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.

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.

In the setting of ‘affine’ jump-diffusion state processes, this paper provides an analytical treatment of a class of transforms, including various Laplace and Fourier transforms as special cases, that allow an analytical treatment of a range of valuation and econometric problems. Example applications include fixed-income pricing models, with a role for intensity-based models of default, as well as a wide range of option-pricing applications. An illustrative example examines the implications of stochastic volatility and jumps for option valuation. This example highlights the impact on option ‘smirks’ of the joint distribution of jumps in volatility and jumps in the underlying asset price, through both jump amplitude as well as jump timing.

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. Sometimes, the strangest things happen and the least expected occurs. In financial markets, the mere possibility of extreme events, no matter how unlikely, could have a profound impact. One such example is the so-called

From 2007 to June 2013, a small group of fee-paying, high-speed traders receive the Michigan Index of Consumer Sentiment two seconds before its broader release. Within this early peek window, we find highly concentrated trading and a fast price discovery of less than 200 milliseconds. Outside this narrow window, general investors trade at fully adjusted prices. We further establish a causal relationship between the early peek mechanism and the fast price discovery by isolating the impact of the early peek arrangement along two dimensions. In cross section, we use other news releases without the early peek (as controls); in time series, we use the sudden suspension of the early peek arrangement in July 2013 (as the treatment). Our difference-in-difference tests directly connect the early peek arrangement to more efficient price discovery — it results in faster price discovery, lower volatility, and faster resolution of uncertainty. These results show that contrary to the common perception, tiered information release may help to reduce, rather than enhance, the informational advantage of faster traders and improve the efficiency of the price discovery process in financial markets.