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

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  • Shi, Yanlin

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.

Suggested Citation

  • Shi, Yanlin, 2022. "A closed-form estimator for the Markov switching in mean model," Finance Research Letters, Elsevier, vol. 44(C).
    • Handle: RePEc:eee:finlet:v:44:y:2022:i:c:s1544612321001884
    DOI: 10.1016/j.frl.2021.102107
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    References listed on IDEAS

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    More about this item

    Keywords

    Markov switching; Moments; Yale–Walker equations; Closed-form estimator;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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