Informed options trading on the implied volatility surface: A cross‐sectional approach

Abstract

This study investigates the cross‐sectional implication of informed options trading across different strikes and maturities. We explore the term structure perspective of the one‐way information transmission from options markets to stock markets by adopting well‐known option‐implied volatility measures to examine stock return predictability. Using equity options data for U.S. listed stocks spanning 2000–2013, we find that the shape of the long‐term implied volatility curve exhibits extra predictive power for stock returns of subsequent months even after orthogonalizing the short‐term components. Our findings indicate that the inter‐market information asymmetry rapidly disappears before the expiration of long‐term option contracts.

Harvesting the volatility smile in a large emerging market: A Dynamic Nelson–Siegel approach

“…For markets with liquid long‐maturity options, researchers have also looked at both the pure term structure of volatility (the time dimension) as well as the volatility surface—the mapping of IV with respect to both strike and time to maturity. Some examples of such studies include Chalamandaris and Tsekrekos (2011), Guo et al (2014), Chalamandaris and Tsekrekos (2014), Guo et al (2018), Kearney et al (2019, and references therein), and Kim et al (2020). Since liquidity in stock options in India is restricted to those with short maturity, exploring the time dimension or the volatility surface is outside the scope of our study.…”

“…Alexander (2001) showed that similar to the term structure, the three principal components of volatility can also be understood in terms of the level, the slope, and the curvature of the volatility smile. In the literature on modeling volatility smile; however, the DNS model has only been predominantly used to model the volatility term structure, with examples including Chalamandaris and Tsekrekos (2011), Guo et al (2014), Chalamandaris and Tsekrekos (2014), Guo et al (2018), Kearney et al (2019, and references therein), and Kim et al (2020).…”

“…There is a growing literature on understanding the behavior of volatility smile in the options markets, the name given to the commonly observed empirical relationship between implied volatility (IV) and option strike. In the last decade, using data from economies with liquid option markets, there have been many articles published on the modeling of volatility smile, as well as on its applications in the larger literature on option pricing, financial engineering, and risk management (Carr & Wu, 2003; Christoffersen et al, 2009; Cont & Fonseca, 2002; François & Stentoft, 2021a; García‐Machado & Rybczyński, 2017; GrØborg & Lunde, 2016; Hagan et al, 2002; Jain et al, 2019; Kim et al, 2020; Kim, 2021; Taylor et al, 2010; Wong & Heaney, 2017).…”

“…Given the empirically established nature of volatility smile across markets, asset classes, and geographies (for a survey, see Derman & Miller, 2016; Kearney et al, 2019) a working model for IV becomes important for a variety of reasons. First, and possibly most importantly, it allows option traders to implement trading strategies, given their view on the evolution of the volatility smile (Kim et al, 2020). Second, a model for the volatility smile allows for extracting the market‐implied risk‐neutral probability distribution of future price movements (Hayashi, 2020; Jackwerth, 2004; Malz, 1997).…”