TY - JOUR
T1 - Enhancing portfolio performance and VIX futures trading timing with markov-switching GARCH models
AU - De la Torre-Torres, Oscar V.
AU - Venegas-Martínez, Francisco
AU - Martínez-Torre-enciso, Ma Isabel
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/1/2
Y1 - 2021/1/2
N2 - 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.
AB - 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.
KW - Active investment
KW - Diversification
KW - Institutional investors
KW - Markov-Switching
KW - Markov-Switching GARCH
KW - Portfolio man-agement
KW - VIX
KW - Volatility futures
KW - Volatility hedging
UR - http://www.scopus.com/inward/record.url?scp=85099815920&partnerID=8YFLogxK
U2 - 10.3390/math9020185
DO - 10.3390/math9020185
M3 - Artículo
AN - SCOPUS:85099815920
SN - 2227-7390
VL - 9
SP - 1
EP - 23
JO - Mathematics
JF - Mathematics
IS - 2
M1 - 185
ER -