Forecasting Markov-switching dynamic, conditionally heteroscedastic processes
Davidson, James
Date: 22 April 2004
Journal
Statistics & Probability Letters
Publisher
Elsevier
Publisher DOI
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 ...
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.
Economics
Faculty of Environment, Science and Economy
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