The risk premium that never was: A fair value explanation of the volatility spread

Richard J. McGee and Frank McGroarty

European Journal of Operational Research, 2017, vol. 262, issue 1, 370-380

Abstract: We present a new framework to investigate the profitability of trading the volatility spread, the upward bias on implied volatility as an estimator of future realized volatility. The scheme incorporates the first four option-implied moments in a growth-optimal payoff that is statically replicated using a portfolio of options. Removing the upward bias on implied volatility worsens the likelihood score of risk-neutral densities obtained from S&P 500 index options when they are used as forecasts of the underlying index return distribution. It also results in negative expected capital growth when they are used in a volatility arbitrage scheme. Our empirical finding is that the upward bias on implied volatility does not represent a long-term return premium, rather it is required to mitigate the large losses associated with tail events when trading volatility in options markets.

Keywords: Finance; Volatility spread; Variance premium; Tail risk; Growth-optimal portfolios (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221717303016
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:262:y:2017:i:1:p:370-380

DOI: 10.1016/j.ejor.2017.03.070

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().