We propose a market-wide liquidity measure by exploiting the connection between the amount of arbitrage capital in the market and observed price deviations in U.S. Treasury bonds. During normal times, abundant arbitrage capital smoothes out the Treasury yield curve and keeps the deviations small. During market crises, however, the shortage of arbitrage capital leaves the yields to move more freely relative to the curve, resulting in more "noise" in prices. As such, "noise" in Treasury prices can be informative about the broad market liquidity conditions. Indeed, we find that our "noise" measure captures episodes of liquidity crises of different origins and magnitudes across the financial market, providing information above and beyond existing liquidity proxies. Moreover, using it as a priced risk factor, we show that it helps explain cross-sectional returns on hedge funds and currency carry trades, both known to be sensitive to the general liquidity conditions of the market. * Hu (gracexhu@hku.hk) is from University of Hong Kong, Pan (junpan@mit.edu) and Wang (wangj@mit.edu) are from MIT Sloan School of Management, CAFR, and NBER. We are grateful to Cam Harvey (the editor), the associate editor, two anonymous reviewers, Darrell Duffie, Mark Kritzman, Krishna Ramaswamy, Dimitri Vayanos, Adrien Verdelhan, and Haoxiang Zhu for valuable discussions. We also thank comments from seminar participants at

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. * Hu is from Faculty of Business and Economics, University of Hong Kong, and Pan (corresponding author) and Wang are from MIT Sloan School of Management, CAFR, and NBER. We are grateful to Cam Harvey (the Editor), the associate editor, two anonymous reviewers, Darrell Duffie, Mark Kritzman, Krishna Ramaswamy, Dimitri Vayanos, Adrien Verdelhan, and Haoxiang Zhu for valuable discussions. We also thank comments from seminar participants at Boston University, Shanghai University of The level of liquidity in the aggregate financial market is closely connected to the amount of arbitrage capital available. During normal times, institutional investors such as investment banks and hedge funds have abundant capital, which they can deploy to supply liquidity.Consequently, big price deviations from fundamental values are largely eliminated by arbitrage forces, and assets are traded at prices closer to their fundamental values. During market crises, however, capital becomes scarce and/or willingness to deploy it diminishes, and liquidity in the overall market dries up. The lack of sufficient arbitrage capital limits arbitrage forces and assets can be traded at prices significantly away from their fundamental values.1 Thus, temporary price deviations, or noise in prices, being a key symptom of shortage in arbitrage capital, contains important information about the amount of liquidity in the aggregate market.In this paper, we analyze the noise in the price of U.S. Treasuries and examine its informativeness as a measure of overall market illiquidity.Our basic premise is that the abundance of arbitrage capital during normal times helps smooth out the Treasury yield curve and keep the average dispersion low. This is particularly true given the presence of many proprietary trading desks at investment banks and fixedincome hedge funds that are dedicated to relative value trading with the intention to arbitrage across various habitats on the yield curve.2 During liquidity crises, however, the lack of arbitrage capital forces proprietary trading desks and hedge funds to limit or even abandon their relative value trades, leaving the yields to move more freely in their own habitats and resulting in more noise in the yield curve. We argue that abnormal noise in Treasury prices is a symptom of a market in severe shortage of arbitrage capital. More importantly, to the extent that capital is...

We investigate the size and value factors in the cross-section of returns for the Chinese stock market. We find a significant size effect but no robust value effect. A zero-cost small-minus-big (SMB) portfolio earns an average premium of 0.61% per month, which is statistically significant with a t-value of 2.89 and economically important. In contrast, neither the market portfolio nor the zero-cost high-minus-low (HML) portfolio has average premiums that are statistically different from zero. In both time-series regressions and Fama-MacBeth cross-sectional tests, SMB represents the strongest factor in explaining the cross-section of Chinese stock returns. Our results contradict several existing studies which document a value effect. We show that this difference comes from the extreme values in a few months in the early years of the market with a small number of stocks and high volatility. Their impact becomes insignificant with a longer sample and proper volatility adjustment.

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We propose a general partially-observed framework of Markov processes with marked point process observations for ultra-high frequency (UHF) data. The model well fits the stylized facts of UHF data in both macro-and micro-movements, subsumes important existing models, and incorporates the influence of other observable economic or market factors. We develop the corresponding Bayes estimation via filtering equation to quantify parameter uncertainty. Namely, we derive the normalized filtering equation to characterize the evolution of the posterior distribution, present a weak convergence theorem, and construct consistent, easily-parallelizable, recursive algorithms to calculate the joint posteriors and the Bayes estimates for streaming UHF data. Moreover, an easy-to-check sufficient condition for the consistency of the Bayes estimators is provided. The general estimation theory is illustrated by four specific models built for U.S. Treasury Notes transactions data from GovPX. We show that in this market, both informationbased and inventory management-based motives are significant factors in the trade-to-trade price volatility.

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for comments. We thank Meiling Chen and Zhe Geng for research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.