Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models

Autor: Oscar V. De la Torre-Torres, Francisco Venegas-Martínez, Mᵃ Isabel Martínez-Torre-Enciso
Přispěvatelé: UAM. Departamento de Financiación e Investigación Comercial
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Mathematics
Volume 9
Issue 2
Mathematics, Vol 9, Iss 185, p 185 (2021)
Biblos-e Archivo. Repositorio Institucional de la UAM
instname
ISSN: 2227-7390
DOI: 10.3390/math9020185
Popis: In the present paper, we test the use of Markov-Switching (MS) models with time-fixed or Generalized Autoregressive Conditional Heteroskedasticity (GARCH) variances. This, to enhance the performance of a U.S. dollar-based portfolio that invest in the S&P 500 (SP500) stock index, the 3-month U.S. Treasury-bill (T-BILL) or the 1-month volatility index (VIX) futures. For the investment algorithm, we propose the use of two and three-regime, Gaussian and t-Student, MS and MS-GARCH models. This is done to forecast the probability of high volatility episodes in the SP500 and to determine the investment level in each asset. To test the algorithm, we simulated 8 portfolios that invested in these three assets, in a weekly basis from 23 December 2005 to 14 August 2020. Our results suggest that the use of MS and MS-GARCH models and VIX futures leads the simulated portfolio to outperform a buy and hold strategy in the SP500. Also, we found that this result holds only in high and extreme volatility periods. As a recommendation for practitioners, we found that our investment algorithm must be used only by institutional investors, given the impact of stock trading fees.
This research was funded by the Coordinación de la Investigación Científica at Universidad Michoacana de San Nicolás de Hidalgo and by the Instituto Politécnico Nacional
Databáze: OpenAIRE
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