What Does Implied Volatility Skew Measure?

Mixon, Scott

doi:10.3905/jod.2011.18.4.009

Cited by 25 publications

(7 citation statements)

References 15 publications

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“…Practitioners commonly use the terms "skew" and "implied volatility skew" for the ATM slope of the implied volatility curve for a given expiration date (see, e.g.,[30]). We will use the terms interchangeably 2.…”

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confidence: 99%

“…The ATM skew has received comparatively little attention in the literature, despite the fact that it is actively monitored in practice by traders and analysts (cf. [30]), stemming in part from its rich informational content, and considerable empirical support has in fact been provided for its significance in predicting future equity returns, and as an indicator of the risk of large negative jumps (see, e.g., [40], [41], for individual stock options, and [6], [34], for index options).…”

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confidence: 99%

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Short-term asymptotics for the implied volatility skew under a stochastic volatility model with Lévy jumps

Figueroa-López

Ólafsson

2016

Finance Stoch

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The implied volatility skew has received relatively little attention in the literature on short-term asymptotics for financial models with jumps, despite its importance in model selection and calibration. We rectify this by providing high-order asymptotic expansions for the at-the-money implied volatility skew, under a rich class of stochastic volatility models with independent stable-like jumps of infinite variation. The case of a pure-jump stable-like Lévy model is also considered under the minimal possible conditions for the resulting expansion to be well defined. Unlike recent results for "near-the-money" option prices and implied volatility, the results herein aid in understanding how the implied volatility smile near expiry is affected by important features of the continuous component, such as the leverage and vol-of-vol parameters. As intermediary results we obtain high-order expansions for at-the-money digital call option prices, which furthermore allow us to infer analogous results for the delta of at-the-money options. Simulation results indicate that our asymptotic expansions give good fits for options with maturities up to one month, underpinning their relevance in practical applications, and an analysis of the implied volatility skew in recent S&P500 options data shows it to be consistent with the infinite variation jump component of our models.AMS 2000 subject classifications: 60G51, 60F99, 91G20, 91G60.

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confidence: 99%

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confidence: 99%

Short-term asymptotics for the implied volatility skew under a stochastic volatility model with Lévy jumps

Figueroa-López

Ólafsson

2016

Finance Stoch

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“…Several studies, such as those of Xing et al (2010) and Yan (2011), provide convincing support for a negative relationship between

IVSkew

and future stock returns. Following Mixon (2011), we calculate

IVSkew

as the difference between the fitted implied volatilities of 1‐month‐to‐expiration put and call options with deltas equal to −0.25 and 0.25 divided by the average implied volatility of at‐the‐money (ATM) call and put options with deltas equal to 0.5 and −0.5, respectively. Additionally,

OSVol

is the ratio of the option trading volume to the underlying stock market volume.…”

Section: Empirical Methodologymentioning

confidence: 99%

Investor sentiment, misreaction, and the skewness‐return relationship

Chen

2021

Journal of Futures Markets

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This study examines the effect of investor sentiment on misreaction and explores the time‐series relationship between risk‐neutral skewness (RNS) and subsequent stock market returns contingent on sentiment‐induced overreaction. Using the adjusted put‐call implied volatility spread as a misreaction proxy and Bakshi et al.'s method to measure RNS, we find that pessimism leads to overreaction. This overreaction could strengthen the negative RNS‐return relationship, with higher market returns following lower RNS. Our results are robust even after excluding the sample period of the 2008 financial crisis, profiting from market‐timing strategies based on the levels of RNS and overreaction, and using an alternative RNS measure.

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“…Interest has more recently expanded to other implied moments, such as those of the underlying asset distributions that are constructed from option prices, not only because of their relevance to provide a clearer picture of current market expectations (Vergote and Puigvert, 2012;Vesela and Puigvert, 2014;Sihvonen and Vähämaa, 2014), but also because of their predictive and forward looking power in decision and policy making (Mixon, 2011;DeMiguel et al, 2013;Driessen et al, 2013;Atilgana et al, 2015). The implied volatility (Atilgana et al, 2015), correlation (Skintzi and Apostolos, 2005;Driessen et al, 2009Driessen et al, , 2013, skewness (Mixon, 2011;DeMiguel et al, 2013) and kurtosis (DeMiguel et al, 2013) all help to improve significantly the understanding of expectations, risk management and asset return predictability. For example, when modelling risk scenarios, larger-than-usual implied tails or skewness will have a differential content of information about the market's beliefs beyond the information that is available only in the implied second moment.…”

Section: Introductionmentioning

confidence: 99%