Volatility as an Alternative Asset Class: Does It Improve Portfolio Performance?

Elvira Caloiero; Massimo Guidolin; Elvira Caloiero; Massimo Guidolin

doi:10.3934/QFE.2017.4.334

Quantitative Finance and Economics

2017, Volume 1, Issue 4: 334-362. doi: 10.3934/QFE.2017.4.334

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Volatility as an Alternative Asset Class: Does It Improve Portfolio Performance?

Elvira Caloiero ,
Massimo Guidolin ^,

Bocconi University Finance Dept., and BAFFI-CAREFIN, via Roentgen 1, 20136 Milan, Italy

Received: 29 July 2017 Accepted: 20 November 2017 Published: 13 December 2017

We investigate the potential role of Exchange Traded Products (Notes) as vehicles to trade volatility (here proxied by the VIX index) as an asset class in a fully optimizing asset allocation framework, subject to long-only constraints. In back-testing, recursive exercises based on an expanding window of data from February 2010 to February 2016, we find evidence that VIX should enter with non-negligible weight most portfolio strategies and that under many circumstances, long VIX positions may generate positive risk-adjusted performance benefits. However, the volatility positions that can be managed and traded through (one of) the most popular US exchange-traded notes (VXX) fails to deliver such realized, out-of-sample benefits under all utility functions and for a range of assumptions on investors' risk aversion. Even though the turnover implied by VXX does not appear excessive, taking into account transaction costs worsens considerably its performance and even casts doubts as to whether volatility ought to be considered as an alternative asset class altogether. Direct strategies that trade appropriate futures on the VIX improve somewhat realized performance, but not enough to tilt over the balance of our conclusions.
- volatility,
- VIX,
- Exchange-Traded Products,
- Exchange-Traded Notes,
- optimal asset allocation
Citation: Elvira Caloiero, Massimo Guidolin. Volatility as an Alternative Asset Class: Does It Improve Portfolio Performance?[J]. Quantitative Finance and Economics, 2017, 1(4): 334-362. doi: 10.3934/QFE.2017.4.334

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Abstract

We investigate the potential role of Exchange Traded Products (Notes) as vehicles to trade volatility (here proxied by the VIX index) as an asset class in a fully optimizing asset allocation framework, subject to long-only constraints. In back-testing, recursive exercises based on an expanding window of data from February 2010 to February 2016, we find evidence that VIX should enter with non-negligible weight most portfolio strategies and that under many circumstances, long VIX positions may generate positive risk-adjusted performance benefits. However, the volatility positions that can be managed and traded through (one of) the most popular US exchange-traded notes (VXX) fails to deliver such realized, out-of-sample benefits under all utility functions and for a range of assumptions on investors' risk aversion. Even though the turnover implied by VXX does not appear excessive, taking into account transaction costs worsens considerably its performance and even casts doubts as to whether volatility ought to be considered as an alternative asset class altogether. Direct strategies that trade appropriate futures on the VIX improve somewhat realized performance, but not enough to tilt over the balance of our conclusions.

References

[1]	Adams Z, Füss R, Glück T (2017) Are correlations constant? Empirical and theoretical results on popular correlation models in finance. J Bank Financ 84: 9–24.
[2]	Alexander C, Kapraun J, Korovilas D (2015) Trading and investing in volatility products. Financ Mark, Inst Instrum 24: 313–347. doi: 10.1111/fmii.12032
[3]	Alexander C, Korovilas D (2013) Volatility exchange-traded notes: curse or cure? J Altern Invest 12: 52–70.
[4]	Amenc N, Glotz F, Grigoriu A (2010) Risk Control through Dynamic Core-Satellite Portfolios of ETFs: Applications to Absolute Return Funds and Tactical Asset Allocation. EDHEC-Risk Institute Publication.
[5]	Bhansali V (2008) Tail risk management. J Portf Manage 34: 68–75. doi: 10.3905/jpm.2008.709982
[6]	Bekaert G, Wu G (2000) Asymmetric Volatility and Risk in Equity Markets. Rev Financ Stud 13: 1–42. doi: 10.1093/rfs/13.1.1
[7]	Bollen N, O'Neill MJ, Whaley R (2017) Tail Wags Dog: Intraday Price Discovery in VIX Markets. J Futures Mark 37: 431–451. doi: 10.1002/fut.21805
[8]	Black K (2006) Improving Hedge Fund Risk Exposures by Hedging Equity Market Volatility, or How the VIX Ate My Kurtosis. J Trading 1: 6–15.
[9]	Brenner M, Ou E, Zhang J (2006) Hedging Volatility Risk. J Bank Financ 30: 811–821. doi: 10.1016/j.jbankfin.2005.07.015
[10]	Brière M, Burgues A, Signori O (2009) Volatility Exposure for Strategic Asset Allocation. J Portf Manage 36: 105–116.
[11]	Carroll R, Conlon T, Cotter J, et al. (2017) Asset allocation with correlation: A composite trade-off. European J Oper Res 262: 1164–1180. doi: 10.1016/j.ejor.2017.04.015
[12]	Chicago Board Options Exchange (2003) VIX: CBOE Volatility Index. Working Paper.
[13]	Dash S, Liu B (2012) Volatility ETFs and ETNs. J Trading 7: 43–48.
[14]	Dash S, Moran MT (2005) VIX as a Companion for Hedge Fund Portfolios. J Altern Invest 8: 75–80. doi: 10.3905/jai.2005.608034
[15]	DeLisle J, Doran JS, Krieger K (2010) Volatility as an Asset Class: Holding VIX in a Portfolio. Working Paper.
[16]	DeMiguel V, Garlappi L, Uppal R (2007) Optimal Versus Naive Diversification: How Inefficient is the 1/N Portfolio Strategy? Rev Financ Stud 22: 1915–1953.
[17]	Doran J, Krieger K (2010) Implications for Asset Returns in the Implied Volatility Skew. Financ Anal J 66: 65–76. doi: 10.2469/faj.v66.n1.9
[18]	Fallon W, Park J, Yun D (2015) Asset Allocation Implications of the Global Volatility Premium. Financ Anal J 71: 38–56. doi: 10.2469/faj.v71.n5.4
[19]	Füss R, Grabellus M, Mager F, et al. (2014) How risk-return efficient are target risk strategies? J Index Invest 4: 33–42. doi: 10.3905/jii.2014.4.4.033
[20]	Grant M, Gregory K, Lui J (2007) Volatility as an Asset. Goldman Sachs Equity Research.
[21]	Guidolin M (2013) Preference Models in Portfolio Construction and Evaluation, in K., Baker and G., Filbeck (eds.), Portf Theory Manage, chapter 11, Oxford University Press.
[22]	Guidolin M, Timmermann A (2005) Optimal Portfolio Choice under Regime Switching, Skew and Kurtosis Preferences. Federal Reserve Bank of St. Louis W.P. No. 2005-006A.
[23]	Guidolin M, Timmermann A (2008) International Asset Allocation under Regime Switching, Skew and Kurtosis Preferences. Rev Financ Stud 21: 889–935. doi: 10.1093/rfs/hhn006
[24]	Hancock G (2013) VIX futures ETNs: three dimensional losers. Account Financ Res 2: 53–64.
[25]	Jondeau E, Rockinger M (2006) Optimal Portfolio Allocation under Higher Moments. European Financ Manage 12: 29–55.
[26]	Hafner R, Wallmeier M (2008) Optimal Investments in Volatility. Financ Mark Portf Manage 22: 147–167.
[27]	Hafner R, Wallmeier M (2007) Volatility as an Asset Class: European Evidence. European J Financ 13: 621–644. doi: 10.1080/13518470701380142
[28]	Jondeau E, Rockinger M (2006) Optimal Portfolio Allocation under Higher Moments. European Financ Manage 12: 29–55. doi: 10.1111/j.1354-7798.2006.00309.x
[29]	Kuenzi D, Xu S (2007) Asset Based Style Analysis for Equity Strategies: The Role of the Volatility Factor. J Altern Invest 10: 10–24.
[30]	Rakowski D, Shirley SE, Stark JR (2017) Tail-risk hedging, dividend chasing, and investment constraints: The use of exchange-traded notes by mutual funds. J Empir Financ 44: 91–107. doi: 10.1016/j.jempfin.2017.08.003
[31]	Scott R, Horvath P (1980) On the Direction of Preference for Moments of Higher Order than the Variance. J Financ 35: 915–919.
[32]	Sharpe W (2006) Expected Utility Asset Allocation. Financ Anal J 63: 12–39.
[33]	Stanton C (2011) Volatility as an Asset Class. J Invest Consult 12: 23–30.
[34]	Szado E (2009) VIX Futures and Options: A Case Study of Portfolio Diversification during the 2008 Financial Crisis. J Altern Invest 12: 68–95. doi: 10.3905/JAI.2009.12.2.068
[35]	Whaley R (2000) The Investor Fear Gauge. J Portf Manage 26: 12–17.
[36]	Whaley R (2009) Understanding the VIX. J Portf Manage 35: 98–105. doi: 10.3905/JPM.2009.35.3.098
[37]	Whaley R (2013) Trading Volatility: At What Cost? J Portf Manage 40: 95–108.

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