A closed-form estimator for the Markov switching in mean model

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Abstract

This paper revisits the Markov switching in mean model which is commonly fitted by maximizing its log-likelihood. To effectively resolve the computational complexity caused by the nolinear nature and iterative components in the log-likelihood, we propose a closed-form solution inspired by moment-based and Yule-Walker methods. Associated asymptotics are discussed with numerical evidence. For practical considerations, we demonstrate the usefulness of the proposed estimates when supplied as initial values to obtain the usual maximum likelihood estimates for reliable statistical inferences.
Original languageEnglish
Article number102107
Pages (from-to)1-7
Number of pages7
JournalFinance Research Letters
Volume44
Early online date3 May 2021
DOIs
Publication statusPublished - Jan 2022

Keywords

  • Closed-form estimator
  • Markov switching
  • Moments
  • Yale–Walker equations

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