This study examines the information content of stock option-implied volatility. We measure the arrival intensities and magnitudes of scheduled and unscheduled news as well as fundamental and non-fundamental news. Most of these news measures exhibit strong and positive associations with contemporaneous stock return volatility, and many of them can be predicted by implied volatility. Approximately one third of the predictive power of implied volatility on future realized volatility can be attributed to its ability to predict these news measures, with the majority of the predictive power arising from its capacity to predict the arrival intensities of both scheduled and unscheduled news. The predictive power is higher for fundamental news than for non-fundamental news.

We derive a model with qualitative implications for options pricing under counterparty credit risk and provide empirical evidence using the data from the Hong Kong derivatives market during 2005–2014. We find that the log-price difference between a derivative warrant with counterparty credit risk and an otherwise identical option without counterparty credit risk is significantly and negatively associated with the credit default swap spread on the warrant issuer. We also find that the prices of out-of-the-money put warrants are more sensitive to credit risk than those of other warrants. Our results show counterparty credit risk matters for derivative pricing.

Affine jump-diffusion models have been the mainstream in options pricing because of their analytical tractability. Popular affine jump-diffusion models, however, are still unsatisfactory in describing the options data and the problem is often attributed to the diffusion term of the unobserved state variables. Using prices of variance-swaps (i.e., squared VIX) implied from options prices, we provide fresh evidence regarding the misspecification of affine jump-diffusion models, as variance-swap prices are affine functions of the state variables in a broader class of models that do not restrict the diffusion term of the state variables. We apply the nonparametric methodology used by Aït-Sahalia (1996b), supplemented with bootstrap tests and other parametric tests, to the S&P 500 index options data from January 1996 to September 2008. We find that, while the affine diffusion term of the state variables may contribute to the misspecification as the literature has suggested, the affine drift of the state variables, jump intensities, and risk premiums are also sources of misspecification.

We show theoretically and empirically that the cross-section of stock return idiosyncratic volatilities contains useful information about the ICAPM. We construct a proxy cross-sectional bivariate idiosyncratic volatility (CBIV) for the covariance risk between the market and the unobserved hedge portfolio under the ICAPM. Consistent with the ICAPM pricing relation, CBIV is a robust and significant predictor of the equity risk premium. We further show that the return predictability of the tail index in Kelly and Jiang (2014) can be explained by the ICAPM covariance risk.

Derivative warrants typically have higher prices than do otherwise identical options. Using data from the Hong Kong market during 2002–2007, we show that the price difference reflects the liquidity premium of derivative warrants over options. Newly issued derivative warrants are much more liquid than options with similar terms. As a result, long-term derivative warrants are preferred by traders who trade frequently. In spite of their higher prices, short-term returns on long-term derivative warrants are, in fact, higher than the hypothetical short-term returns on options. The differences in price and liquidity measures decline as the contracts get closer to maturity.

We study how equity option trading affects the market risk premium. We find that a measure of aggregate call order imbalance (ACIB), defined as the cross-sectional average of the difference between open-buy and open-sell volume, negatively forecasts future stock market returns significantly from days to months. Moreover, ACIB represents an option-based investor sentiment measure that accounts for excess option buying or selling, and is highly correlated with the stock investor sentiment. Our findings shed new insights on the distinctions for call and put option trading, index and equity option trading, and cross-sectional and time-series predictions.