Risk Premium Effects on Implied Volatility Regressions

Volatility Forecasting and Time‐varying Variance Risk Premiums in Grains Commodity Markets

“…When we use option‐implied skewness as an additional factor in our initial univariate predictive regressions, the adjusted R 2 increases from 28.6% to 41.5% for the case of soybeans . In section we found that the soybeans market has a substantial negative variance risk premium and therefore the inclusion of risk‐neutral skewness corrects for the biases in the predictive regressions following Rompolis and Tzavalis (). For all commodities considered, macroeconomic factors are insignificant and do not improve the forecasting performance for price variance.…”

“…In practice the actual volatility observed over the period of trading the relevant option is not the same as 3 Previous studies in the commodity pricing literature that use Black's implied volatility to forecast future realised volatility are Simon (2002), Giot (2003) and Manfredo and Sanders (2004). 4 For example, Rompolis and Tzavalis (2010) show that option-implied skewness corrects for bias of option-implied volatility to forecast realised volatility. Conrad et al (2013) find that risk-neutral skewness of individual stocks has a strong negative relationship with subsequent returns and Chang et al (2013) find an economically significant risk premium for equity systematic risk-neutral skewness.…”

Exploring the role of the realized return distribution in the formation of the implied volatility smile

“…8 The cross-correlation of the respective risk premia can also be theoretically explained. Rompolis and Tzavalis (2010b) show that under the assumption of a representative investor with a power utility function the nth-order cumulant risk premium depend on all cumulants (physical or risk-neutral) of order higher than n. 9 See Cuthbertson and Nitzsche (2004) for a derivation of this result. this issue by examining the out-of-sample performance of the proposed model as described in the following section.…”

Retrieving risk neutral moments and expected quadratic variation from option prices

“…For instance, they can be used to study the information content of option prices about future stock market volatility or any other higher-order risk neutral moment (Canina and Figlewski 1993;Christensen and Prabhala 1998;Dennis and Mayhew 2002;Jiang and Tian 2005;Bollerslev and Zhou 2006;Blenman and Wang 2012). Secondly, they can be employed to examine the relationship between higher-order risk neutral moments of asset returns and their physical counterparts, and/or to estimate the implied risk aversion coefficient of the stock and option markets participants (Bakshi et al 2003;Bakshi and Madan 2006a, b;Rompolis and Tzavalis 2010;Polkovnichenko and Zhao 2013). Thirdly, they can be applied to estimate the risk neutral density (RND) of the underlying asset return based on an approximation density method (Corrado and Su 1996;Ang et al 2002;Rompolis and Tzavalis 2008;Rompolis 2010;Mozumder et al 2013;Ghysels and Wang 2014).…”