[We find that the empirical volatilities of corporate bond and CDS returns are higher than implied by equity return volatilities and the Merton model. This excess volatility may arise because structural models inadequately capture either fundamentals or illiquidity. Our evidence supports the latter explanation. We find little relation between excess volatility and measures of firm fundamentals and the volatility of firm fundamentals but some relation with variables proxying for time-varying illiquidity. Consistent with an illiquidity explanation, firm-level bond portfolio returns, which average out bond-specific effects, significantly decrease excess volatility.]

We present strong evidence that option trading volume contains information about future stock prices. Taking advantage of a unique data set, we construct put-call ratios from option volume initiated by buyers to open new positions. Stocks with low put-call ratios outperform stocks with high put-call ratios by more than 40 basis points on the next day and more than 1% over the next week. Partitioning our option ignals into components that are publicly and nonpublicly observable, we find that the economic source of this predictability is nonpublic information possessed by option traders rather than market inefficiency. We also find greater predictability for stocks with higher concentrations of informed traders and from option contracts with greater leverage.

This paper examines the joint time series of the S&P 500 index and near-the-money short-dated option prices with an arbitrage-free model, capturing both stochastic volatility and jumps. Jump-risk premia uncovered from the joint data respond quickly to market volatility, becoming more prominent during volatile markets. This form of jump-risk premia is important not only in reconciling the dynamics implied by the joint data, but also in explaining the volatility “smirks” of cross-sectional options data.

This article studies the asset pricing implication of imprecise knowledge about rare events. Modeling rare events as jumps in the aggregate endowment, we explicitly solve the equilibrium asset prices in a pure-exchange economy with a representative agent who is averse not only to risk but also to model uncertainty with respect to rare events. The equilibrium equity premium has three components: the diffusive- and jump-risk premiums, both driven by risk aversion; and the "rare-event premium," driven exclusively by uncertainty aversion. To disentangle the rare-event premiums from the standard risk-based premiums, we examine the equilibrium prices of options across moneyness or, equivalently, across varying sensitivities to rare events. We find that uncertainty aversion toward rare events plays an important role in explaining the pricing differentials among options across moneyness, particularly the prevalent "smirk" patterns documented in the index options market.

We find that the empirical volatilities of corporate bond and CDS returns are higher than implied by equity return volatilities and the Merton model. This excess volatility may arise because structural models inadequately capture either fundamentals or illiquidity. Our evidence supports the latter explanation. We find little relation between excess volatility and measures of firm fundamentals and the volatility of firm fundamentals but some relation with variables proxying for time-varying illiquidity. Consistent with an illiquidity explanation, firm-level bond portfolio returns, which average out bond-specific effects, significantly decrease excess volatility.

We present strong evidence that option trading volume contains information about future stock prices. Taking advantage of a unique data set, we construct put-call ratios from option volume initiated by buyers to open new positions. Stocks with low put-call ratios outperform stocks with high put-call ratios by more than 40 basis points on the next day and more than 1% over the next week. Partitioning our option signals into components that are publicly and nonpublicly observable, we find that the economic source of this predictability is nonpublic information possessed by option traders rather than market inefficiency. We also find greater predictability for stocks with higher concentrations of informed traders and from option contracts with greater leverage.

ABSTRACT Studying China's credit market using a structural default model that integrates credit risk, liquidity, and bailout, we document improved price discovery and a deepening divide between state‐owned enterprises (SOEs) and non‐SOEs. Amidst liquidity deterioration, the presence of government bailout helps alleviate the heightened liquidity‐driven default, making SOE bonds more valuable and widening the SOE premium. Meanwhile, the increased importance of government support makes SOEs more sensitive to bailout, while the heightened default risk increases non‐SOEs' sensitivity to credit quality. Examining the real impact, we find severe performance deteriorations of non‐SOEs relative to SOEs, reversing the long‐standing trend of non‐SOEs outperforming SOEs.

ABSTRACT This paper explores the nature of default arrival and recovery implicit in the term structures of sovereign CDS spreads. We argue that term structures of spreads reveal not only the arrival rates of credit events , but also the loss rates given credit events. Applying our framework to Mexico, Turkey, and Korea, we show that a single‐factor model with following a lognormal process captures most of the variation in the term structures of spreads. The risk premiums associated with unpredictable variation in are found to be economically significant and co‐vary importantly with several economic measures of global event risk, financial market volatility, and macroeconomic policy.

We analyze price discovery in the options and CDS markets during the 2008 short-sale ban. Among the banned stocks, those with high open-purchased put–call ratios, low synthetic-to-stock price ratios, or high CDS rates exhibit poor performance in the following days. Additionally, options prices are more efficient for unbanned stocks during the ban period. These findings suggest that informed investors engage in derivative trading during highly distressed market conditions and that derivative prices contain more information about stock prices during the ban.