Noise as Information for Illiquidity: Noise as Information for Illiquidity

By Grace Xing Hu, Jun Pan, Jiang Wang. 2013

423 citations recorded by the source corpus.

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 Finance and Economics, University of Maryland, University of Michigan, University of Pennsylvania, University of Western Australia, Capula Investment Management LLC, 2011 NBER Asset Pricing Program Spring Meeting, Moody’s 2011 Credit Risk Conference, Morgan Stanley, and Q Group 2012 Spring Conference. 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. 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. 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 allocated across markets for major marginal players in the market, this symptom applies not only to the Treasury market, but also more broadly to the overall financial market.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/19912e4468b6e8469c8126106c7de852142849a2

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Citations in the corpus

The Risk Premia Embedded in Index Options (2015, background): “The absence of perfect information plus aversion to ambiguity (particularly about extreme negative risks), like in Hansen and Sargent (2008), or lack of confidence in the estimate of the state vector, like in Bansal and Shaliastovich (2010), can make investors appear more risk averse than they…”
Understanding FX Liquidity (2015, background): “Hu, Pan, and Wang (2012) and Deuskar, Gupta, and Subrahmanyam (2011) focus on government bond and OTC markets, respectively. by four times (i.e., from 0.9 to 4.1 bp).”
Convective Risk Flows in Commodity Futures Markets (2015, positive): “In our analysis, we also explore several alternative measures, including the implied volatility of financial sector ETFs, the average CDS spread of primary dealers, and the measure of Treasury market illiquidity developed by Hu, Pan, and Wang (2013).”
Working Paper # 0001 January 5 , 2012 A Survey of Systemic Risk Analytics (2012, neutral): “Hu, Pan, and Wang (2010) extract an indicator of market illiquidity from the noise in Treasury prices.”
Systemic Risk and the Macroeconomy: An Empirical Evaluation (2016, methodology): “Similar to Kelly and Pruitt’s (2012) argument for partial least squares, this has been done in order to try and extract from x only the relevant information f while leaving out the irrelevant g.”
Can Facebook Predict Stock Market Activity (2013, background): “Particularly, Hu et al. (2010) argue that reluctance of arbitrageurs to bet against mispricing is especially severe in crisis periods since arbitrage capital is scarce and associated risks are high, which altogether may end up in ‘more noise’ in asset prices.”
FLOW AND STOCK EFFECTS OF LARGE-SCALE TREASURY PURCHASES: EVIDENCE ON THE IMPORTANCE OF LOCAL SUPPLY (2012, positive): “…any purchases took place—presumably, this mechanism accounted for much of the 25 to 50 basis point drop in Treasury yields on the day the program was announced.16 15 Hu, Pan, and Jiang (2010) use an index of similarly constructed fitting errors to gauge the evolution of Treasurymarket liquidity.”
The Time Variation in Risk Appetite and Uncertainty (2019, background): “The expressions for these variables are derived in Equations (27) – (29).”