AQR Insight Award

The AQR Insight Award, sponsored by AQR Capital Management, recognizes important, unpublished papers that provide the most significant, new practical insights for tax-exempt institutional or taxable investor portfolios. Up to three papers share a $100,000 prize.

2014 Award Winners

  1. First Prize


    Abstract

    2014 FIRST PRIZE

    Eric Budish, Ph.D., Peter Cramton, Ph.D., and John J. Shim

    We argue that the continuous limit order book is a flawed market design and propose that financial exchanges instead use frequent batch auctions: uniform-price sealed-bid double auctions conducted at frequent but discrete time intervals, e.g., every 1 second. Our argument has four parts. First, we use millisecond-level direct-feed data from exchanges to show that the continuous limit order book market design does not really “work” in continuous time: market correlations completely break down at high-frequency time horizons. Second, we show that this correlation breakdown creates frequent technical arbitrage opportunities, available to whomever is fastest, which in turn creates an arms race to exploit such opportunities. Third, we develop a simple new theory model motivated by these empirical facts. The model shows that the arms race is not only socially wasteful — a prisoner’s dilemma built directly into the market design — but moreover that its cost is ultimately borne by investors via wider spreads and thinner markets. Last, we show that frequent batch auctions eliminate the arms race, both because they reduce the value of tiny speed advantages and because they transform competition on speed into competition on price. Consequently, frequent batch auctions lead to narrower spreads, deeper markets, and increased social welfare.

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    Presentation
    Authors
    • Eric Budish

      Eric Budish, Ph.D.
      Associate Professor of Economics
      Booth School of Business, University of Chicago

      Eric Budish is Associate Professor of Economics at the University of Chicago, Booth School of Business. He is an applied micro-economist and game theorist who researches market design. His most recent research concerns the design of financial exchanges. Budish shared the inaugural Kauffman/iHEA Award for Health Care Entrepreneurship and Innovation Research for research on how that the patent system inadvertently under-incentivizes long horizon R&D for cancer drugs. Budish received a B.A. in economics and philosophy from Amherst College, an M.Phil. in economics from Oxford (Nuffield College), where he was a Marshall Scholar, and received a Ph.D. in business economics from Harvard University. Prior to graduate school, Budish worked at Goldman Sachs as an analyst in the mergers and acquisitions group.

    • Peter Cramton

      Peter Cramton, Ph.D.
      Professor of Economics
      The University of Maryland, College Park

      Peter Cramton is Professor of Economics at the University of Maryland. He conducts research on auction theory and practice, and publishes in the leading economics journals. He is also Chairman of Market Design Inc., an economics consultancy founded in 1995, focusing on the design of auction and matching markets. Since 1993, he has advised 12 governments and 36 bidders in spectrum auctions, and has played a lead role in the design and implementation of electricity and gas auctions in North America, South America and Europe. He has advised on the design of carbon auctions in Europe, Australia and the United States. He received his B.S. in Engineering from Cornell University and his Ph.D. in Business from Stanford University.

    • John Shim

      John J. Shim
      Ph.D. student
      Booth School of Business, University of Chicago

      John J. Shim is working on a Ph.D. in finance at the University of Chicago Booth School of Business, where he is researching empirical asset pricing, market efficiency, market microstructure and financial market design. He began his career as a trader at Jump Trading and later was a research and teaching assistant at the University of Chicago. Shim earned B.S. in statistics and computer science from the University of Illinois at Urbana Champaign, and an M.B.A. in analytic finance, finance and econometrics, with honors, from the University of Chicago.

  2. Honorable Mention


    Abstract

    2014 HONORABLE MENTION

    Dong Lou, Ph.D., and Christopher Polk, Ph.D.

    We propose a novel measure of arbitrage activity to examine whether arbitrageurs can have a destabilizing effect in the stock market. We apply our insight to stock price momentum, a classic example of the type of unanchored, positive-feedback strategy that theory predicts can be destabilizing. We define our measure, which we dub comomentum, as the high-frequency abnormal return correlation among stocks on which a typical momentum strategy would speculate. We show that during periods of low comomentum, momentum strategies are profitable and stabilizing, reflecting an underreaction phenomenon that arbitrageurs correct. In contrast, during periods of high comomentum, these strategies tend to crash and revert, reflecting prior overreaction resulting from crowded momentum trading pushing prices away from fundamentals. Theory suggests that we should not find destabilizing arbitrage activity in anchored strategies. Indeed, we find that a corresponding measure of arbitrage activity for the value strategy, covalue, positively forecasts future value strategy returns and is positively correlated with the value spread, a natural anchor for the value-minus-growth trade. Similar tests in the currency market as well as further analysis of stock momentum at the firm, fund and international level confirm that our approach to measuring arbitrage activity in the momentum strategy is sensible.

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    Presentation
    Authors
    • Dong Lou

      Dong Lou, Ph.D.
      Assistant Professor of Finance
      London School of Economics

      Dong Lou is an Assistant Professor of Finance at the London School of Economics and Political Science. He is also a research affiliate of the Center for Economic Policy Research. His research interests include empirical asset pricing, behavioral finance and empirical corporate finance. He has published research in The Review of Financial Studies and the Journal of Financial Economics. Lou earned a B.S. in computer science from Columbia University, graduating summa cum laude, and a Ph.D. in finance from Yale University.

    • Christopher Polk

      Christopher Polk, Ph.D.
      Professor of Finance
      London School of Economics

      Christopher Polk is a Professor of Finance at the London School of Economics and Political Science and director of LSE’s Financial Markets Group Research Centre. He is also a research fellow at the Center for Economic Policy Research and an associate editor of The Journal of Finance. Earlier in his career he was an advisor or consultant at the European Securities and Markets Authority and the Bank of England. He spent 12 years as an assistant professor at the Kellogg School of Management at Northwestern University. Polk earned a B.S. in physics and economics from Duke University, graduating magna cum laude, and a Ph.D. in finance from the University of Chicago Graduate School of Business.

  3. Honorable Mention


    Abstract

    2014 HONORABLE MENTION

    Robert Engle, Ph.D., and Emil Siriwardane

    We propose a new model of volatility where financial leverage amplifies equity volatility by what we call the “leverage multiplier”. The exact specification is motivated by standard structural models of credit; however, our parametrization departs from the classic Merton (1974) model and is, as we show, flexible and accurate enough to capture environments where the firm’s asset volatility is stochastic, asset returns can jump, and asset shocks are non-normal. As a result, our model also provides estimates of daily asset returns and asset volatility. In addition, our specification nests both a standard GARCH and the Merton model, which allows for a simple statistical test of how leverage interacts with equity volatility. Empirically, the Structural GARCH model outperforms a standard GARCH model for approximately 75% of the financial firms we analyze. We then apply the Structural GARCH model to two empirical applications: the leverage effect and systemic risk measurement.

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    Presentation
    Authors
    • Robert Engle

      Robert Engle, Ph.D.
      Michael Armellino Professor of Management and Financial Services
      Stern School of Business, New York University

      Robert Engle, the Michael Armellino Professor of Finance at New York University Stern School of Business, shared the 2003 Nobel Prize in Economics for his research on the concept of autoregressive conditional heteroskedasticity. His research has produced such statistical methods as autoregressive conditional duration and DCC models. He is director of the NYU Stern Volatility Institute and a cofounder of the Society for Financial Econometrics. Before joining NYU, he was Chancellor’s Associates Professor and Economics Department chair at the University of California at San Diego, and associate professor of economics at the Massachusetts Institute of Technology. He is a member of the National Academy of Science. He earned a B.S. from Williams College and an M.S. in physics and Ph.D. in economics from Cornell University.

    • Emil N. Siriwardane

      Emil N. Siriwardane
      Ph.D. student
      Stern School of Business, New York University

      Emil N. Siriwardane is working on a Ph.D. in finance at the New York University Stern School of Business, where he is researching systemic risk in financial markets, tail risk and extreme events in finance, volatility and regulation, among other things. Siriwardane earned a B.S.E. in operational engineering and financial engineering from Princeton University, graduating magna cum laude, and an M.Phil. in finance from the New York University Stern School of Business. 

  4. Honorable Mention


    Abstract

    2014 HONORABLE MENTION

    Torben G. Andersen, Ph.D., Nicola Fusari, Ph.D., and Viktor Todorov, Ph.D.

    We study the dynamic relation between aggregate stock market risks and risk premia via an exploration of the time series of equity-index option surfaces. The analysis is based on estimating a general parametric asset pricing model for the risk-neutral equity market dynamics using a panel of options on the S&P 500 index, while remaining fully nonparametric about the actual evolution of market risks. We find that the risk-neutral jump intensity, which controls the pricing of left tail risk, cannot be spanned by the market volatility (and its components), so an additional factor is required to account for its dynamics. This tail factor has no incremental predictive power for future equity return volatility or jumps beyond what is captured by the current and past level of volatility. In contrast, the novel factor is critical in predicting the future market excess returns over horizons up to one year, and it explains a large fraction of the future variance risk premium. We contrast our findings with those implied by structural asset pricing models that seek to rationalize the predictive power of option data. Relative to those studies, our findings suggest a wider wedge between the dynamics of equity market risks and the corresponding risk premia with the latter typically displaying a far more persistent reaction following market crises.

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    Presentation
    Authors
    • Torben G. Andersen

      Torben G. Andersen, Ph.D.
      Nathan S. and Mary P. Sharp Professor of Finance
      Kellogg School of Management, Northwestern University

      Torben G. Andersen is the Nathan S. and Mary P. Sharp Professor of Finance and Director of the International Business & Markets Program and Research Center. He is a faculty research associate of the National Bureau of Economic Research, an International Fellow of the Center for Research in Econometric Analysis of Economic Time Series in Aarhus, Denmark, and a Fellow of the Econometric Society. He has published widely in asset pricing, empirical finance and empirical market microstructure. He was the editor-in-chief of the Journal of Business and Economic Statistics and he has served on the editorial board of other leading journals. He earned a B.A. and M.A. in economics from the University of Aarhus, and an M.Phil. and Ph.D. in economics from Yale University.

    • Nicola Fusari

      Nicola Fusari, Ph.D.
      Assistant Professor of Finance
      Carey Business School, Johns Hopkins University

      Nicola Fusari is an assistant professor of finance at the Johns Hopkins University Carey Business School. His work focuses on theoretical and empirical asset pricing with particular attention to derivatives markets and market volatility. His current work explores the information contained in large panels of options for estimating and describing market and variance risk premia dynamics. He earned his undergraduate degree from the University of Verona in Italy and a Ph.D. from the Swiss Finance Institute at the University of Lugano. He also spent time as a post-doctoral researcher at the Kellogg School of Management at Northwestern University.

    • Viktor Todorov

      Viktor Todorov, Ph.D.
      Associate Professor of Finance
      Kellogg School of Management, Northwestern University

      Viktor Todorov is an associate professor of Finance at the Kellogg School of Management at Northwestern University. His research interests include theoretical and empirical asset pricing, derivatives and econometrics. His recent research focuses on robust estimation of asset pricing models using high-frequency financial data as well as the identification and modeling of jump risk premium combining information from options markets. Todorov earned a B.A. in finance from Varna University of Economics, in Bulgaria, an M.A. in economics from Central European University, in Hungary, and a Ph.D. in economics at Duke University.

  5. Honorable Mention


    Abstract

    2014 HONORABLE MENTION

    Samuel M. Hartzmark

    I document a new stylized fact about how investors trade assets: individuals are more likely to sell the extreme winning and extreme losing positions in their portfolio (“the rank effect”). This effect is not driven by firm-specific information or the level of returns itself, but is associated with the salience of extreme portfolio positions. The rank effect is exhibited by both retail traders and mutual fund managers, and is large enough to induce significant price reversals in stocks of up to 160 basis points per month. The effect indicates that trades in a given stock depend on what else is in an investor’s portfolio.

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    Presentation
    Authors
    • Samuel M. Hartzmark

      Samuel M. Hartzmark
      Ph.D. student
      Marshall School of Business, University of Southern California

      Samuel Hartzmark is a Ph.D. student in finance and business economics at the Marshall School of Business at the University of Southern California. His work has been published in Journal of Financial Economics and Quarterly Journal of Finance. At the Financial Research Association Conference in 2013, he won both the UBS Global Asset Management Award and the Michael J. Barclay Award. Hartzmark earned a B.A. in mathematics/economics and religion from Emory University and an M.B.A. from the Booth School of Business at the University of Chicago.