier	en_GB
dc.subject	Forecasts	en_GB
dc.subject	Markov-switching	en_GB
dc.subject	ARFIMA	en_GB
dc.subject	ARCH	en_GB
dc.title	Forecasting Markov-switching dynamic, conditionally heteroscedastic processes	en_GB
dc.type	Article	en_GB
dc.date.available	2008-06-02T09:37:37Z	en_GB
dc.date.available	2011-01-25T10:25:31Z	en_GB
dc.date.available	2013-03-19T15:57:08Z
dc.identifier.issn	01677152	en_GB
dc.identifier.journal	Statistics & Probability Letters	en_GB