Does increased hedging lead to decreased price efficiency? The case of VIX ETPs and VIX futures

Date01 August 2019
Published date01 August 2019
DOI: 10.1111/fire.12195
Does increased hedging lead to decreased price
efficiency? The case of VIX ETPs and VIX futures
Adrian Fernandez-Perez1Bart Frijns1AlirezaTourani-Rad1
Robert I. Webb2
1Department of Finance, Auckland University of
Technology,Auckland, New Zealand
2McIntire School of Commerce, Universityof
Virginia, Charlottesville, Virginia
BartFrijns, Department of Finance, Auckland
Universityof Technology,Private Bag 92006,
Auckland1142, New Zealand.
We examine the impact of the introduction of VIX exchange-traded
products (ETPs) on the information content and pricing efficiency of
VIX futures. We document that trades in VIX futures have become
less informative and that pricing errors exhibit more persistence
after the introduction of VIX ETPs. In addition, we observe that the
price process of the VIX futures has become noisier over time. These
findings suggest that the introduction of the VIX ETPs had a promi-
nent effect on the properties and dynamics of the VIX futures.
market microstructure, price pressure, VIX ETPs, VIX futures
C22, G13
Exchange-traded products (ETPs) havebecome increasingly popular among retail investors. Issuers of ETPs often use
futures contracts to manage their risk exposure as demand for their ETPs changes. Alexander and Korovilas (2012)
and Asensio (2013) document that excessive liquidity demand from VIX ETPs due to their large-scale hedging activi-
ties could affect VIX futures prices.1This paper examines whether the introduction of ETPs on the VIX changed the
intraday price dynamicsof VIX futures due to hedging pressure by VIX ETPs issuers.
Although VIX futures were introduced by the Chicago Board Options Exchange(CBOE) on March 26, 2004, trading
volume was rather low until the introduction of VIX options on February 24, 2006. However,what really led to the
popularity and a major uptake in VIX futures trading was the introduction of several VIX ETPs. These ETPs, which
track an index based on VIX futures, made the tradingof volatility widely accessible to retail investors. The first ETPs
were the VXX and the VXZ (introduced by Barclays Bank PLCon January 29, 2009), which track the Standard & Poor's
1Białkowski, Dang, and Wei (2016) find the fund flows into different VIX ETP groups have significant impacts on daily changes in the VIX. Bollen, O'Neill,
and Whaley(2017) document that VXX (the most important direct VIX ETP) leads the short-term VIX futures price index in price discovery, and likewise VIX
futures leads VIX index, or as theycall it the “tail is wagging the dog.” Bessembinder, Carrion, Tuttle, and Venkataraman (2016) document a similar effect of
howthe demand in the USO (the ETF on crude oil) has an impact on crude oil futures. Henderson, Pearson, and Wang (2015) find that investor flows in and out
ofcommodity-linked notes (CLNs) are passed to and withdrawn from the futures markets via issuers’ trades to hedge their CLN liabilities.
Financial Review.2019;54:477–500. c
2019 The Eastern Finance Association 477
(S&P) 500 VIX short- and medium-term futures indexes,respectively. As these ETPs track a VIX futures index, the ETP
provider needs to hedgeits positions bytrading in the VIX futures. Increased demand for ETPs by retail investors led to
such a large increase in the tradingvolume of VIX futures that the demand for VIX futures from ETPs at times exceeded
the open interest in VIX futures (Bollen et al., 2017).2
In this paper, we are interested in investigating the (marketmicrostructure) properties of the VIX futures, focus-
ing on the first- and second-nearby futures contracts. These contracts are by far the most heavilytraded and are also
the most demanded by VIX ETPs, as they are the constituents of the S&P 500 VIX short-term index. Webuild a state-
space model for intraday price dynamics based on Brogaard, Henderschott, and Riordan (2014) and Hendershott and
Menkveld(2014), which we model in transaction time. This model allows us to assess the intraday price dynamics of the
VIX futures and study the informativeness of trades. More importantly, this model allows us to decompose the price
process of the VIX futures into a permanent part (representing the efficient price process) and a transitory part (rep-
resenting temporary deviations from the efficient price or pricing error), assessing the properties of both processes.
Empirically, we estimate our model daily using the Kalman Filter overthe period February 24, 2006 to September 2,
Our results show that both the price impact (orinformativeness) of order flow for the evolution of the efficient price
and the contribution of order flow to the variance of the efficient price process decrease after the introduction of VIX
ETPs. For the pricing error,we find that order flow, in general, is in the opposite direction of the error (a finding that
is in line with Brogaard et al., 2014). However,this correction of the pricing error has declined, suggesting that there
is less correction occurring in the period after the introduction of the VIX ETPs. In addition, we observe that there is
persistence in the pricing error. This persistence increases overtime, again suggesting that, after the introduction of
the VIX ETPs, pricing errors persist longer. Finally,the efficiency of the VIX futures prices, measured by the ratio of
the variance of the efficient price to the variance of the observed price (efficient price plus transitorycomponent) has
declined, indicating that VIX futures price movementsare less driven by movements in the efficient price and are more
driven by noise. To providefurther evidence of the impact of the introduction of VIX ETPs on the dynamics of VIX
futures, we assess the properties of the VIX futures intraday and find that the persistence in the pricing error declines
toward the end of the trading day in the period before the introduction of the VIX ETPs. However, this persistence
increases toward the end of the trading day after the introduction of the VIX ETPs. This intraday variation may be a
consequence of VIX ETP traders, who rebalance their positions mostly toward the end of the trading day (Alexander
& Korovilas, 2012).
Since the analysis over different subsamples provides only anecdotal evidence of the impact of VIX ETPs on VIX
futures, we conduct an instrumental variables-generalized method of moments (IV-GMM) regression approach to
establish whether it is indeed VIX ETP hedging demand that has caused the reduction in the informativeness of the
VIX futures. The IV-GMM regression indeed supports the idea that the hedging demand of the VIX ETPs adds noise to
the price process of VIX futures, especially toward the end of the trading day.These results hold after controlling for
changes in the underlying, the effect of the algorithmic tradingactivity and a dummy that controls for the technological
changes in futures trading.Therefore, our results suggest that the increase in the noise component of the price process
of VIX futures after the introduction of the VIX ETPs is caused by the impact of their hedging demands.
A related study to ours is that of Bollen et al. (2017) who document that prices of VIX ETPs (VXX in partic-
ular) lead prices of its benchmark, the VIX short-term futures index (SPVXSTR). This price leadership could be
attributed to the relative informativeness/efficiency or market structure of one market over another. In our paper,
we do not consider relative informativeness/efficiency but focus on the VIX futures themselves. We indeed docu-
ment that informativeness of VIX futures has decreased over time, and we attribute this decline to the increase in
hedging demand from the VIX ETPs. We therefore contribute to the literature as these results could not be inferred
from Bollen et al. (2017) as changes in relative informativeness could be due to changes in the numerator or the
2The VIX ETP market is large, reaching approximately US$4 billion investedin these ETPs. The market for VIX futures is large as well with over 200,000
contractstraded per month. In fact, VIX derivatives are a major contributor to the profits of the CBOE after options on the S&P 500 index.

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