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Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)

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  • Oscar V. De la Torre-Torres

    (Facultad de Contaduría y Ciencias Administrativas, Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Morelia 58000, Mexico
    These authors contributed equally to this work.)

  • Evaristo Galeana-Figueroa

    (Facultad de Contaduría y Ciencias Administrativas, Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Morelia 58000, Mexico
    These authors contributed equally to this work.)

  • María de la Cruz Del Río-Rama

    (Business Management and Marketing Department, Faculty of Business Sciences and Tourism, University of Vigo, 32004 Ourense, Spain
    These authors contributed equally to this work.)

  • José Álvarez-García

    (Departamento de Economía Financiera y Contabilidad, Instituto Universitario de Investigación para el Desarrollo Territorial Sostenible (INTERRA), Facultad de Empresa Finanzas y Turismo, Universidad de Extremadura, Avd. de la Universidad, n° 47, 10071 Caceres, Spain
    These authors contributed equally to this work.)

Abstract

In this study, we tested the benefit of using Markov-Switching (M-S) models to forecast the views of the 26 most traded stocks in the US in a Black–Litterman (B–L) optimal selection context. With weekly historical data of these stocks from 1 January 1980, we estimated and simulated (from 7 January 2000, to 7 February 2022) three portfolios that used M-S views in each stock and blended them with the market equilibrium views in a B–L context. Our position was that the B–L optimal portfolios could generate alpha (extra return) against a buy-and-hold and an actively managed portfolio with sample portfolio parameters (à la Markowitz, SampP). Our results suggest that the outperformance of the B–L managed portfolios holds only in the short term. In the long-term, the performance of the B–L portfolios, the SampP, and the market portfolio are statistically equal in terms of returns or their mean–variance efficiency in an ex-ante or ex-post analysis.

Suggested Citation

  • Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & María de la Cruz Del Río-Rama & José Álvarez-García, 2022. "Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)," Mathematics, MDPI, vol. 10(8), pages 1-28, April.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:8:p:1296-:d:793207
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