Heterogeneous Markov-Switching GARCH Models for U.S. Tourism Active Stock Trading

Oscar V. De la Torre-Torres; José Álvarez-García; María de la Cruz del Río-Rama; Francisco J. Fernández-González

doi:10.3390/math14071200

journal article Open Access Apr 03, 2026

Heterogeneous Markov-Switching GARCH Models for U.S. Tourism Active Stock Trading

Oscar V. De la Torre-Torres José Álvarez-García

María de la Cruz del Río-Rama

Francisco J. Fernández-González

Mathematics Vol. 14 No. 7 pp. 1200 · MDPI AG

View at Publisher Save 10.3390/math14071200

Abstract

This paper tests the benefits of using heterogeneous Markov-Switching GARCH (MS-GARCH) models for active trading of tourism (leisure and entertainment) stocks by performing a weekly backtest of the 36 combinations of two-regime MS-GARCH models, given their regime-specific marginal probability (Gaussian and Student-t). Their regime-specific variance model (time-fixed, symmetric GARCH, or asymmetric EGARCH), and by assuming a two-regime context with a low (high)-volatility regime s = 1 (s = 2), the results suggest that using an MS-GARCH model with a Student-t pdf and a symmetric GARCH variance in s = 1, and a Gaussian pdf with a time-fixed variance in s = 2, leads to a better performance than a buy-and-hold strategy (with a compound annual growth rate, or CAGR, of 10.0716% and an annualized Sharpe ratio of 5.0891). This performance reflects the impact of a 0.1% trading fee per traded amount and a 10% tax. This result suggests that, only in the short term, MS-GARCH models are useful for active trading in tourism stocks by portfolio managers and could be used to forecast high-volatility episodes in such companies, which are prone to price declines during sanitary, geopolitical, or consumer-sentiment crises. Despite this in-sample result, it is important to highlight that the results do not hold in the long term, as tested for randomness in the backtest results (data snooping), and that further improvements must be made to the algorithm to generate a significant overperformance of the trading strategy.

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Details

Published: Apr 03, 2026
Vol/Issue: 14(7)
Pages: 1200
License: View

Authors

O

Oscar V. De la Torre-Torres

Faculty of Accounting and Management Sciences, Universidad Michoacana de San Nicolás de Hidalgo (UMSNH), Morelia 58000, Mexico

J

José Álvarez-García

Departamento de Economía Financiera y Contabilidad, Instituto Universitario de Investigación para el Desarrollo Territorial Sostenible (INTERRA), Universidad de Extremadura, 10071 Cáceres, Spain

M

María de la Cruz del Río-Rama

Business Management and Marketing Department, Faculty of Business Sciences and Tourism, University of Vigo, 32004 Ourense, Spain

F

Francisco J. Fernández-González

Doctoral Program in Sustainable Territorial Development (R015), The International Doctoral School, University of Extremadura, 06006 Badajoz, Spain

Cite This Article

Oscar V. De la Torre-Torres, José Álvarez-García, María de la Cruz del Río-Rama, et al. (2026). Heterogeneous Markov-Switching GARCH Models for U.S. Tourism Active Stock Trading. Mathematics, 14(7), 1200. https://doi.org/10.3390/math14071200

Heterogeneous Markov-Switching GARCH Models for U.S. Tourism Active Stock Trading

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