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 that firms collect almost 70% of their cash flows in the second half of the fiscal year, and that firms that collect more cash by year-end earn a 6.8% higher per annum risk premium and save more cash. We rationalize these facts in a quantitative investment-based asset pricing model. Immediate cash payments negatively affect profitability, but reduce equity financing costs by increasing information transparency. Financially constrained firms optimally collect more cash at year-end when firms’ performance attracts more attention and information transparency is more valuable. Such behavior further results in greater exposure to aggregate productivity and financial shocks.

Using a large sample of U.S. firms for the period 1995–2008, we provide strong and robust evidence that corporate tax avoidance is positively associated with firm-specific stock price crash risk. This finding is consistent with the following view: Tax avoidance facilitates managerial rent extraction and bad news hoarding activities for extended periods by providing tools, masks, and justifications for these opportunistic behaviors. The hoarding and accumulation of bad news for extended periods lead to stock price crashes when the accumulated hidden bad news crosses a tipping point, and thus comes out all at once. Moreover, we show that the positive relation between tax avoidance and crash risk is attenuated when firms have strong external monitoring mechanisms such as high institutional ownership, high analyst coverage, and greater takeover threat from corporate control markets.

Using a large sample of U.S. firms for the period 1993–2009, we provide evidence that the sensitivity of a chief financial officer's (CFO) option portfolio value to stock price is significantly and positively related to the firm's future stock price crash risk. In contrast, we find only weak evidence of the positive impact of chief executive officer option sensitivity on crash risk. Finally, we find that the link between CFO option sensitivity and crash risk is more pronounced for firms in non-competitive industries and those with a high level of financial leverage.

Embedding disasters into a general equilibrium model with heterogeneous firms induces strong nonlinearity in the pricing kernel, helping explain the empirical failure of the (consumption) CAPM. Our single-factor model reproduces the failure of the CAPM in explaining the value premium in finite samples without disasters and its relative success in samples with disasters. Due to beta measurement errors, the estimated beta-return relation is flat, consistent with the beta “anomaly,” even though the true beta-return relation is strongly positive. Finally, the consumption CAPM fails in simulations, even though a nonlinear model with the true pricing kernel holds exactly by construction.