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.

ABSTRACT This paper examines the illiquidity of corporate bonds and its asset‐pricing implications. Using transactions data from 2003 to 2009, we show that the illiquidity in corporate bonds is substantial, significantly greater than what can be explained by bid–ask spreads. We establish a strong link between bond illiquidity and bond prices. In aggregate, changes in market‐level illiquidity explain a substantial part of the time variation in yield spreads of high‐rated (AAA through A) bonds, overshadowing the credit risk component. In the cross‐section, the bond‐level illiquidity measure explains individual bond yield spreads with large economic significance.

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

Abstract We document the central role of collateral in the pricing of tri-party repos. Markets are competitive for repos with safe collateral but are severely segmented for repos with risky collateral, such as equities and low-grade corporate bonds. Fund families are the sole contributors to the segmentation, and collateral concentration is the main determinant in the substantial variation in repo pricing, both across and within segments. The segmented structure points to Fidelity as a systemically important player and the markets potential fragility. Facing market segmentation, dealers optimize financing costs by allocating their collateral across fund families.

Major events often trigger abrupt changes in stock prices and volatility. We study the implications of jumps in prices and volatility on investment strategies. Using the event‐risk framework of Duffie, Pan, and Singleton (2000) , we provide analytical solutions to the optimal portfolio problem. Event risk dramatically affects the optimal strategy. An investor facing event risk is less willing to take leveraged or short positions. The investor acts as if some portion of his wealth may become illiquid and the optimal strategy blends both dynamic and buy‐and‐hold strategies. Jumps in prices and volatility both have important effects.

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.

ABSTRACT This paper investigates informed trading on stock volatility in the option market. We construct non‐market maker net demand for volatility from the trading volume of individual equity options and find that this demand is informative about the future realized volatility of underlying stocks. We also find that the impact of volatility demand on option prices is positive. More importantly, the price impact increases by 40% as informational asymmetry about stock volatility intensifies in the days leading up to earnings announcements and diminishes to its normal level soon after the volatility uncertainty is resolved.

We find large overnight returns with no abnormal variance before nonfarm payrolls, ISM, and GDP announcements, similar to the pre-FOMC returns. To explain this common pattern, we propose a two-risk model with the uncertainty about the magnitude of the impending news’ market impact as an additional risk, and link the pre-announcement return directly to the accumulation of heightened uncertainty and its later resolution prior to the announcement. We empirically test and verify the model’s distinct predictions on the joint intertemporal behavior of return, variance, and particularly VIX – a gauge of impact uncertainty by our model, surrounding macroeconomic announcements.

ABSTRACT We propose a market‐wide liquidity measure by exploiting the connection between the amount of arbitrage capital in the market and observed “noise” in U.S. Treasury bonds—the shortage of arbitrage capital allows yields to deviate more freely from the curve, resulting in more noise in prices. Our noise measure captures episodes of liquidity crises of different origins across the financial market, providing information beyond existing liquidity proxies. Moreover, as a priced risk factor, it helps to explain cross‐sectional returns on hedge funds and currency carry trades, both known to be sensitive to the general liquidity conditions of the market.