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

Author

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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)

  • Francisco Venegas-Martínez

    (Escuela Superior de Economía, Instituto Politécnico Nacional, México 07320, Mexico)

  • Mᵃ Isabel Martínez-Torre-Enciso

    (Facultad de Economía y Ciencias Administrativas, Universidad Autónoma de Madrid, Madrid 28049, Spain)

Abstract

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.

Suggested Citation

  • Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:2:p:185-:d:482359
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    as
    1. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    2. Mehmet Balcilar & Reneé van Eyden & Josine Uwilingiye & Rangan Gupta, 2017. "The Impact of Oil Price on South African GDP Growth: A Bayesian Markov Switching-VAR Analysis," African Development Review, African Development Bank, vol. 29(2), pages 319-336, June.
    3. Jacinto Marabel Romo, 2012. "Volatility Regimes For The Vix Index," Revista de Economia Aplicada, Universidad de Zaragoza, Departamento de Estructura Economica y Economia Publica, vol. 20(2), pages 111-134, Autumn.
    4. Longstaff, Francis A., 1990. "The valuation of options on yields," Journal of Financial Economics, Elsevier, vol. 26(1), pages 97-121, July.
    5. Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(4), pages 493-530.
    6. Boamah, Nicholas Addai & Watts, Edward J. & Loudon, Geoffrey, 2016. "Investigating temporal variation in the global and regional integration of African stock markets," Journal of Multinational Financial Management, Elsevier, vol. 36(C), pages 103-118.
    7. Nelson Areal & Maria Cortez & Florinda Silva, 2013. "The conditional performance of US mutual funds over different market regimes: do different types of ethical screens matter?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(4), pages 397-429, December.
    8. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    9. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    10. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
    11. Chenghan Hou & Bao H. Nguyen, 2018. "Understanding the US natural gas market: A Markov switching VAR approach," CAMA Working Papers 2018-14, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    12. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    13. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    14. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    15. Tomohiro Ando, 2007. "Bayesian predictive information criterion for the evaluation of hierarchical Bayesian and empirical Bayes models," Biometrika, Biometrika Trust, vol. 94(2), pages 443-458.
    16. Klein, Arne C., 2013. "Time-variations in herding behavior: Evidence from a Markov switching SUR model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 291-304.
    17. Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
    18. J. Tobin, 1958. "Liquidity Preference as Behavior Towards Risk," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 25(2), pages 65-86.
    19. David Ardia & Jeremy Kolly & Denis‐Alexandre Trottier, 2017. "The impact of parameter and model uncertainty on market risk predictions from GARCH‐type models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 808-823, November.
    20. Ma, Jason Z. & Deng, Xiang & Ho, Kung-Cheng & Tsai, Sang-Bing, 2018. "Regime-switching determinants of emerging markets sovereign credit risk swaps spread," Economics Discussion Papers 2018-52, Kiel Institute for the World Economy (IfW Kiel).
    21. Marie Briere & Alexandre Burgues & Ombretta Signori, 2008. "Volatility Exposure for Strategic Asset Allocation," Working Papers CEB 08-034.RS, ULB -- Universite Libre de Bruxelles.
    22. Robert Elliott & Tak Kuen Siu & Leunglung Chan, 2007. "Pricing Volatility Swaps Under Heston's Stochastic Volatility Model with Regime Switching," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(1), pages 41-62.
    23. Markus Haas, 2004. "Mixed Normal Conditional Heteroskedasticity," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 211-250.
    24. Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Time-varying mixture GARCH models and asymmetric volatility," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 602-623.
    25. Falcone, Pasquale Marcello & De Rosa, Salvatore Paolo, 2020. "Use of fuzzy cognitive maps to develop policy strategies for the optimization of municipal waste management: A case study of the land of fires (Italy)," Land Use Policy, Elsevier, vol. 96(C).
    26. Chittineni, Jyothi, 2017. "Regime switching behavior of Indian VIX and its time dependent correlation with select developed economies," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 13(5), December.
    27. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    28. Cai, Jun, 1994. "A Markov Model of Switching-Regime ARCH," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 309-316, July.
    29. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    30. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    31. Harold Glenn A. Valera & Jim Lee, 2016. "Do rice prices follow a random walk? Evidence from Markov switching unit root tests for Asian markets," Agricultural Economics, International Association of Agricultural Economists, vol. 47(6), pages 683-695, November.
    32. Ardia, David & Hoogerheide, Lennart F., 2014. "GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts," Economics Letters, Elsevier, vol. 123(2), pages 187-190.
    33. Brooks, Chris & Persand, Gita, 2001. "The trading profitability of forecasts of the gilt-equity yield ratio," International Journal of Forecasting, Elsevier, vol. 17(1), pages 11-29.
    34. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    35. Gurdip Bakshi & Nikunj Kapadia, 2003. "Delta-Hedged Gains and the Negative Market Volatility Risk Premium," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 527-566.
    36. Dueker, Michael J, 1997. "Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 26-34, January.
    37. Robert C. Merton, 2005. "Theory of rational option pricing," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 8, pages 229-288, World Scientific Publishing Co. Pte. Ltd..
    38. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    39. Song, Wonho & Ryu, Doojin & Webb, Robert I., 2016. "Overseas market shocks and VKOSPI dynamics: A Markov-switching approach," Finance Research Letters, Elsevier, vol. 16(C), pages 275-282.
    40. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    41. Grunbichler, Andreas & Longstaff, Francis A., 1996. "Valuing futures and options on volatility," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 985-1001, July.
    42. N. Baba & Y. Sakurai, 2011. "Predicting regime switches in the VIX index with macroeconomic variables," Applied Economics Letters, Taylor & Francis Journals, vol. 18(15), pages 1415-1419.
    43. Johannes Hauptmann & Anja Hoppenkamps & Aleksey Min & Franz Ramsauer & Rudi Zagst, 2014. "Forecasting market turbulence using regime-switching models," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 28(2), pages 139-164, May.
    44. Ye, Wuyi & Zhu, Yangguang & Wu, Yuehua & Miao, Baiqi, 2016. "Markov regime-switching quantile regression models and financial contagion detection," Insurance: Mathematics and Economics, Elsevier, vol. 67(C), pages 21-26.
    45. Andrew Papanicolaou & Ronnie Sircar, 2014. "A regime-switching Heston model for VIX and S&P 500 implied volatilities," Quantitative Finance, Taylor & Francis Journals, vol. 14(10), pages 1811-1827, October.
    46. repec:dau:papers:123456789/7739 is not listed on IDEAS
    47. Imlak Shaikh, 2019. "On the Relationship between Economic Policy Uncertainty and the Implied Volatility Index," Sustainability, MDPI, vol. 11(6), pages 1-11, March.
    48. Alexander, Carol & Korovilas, Dimitris & Kapraun, Julia, 2016. "Diversification with volatility products," Journal of International Money and Finance, Elsevier, vol. 65(C), pages 213-235.
    49. Jung, Young Cheol, 2016. "A portfolio insurance strategy for volatility index (VIX) futures," The Quarterly Review of Economics and Finance, Elsevier, vol. 60(C), pages 189-200.
    50. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    51. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2019. "A Test of Using Markov-Switching GARCH Models in Oil and Natural Gas Trading," Energies, MDPI, vol. 13(1), pages 1-24, December.
    52. Jason Z. Ma & Xiang Deng & Kung-Cheng Ho & Sang-Bing Tsai, 2018. "Regime-Switching Determinants for Spreads of Emerging Markets Sovereign Credit Default Swaps," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
    53. Donald Aingworth & Sanjiv Das & Rajeev Motwani, 2006. "A simple approach for pricing equity options with Markov switching state variables," Quantitative Finance, Taylor & Francis Journals, vol. 6(2), pages 95-105.
    54. Reinhold Hafner & Martin Wallmeier, 2007. "Volatility as an Asset Class: European Evidence," The European Journal of Finance, Taylor & Francis Journals, vol. 13(7), pages 621-644.
    55. Mehmet Balcilar & Riza Demirer & Rangan Gupta, 2017. "Do Sustainable Stocks Offer Diversification Benefits for Conventional Portfolios? An Empirical Analysis of Risk Spillovers and Dynamic Correlations," Sustainability, MDPI, vol. 9(10), pages 1-18, October.
    56. Jyothi Chittineni,, 2017. "Regime switching behavior of Indian VIX and its time dependent correlation with select developed economies," Business and Economic Horizons (BEH), Prague Development Center, vol. 13(5), pages 666-675, December.
    57. Harry Markowitz, 1956. "The optimization of a quadratic function subject to linear constraints," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 111-133, March.
    58. Alizadeh, Amir H. & Nomikos, Nikos K. & Pouliasis, Panos K., 2008. "A Markov regime switching approach for hedging energy commodities," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1970-1983, September.
    59. Paul A. Samuelson, 1973. "Proof That Properly Discounted Present Values of Assets Vibrate Randomly," Bell Journal of Economics, The RAND Corporation, vol. 4(2), pages 369-374, Autumn.
    60. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    61. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    62. Alexander Zeitlberger & Alexander Brauneis, 2016. "Modeling carbon spot and futures price returns with GARCH and Markov switching GARCH models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 149-176, March.
    63. Longstaff, Francis A & Schwartz, Eduardo S, 1992. "Interest Rate Volatility and the Term Structure: A Two-Factor General Equilibrium Model," Journal of Finance, American Finance Association, vol. 47(4), pages 1259-1282, September.
    64. Black, Fischer, 1972. "Capital Market Equilibrium with Restricted Borrowing," The Journal of Business, University of Chicago Press, vol. 45(3), pages 444-455, July.
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