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Jack Treynor Prize

Recognizing superior academic working papers


The Q Group’s annual Jack Treynor Prize recognizes superior academic working papers with potential applications in the fields of investment management and financial markets. Each year, Q awards three prizes for prepublication working papers produced by post-doctoral researchers who are employed full-time by academic institutions. The Prize was first instituted in 2014.

View 2024 and Past Winners


The Q Group Research Committee organizes the prize competition and evaluates the submissions. Every spring, the Committee issues a call for working paper submissions with a mid-August deadline.  The Committee reviews the papers in September and October and makes its final selection of the three papers to honor with Jack Treynor Prize at Q Group’s Fall Conference.

The Q Group invites winners of the Prize to attend our subsequent Spring conference where they are formally recognized and given the opportunity to discuss their research with Q Group members. Q Group provides funding for travel and accommodations for up to three authors of each winning prize. The most recent winners are announced in the Journal of Portfolio Management as well as on the Q Group website. In addition, Q may invite the author(s) to present their paper at the Spring seminar or at a future seminar. When published, winning papers must acknowledge the Q Group Jack Treynor Prize in their introductory footnotes.

About Jack Treynor

Jack Treynor was one of the founders of modern quantitative investment management. His pioneering work on how discount rates should depend on risk anticipated and contributed to the development of the Capital Asset Pricing Model. Treynor subsequently made numerous other contributions in the areas of performance evaluation, risk management, trading analytics, and inflation dynamics. As long-time editor of the Financial Analysts Journal, Treynor substantially raised the quality of discourse among financial analysts. Many of his articles, including those written under the pseudonym Walter Bagehot, have become classics of investment management. Treynor was a Q Group Research Fellow and a long-time member of Q Group where his contributions to program and discussions have been, and remain, invaluable.


2024 Jack Treynor Prize Winners

Valuation Fundamentals

Paul H. Décaire, Arizona State University

John R. Graham, Duke University; National Bureau of Economic Research (NBER)

This paper brings a fresh perspective to the investigation of 78,000 analyst forecasts from 93 countries over 24 years. The authors extract the analysts’ estimates of rates of long-term terminal growth; short-term free cash flows; and their subjective discount rates.

They find that the analysts’ discount rates are unbiased predictors of future returns and that return predictability is associated with innovations in firm subjective betas. To understand these results, they investigate how analysts update discount rate inputs. Drawing from textual descriptions and using a noisy information model, they find that analysts are forward-looking and attempt to filter estimation noise when adjusting inputs. They find that these subjective adjustments appear to mitigate the effect of noise in model estimates, and lead to stickier processes than simply using benchmark model outputs.

Complexity in Factor Pricing Models

Antoine Didisheim, The University of Melbourne; Swiss Finance Institute
Shikun Ke, Yale University
Bryan T. Kelly, Yale; AQR Capital Management, LLC; National Bureau of Economic Research (NBER)

Semyon Malamud, Ecole Polytechnique Federale de Lausanne; Centre for Economic Policy Research (CEPR); Swiss Finance Institute

The authors build a theoretical model of the behavior of machine learning asset pricing models in which the number of factors continue increasing as the number of stocks increase. Usually larger numbers of factors would usually be associated with overfitting in sample leading to degraded out of sample prediction. But the authors show that under their model, expected out-of-sample model performance—in terms of Stochastic Discount Factor Sharpe ratio and test asset pricing errors—is improving rather than degrading as complexity increases. They further perform empirical tests that agree with the virtue of increased complexity in the cross-section of stock returns. They find that models with an extremely large number of factors (more than the number of training observations or base assets) outperform simpler alternatives by a large margin.


Forecasting Crashes with a Smile

Ian W. R. Martin, London School of Economics

Ran Shi, University of Colorado Boulder


The well-known skew in individual stock implied volatilities (due to a strong preference for crash insurance) means that probabilities of large drops in individual stock prices are overpredicted by options prices. To correct this, the authors assume a representative investor with a power utility function, and note that under their assumptions the representative investor’s stochastic discount factor will be a power of the overall market’s return. In that case, knowing the joint distribution of the market and an individual stock would allow the recovery of the real-world probability from the risk-neutral one. While there are generally no market observables giving the joint distribution, the Fréchet–Hoeffding inequalities give lower and upper bounds on any copula function linking the two. The authors show that the lower bound in particular gives a very good estimate such that out of sample predictions of individual stock crash probabilities are significantly improved.

Past Jack Treynor Prize Winners

2023 

A Joint Factor Model for Bonds, Stocks, and Options
Turan G. Bali, Georgetown University
Heiner Beckmeyer, University of Münster
Amit Goyal, University of Lausanne and Swiss Finance Institute

The authors propose a parsimonious reduced-form joint factor model for bonds, options, and stocks.  Using Kelly, Pruitt, and Su’s

instrumented principal components analysis, they reduce 107 characteristics to six latent factors, which explain 31% of the total variation of firm asset returns; 22% for options, 32% for stocks, and 37% for bonds. The authors find that the joint model explains almost all the alpha in characteristic-managed portfolios, whereas single-asset-class models leave much of the alpha unexplained.


Counterproductive Sustainable Investing: The Impact Elasticity of Brown and Green Firms
Samuel M. Hartzmark, Boston College and NBER
Kelly Shue, Yale University and NBER

The authors develop a new measure of impact elasticity, defined as a firm’s change in environmental impact due to a change in its cost of capital.  They show empirically that reducing financing costs for already green firms leads at best to minor improvements in impact.  In contrast, increasing financing costs for brown firms leads to large negative changes in firm impact.  Thus, sustainable investing that directs capital away from brown firms and toward green firms may be counterproductive by making brown firms more brown without making green firms more green.  

Forecasting and Managing Correlation Risks
Tim Bollerslev, Duke University, NBER, and CREATES
Sophia Zhengzi Li, Rutgers University
Yushan Tang, Rutgers University

The authors propose a novel, easy-to-implement framework for forecasting correlation risks based on a large set of salient realized correlation and factor features with the sparsity-encouraging LASSO technique.  The new approach produces statistically superior out-of-sample forecasts compared to commonly used procedures.  They further demonstrate that the forecasts translate into significant economic gains in higher pairs trading profits, better equity premium predictions, more accurate portfolio risk targeting, and superior overall risk control and minimization.

2022

Is Physical Climate Risk Priced? Evidence from Regional Variation in Exposure to Heat Stress
Viral V. Acharya, New York University Stern School of Business; CEPR; ECGI; and NBER
Tim Johnson, University of Illinois Urbana-Champaign
Suresh Sundaresan, Columbia Business School
Tuomas Tomunen, Boston College Carroll School of Management

The authors exploit regional variation in exposure to heat stress to study if physical climate risk is priced in municipal and corporate bonds as well as in equity markets. They find that local exposure to substantial damages (1% of GDP) related to heat stress is associated with municipal bond yield spreads that are higher by around 15 basis points per annum. Among S&P 500 companies, one standard deviation increase in exposure to heat stress is associated with yield spreads that are higher by around 40 bps for subinvestment grade corporate bonds, with little effect for investment grade bond spreads, and with conditional expected returns on stocks that are higher by around 45 bps. These results are observed robustly only starting in 2013–15 and are mostly absent for physical risks other than exposure to heat stress.

Performance of Characteristic-Sorted Portfolios
Aydogan Alti, University of Texas at Austin
Travis L. Johnson, University of Texas at Austin
Sheridan Titman, University of Texas at Austin

This paper presents an elegant model for persistent fluctuations in characteristic-sorted portfolio returns (i.e., based on factors like value, investment, profitability, and size). With plausible parameter values, the adjusted standard errors double, casting doubt on the interpretation of the historical performance of characteristic-sorted portfolios as evidence of long-term return premia. The authors show that investors’ posterior beliefs about expected returns are highly dependent on their priors about persistence, even after observing close to 60 years of data. This research provides a framework to understand phenomena like the long underperformance of value and the strengthening of the profitability effect.

Discount-Rate Risk in Private Equity: Evidence from Secondary Market Transactions
Brian Boyer, Marriott School of Business, Brigham Young University
Taylor D. Nadauld, Marriott School of Business, Brigham Young University
Keith P. Vorkink, Marriott School of Business, Brigham Young University
Michael S. Weisbach, Fisher School of Business, Ohio State University; NBER

The authors create private equity (PE) indices using secondary market transactions of Limited Partner (LP) shares. They find that PE discount rates vary considerably. Empirically, their buyout fund indices track public equity much more closely than indices based on PE Fund-reported NAVs.  These new indices have market betas of about 1.8. This is more consistent with the idea that buyouts with increased leverage have higher betas than NAV-based betas, which are less than one due to smoothing.  Their indices also produce CAPM alpha close to zero, in contrast to previous literature showing positive alpha for buyout funds. Their empirical results suggest that the Generalized Public Market Equivalent of Korteweg and Nagel does not appropriately represent the marginal utility gain from an incremental investment in private equity for investors with access to secondary markets.

2021

CLO Performance
Larry Cordell, Philadelphia Federal Reserve
Michael Roberts, Wharton School and NBER
Michael Schwert, Wharton School

This paper studies collateralized loan obligations (“CLOs”).  About $3 trillion of leveraged loans have been written since 2008, of which about $2.1 trillion have been securitized into CLOs.  The authors show that the equity tranches of CLOs have provided significant excess risk-adjusted returns in normal markets and also during the 2008 financial crisis and the pandemic.  This result is mainly due to regulatory pressures to hold safe assets that have made the demand for very safe CLO tranches artificially high.  This demand leads to lower yields on the funding tranches, leaving more room for the equity tranches to outperform.  The authors find no evidence that manager skill in picking assets causes this outperformance: they find that it appears to be simply the structural fact of the low cost of the long-term financing structure of CLOs.

How Competitive is the Stock Market
Valentin Haddad, UCLA
Paul Huebner, UCLA
Erik Loualiche, University of Minnesota

This theoretical and empirical paper seeks to quantify the effects of investors moving from active management to indexing.  Over the last 20 years, about 30% of the market moved from active to passive.  While many observers feel that some level of indexing makes markets unacceptably inelastic to new price information, quantifying that level is hard.  The authors take their theory to the data and estimate that about half the decrease in active investors over the last 20 years has been mitigated by the remaining active investors getting more aggressive, leading to an overall 15% decrease in elasticity of prices to changes in fundamentals.

Predictable Price Pressure
Samuel Hartzmark, University of Chicago and NBER
David Solomon, Boston College

Hartzmark and Solomon show that dividend reinvestment – which is certainly not a surprise as dividends are announced far before their ex-date – leads to price increases that last for about a year.  Similarly, stock compensation payouts that lead to predictable selling lead to noticeable downward price pressure even though the market can easily anticipate the selling.  These effects occur in highly liquid markets and fly in the face of standard finance models.  The market inelasticity revealed by this paper is consistent with the Inelastic Markets Hypothesis that Gabaix and Koijen advanced in one of last year’s Jack Treynor Prize papers.


2020

In Search of the Origins of Financial Fluctuations: The Inelastic Markets Hypothesis
Xavier Gabaix, Harvard
Ralph Koijen, University of Chicago

This thought-provoking paper models the effects of stock-bond mandate ratios. For example, certain investment vehicles may have a mandate to maintain close to an 80:20 stock:bond ratio. The authors show that under such mandates, flows between bonds and stocks will cause startling price changes in the overall value of stocks. In a stylized model with one 80:20 mixed stock-bond fund and one bond fund, a $1 flow from bonds to stocks will cause stock prices overall to go up by $5. The authors then use market data to test the presence of this effect empirically, and find that indeed overall markets do react as if there is an 80:20 mandate. The authors are aware of the unorthodox nature of this result; they have thoughtfully explored many possible objections but find that their hypothesis continues to hold up.

Reconsidering Returns
Samuel Hartzmark, University of Chicago
David Solomon, Boston College

The authors document a widespread reporting phenomenon whereby stock market results are usually reported on a price basis rather than on a total return basis. Leaving out dividends and other distributions causes under-reporting of true returns to investors, leading to more negative market sentiment commentary. While institutional investors know that returns should include distributions, market movements suggest that the adjustment to total returns is not fully incorporated in prices. The authors conjecture that price-based reporting can explain part of the equity risk premium.

Regulatory Limits to Risk Management
Ishita Sen, Harvard

This paper looks at the difference between regulatory requirements for risk-based capital in insurance companies, and the actual hedging that would be needed to fully offset risk exposures to equities and interest rates. Firms’ actual hedging positions for VA (variable annuities) are carefully examined. The conclusion is that regulatory requirements encourage suboptimal hedging. These requirements can lead to offloading of risk into off-balance-sheet entities, which puts the stability of the broader financial system at risk.


2019

Expected Correlation and Future Market Returns
Adrian Buss, INSEAD and CEPR
Lorenzo Schönleber, Frankfurt School of Finance & Management
Grigory Vilkov, Frankfurt School of Finance & Management

Implied correlation, jointly extracted from index and stock options, is a robust predictor of long-term market returns.  Its predictive power stems from its role as a leading pro-cyclical state variable that predicts future investment opportunities, financial-market risks, and macroeconomic conditions for up to 18 months ahead.  The predictability is inherited from the interplay between its three main components: implied market variance, implied idiosyncratic variance, and the implied dispersion of market betas.  The predictability is not subsumed by measures of tail risk.  Out-of-sample evidence suggests that that the predictability can produce substantial economic gains for market-timing strategies.

Factor Momentum and the Momentum Factor
Sina Ehsani, Northern Illinois University
Juhani Linnainmaa, Dartmouth College

Momentum in individual stock returns comes from momentum in factor returns.  Most factors are positively autocorrelated: the average factor earns a monthly return of 1 basis point following a year of losses and 53 basis points following a positive year.  Factor momentum explains all forms of individual stock momentum.  Stock momentum strategies indirectly time factors: they profit when the factors remain autocorrelated, and crash when these autocorrelations break down.  Momentum is not a distinct risk factor; it aggregates the autocorrelations found in all other factors.

Molecular Genetics, Risk Aversion, Return Perceptions, and Stock Market Participation
Richard Sias, University of Arizona
Laura T. Starks, University of Texas at Austin
H. J. Turtle, Colorado State University

Molecular variation in DNA related to cognition, personality, health, and body shape predicts an individual’s equity market participation, risk aversion, and beliefs regarding the distribution of expected equity returns.  Molecular genetic endowments also are strongly associated with many of the investor characteristics (e.g., trust, sociability, wealth) shown to explain heterogeneity in equity market participation.  This analysis helps explain why financial choices are heritable and how these genetic endowments can help explain the links between financial choices, risk aversion, beliefs, and other variables known to predict stock market participation.


2018

The Economics of Factor Timing
Valentin Haddad, UCLA & NBER
Serhiy Kozak, University of Michigan
Shrihari Santosh, University of Maryland

The authors use economic restrictions implied by asset pricing theory to empirically identify and characterize optimal factor timing portfolios.  They find that long-short equity factors are strongly and robustly predictable.  Several of these portfolios have small average risk prices.  These small prices suggest that the economic risks investors worry about conditionally are often different from those that they worry about on average. For bonds and foreign exchange, long-short portfolios sorted on maturity or interest rate differential also are predictable.

How Alternative Are Private Markets?
William N. Goetzmann, Yale School of Management and NBER
Elise Gourier, Queen Mary University of London and CEPR
Ludovic Phalippou, University of Oxford

The authors estimate a parsimonious set of factor portfolios using returns from a comprehensive panel of private market funds. They then determine whether commonly used public equity factors span these private market factors, and whether the private market factors are priced in the cross-section of private market funds.  Four main private market factors explain returns in the cross-section.  One factor, dominated by large leveraged buyout funds, generated a significant positive premium.  A second factor, dominated by venture capital funds, also was priced over the past thirty years.  The pricing of the other two factors, related to real assets and private debt funds, was smaller but has been increasing over time.

Labor Market Competitor Network and the Transmission of Shocks
Yukun Liu, Yale University
Sissi Xi Wu, New York University

Using online job postings, the authors determine the extent to which firms in different industries compete for similar workers.  They show that the overlap between firms’ labor market competitors and their product market rivals is less than 20 percent.  The authors then show that a firm’s stock returns can be partially predicted by the lagged stock returns of its labor market competitors as news about labor market conditions propagates across industries.  A long-short strategy based on this observation generates an annualized alpha of 9.36 percent.


2017

Performance Isn’t Everything: Personal Characteristics and Career Outcomes of Mutual Fund Managers
Brad Barber, University of California, Davis
Anna Scherbina, University of California, Davis
Bernd Schlusche, Board of Governors of the Federal Reserve System

Past performance—measured by returns and fund flows—largely determine mutual fund managers’ career outcomes. Managers’ personal attributes also matter. All else equal, female fund managers are less likely to be promoted than male managers, and they have shorter tenures. Furthermore, managers from elite schools and those holding advanced degrees have better career outcomes, while older managers face significantly worse career prospects, possibly by choice.

Sensation-Seeking Hedge Funds
Stephen Brown, NYU Stern School of Business and Monash Business School
Yan Lu, College of Business, University of Central Florida
Sugata Ray, Culverhouse College of Commerce, University of Alabama
Melvyn Teo, Lee Kong Chian School of Business, Singapore Management University

The authors collect data on hedge fund manager automobile purchases and show that managers who own powerful sports cars take on more investment risk than do other managers but do not deliver higher returns.  Moreover, funds managed by performance car owners exhibit higher operational risk and are more likely to fail.  Performance car owners demonstrate other attributes associated with sensation seeking, such as a preference for lottery-like stocks, unconventional strategies, and active trading.

Trading on Talent: Human Capital and Firm Performance
Anastassia Fedyk, Harvard University
James Hodson, Jožef Stefan Institute

Using a novel dataset with information about 37 million employees of U.S. public companies, the authors show that human capital affects firm performance.  Firms with low employee turnover perform better in the market than firms with higher turnover. Also, firms with disproportionately more employees with sales-oriented skills perform better than others, whereas firms with more employees with administrative skills underperform. The effects of skill are heterogeneous across industries.  Web development skills are more valuable in information industries, but sales-oriented skills are not notably more valuable in Finance.


2016

Credit-Implied Volatility
Bryan Kelly, University of Chicago
Gerardo Manzo, University of Chicago
Diogo Palhares, AQR

The pricing of corporate credit can be succinctly understood via the credit-implied volatility (CIV) surface. Using a method analogous to the estimation of implied volatility from options contracts, the authors compute credit-implied volatility each month from the firm-by-maturity panel of CDS spreads using the Merton model. The process transforms CDS spreads into units of asset volatility. The CIV surface facilitates direct comparison of credit spreads at different “moneyness” (firm leverage) and time to maturity. The authors use this framework to characterize the behavior of corporate credit markets. They examine moneyness (leverage); they show that of credit spreads dynamics can be parsimoniously described with three clearly interpretable factors; and they examine the cross section of CDS risk premia.

Extrapolation Bias and the Predictability of Stock Returns by Price-Scaled Variables
Stefano Cassella, Krannert School of Management, Purdue University
Huseyin Gulen, Krannert School of Management, Purdue University

Using survey data on expectations of future stock returns, the authors estimate the degree of extrapolation bias (DOX)—the belief that what has happened recently will continue to happen—in investor expectations. Considerable time-series variation exists in the DOX, evidence shows that it can predicted to a meaningful extent.  The authors show that the ability of the dividend-price ratio to predict the equity premium is contingent on the DOX. There is Predictability is when the DOX is high and weak otherwise.  These results help answer a critical question: when will an overvalued asset, or even a bubble, experience a correction?.

Lazy Prices
Lauren Cohen, Harvard Business School
Christopher Malloy, Harvard Business School
Quoc Nguyen, University of Illinois at Chicago

When making required regulatory financial reports, firms very often repeat the same MD&A texts that they most recently used. Changes in these texts can be quite informative. Using the complete history of regular quarterly and annual filings by U.S. corporations from 1995-2014, the authors show that changes to the language and construction of financial reports have strong implications for firms’ future returns: a portfolio that shorts “changers” and buys “non-changers” earns up to 188 basis points per month (over 22% per year) in abnormal returns in the future. Changes in language referring to the executive (CEO and CFO) team, or regarding litigation, are especially informative for future returns.


2015

The Credit Spread Puzzle in the Merton Model—Myth or Reality?
Peter Feldhutter, London Business School
Stephen Schaefer, London Business School

The Merton model links bond values to stock values through option pricing theory. Past tests of the model have been unsatisfactory because they depend on default rates which are hard to estimate. This paper shows that when default rates are measured over long periods, the model explains the average level of investment grade spreads and captures the time series variation of the BBB-AAA spread well. The paper further shows that using data on individual firms—rather than a representative firm—is important for matching the slope of the term structure of credit spread.

Low Risk Anomalies?
Paul Schneider, University of Lugano and Swiss Finance Institute
Christian Wagner, Copenhagen Business School
Josef Zechner, CEPR and ECGI, WU Vienna

The stocks of low risk firms have performed surprisingly well when compared to the predictions of standard asset pricing models. This study shows that their performance can be explained by return skewness—the tendency for large negative returns to be more common than large positive returns. Such returns generally are associated with financial distress and the risk of default. With increasing downside risk, the standard capital asset pricing model (CAPM) increasingly overestimates expected equity returns relative to firms’ true (skew-adjusted) market risk.

A Protocol for Factor Identification
Kuntara Pukthuanthong, University of Missouri
Richard Roll, California Institute of Technology

Asset pricing models generally examine various factors for their ability to predict average returns. Several hundred factors have been suggested in the literature. This study proposes a protocol for determining which factors are related to risks and which are related to mean returns. The results will allow quantitative investors to better construct portfolios and to understand the risk and expected returns associated with their portfolios.


2014

Betting Against Beta or Demand for Lottery
Turan G. Bali, Georgetown University
Stephen J. Brown, New York University and University of Melbourne
Scott Murray, University of Nebraska-Lincoln
Yi Tang, Fordham University

Recent academic research has shown that stocks with high betas have worse performance than low beta stocks, which violates conventional finance theory. Beta is the tendency for a stock to rise or fall with the broader market. The evidence in this paper suggests that high beta stocks also or fall with the broader market. The evidence in this paper suggests that high beta stocks also tend to provide lottery-like returns and investors seeking these lottery-like payoffs push up the prices of high beta stocks, causing them to subsequently under perform.

The Shorting Premium and Asset Pricing Anomalies
Itamar Drechsler, New York University and NBER
Qingyi (Freda) Drechsler, Wharton Research Data Service

Academics and practitioners have identified several asset-pricing anomalies that can be associated with seemingly profitable trading strategies. This paper shows that many of these anomalies occur in stocks for which there are a limited supply of shares that can be shorted, or where the costs of shorting are high. Thus, some of the apparent profits available to shorting these stocks don’t exist because either they cannot be shorted or it is too expensive to do so.

X-CAPM: An Extrapolative Capital Asset Pricing Model
Nicholas Barberis, Yale School of Management
Robin Greenwood, Harvard Business School
Lawrence Jin, Yale School of Management
Andrei Shleifer, Harvard University

The Capital Asset Pricing Model (CAPM) is the most important model practitioners and academics use to understand the relation between expected returns and risk. However, empirical studies suggest that it does not work well in practice. This paper argues that asset pricing is the result of a tension between rational investors whose behavior is consistent with the CAPM and other rational investors who extrapolate future investment returns from recent investment returns.

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