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

Research output: Contribution to journalArticlepeer-review


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
Early online date3 May 2021
Publication statusPublished - Jan 2022


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


Dive into the research topics of 'A closed-form estimator for the Markov switching in mean model'. Together they form a unique fingerprint.

Cite this