Robert Stambaugh

Robert Stambaugh is the Miller Anderson & Sherrerd Professor of Finance at the Wharton School of the University of Pennsylvania.   He is a Fellow and former President of the American Finance Association, a Fellow of the Financial Management Association, and a Research Associate of the National Bureau of Economic Research.  Professor Stambaugh has been the editor of the Journal of Finance, an editor of the Review of Financial Studies, an associate editor of those journals as well as the Journal of Financial Economics, and a member of the first editorial committee of the Annual Review of Financial Economics.   He has published articles on topics including return predictability, asset pricing tests, portfolio choice, parameter uncertainty, liquidity risk, volatility, performance evaluation, investor sentiment, and activeversuspassive investing.  His research awards include a SmithBreeden first prize for an article in the Journal of Finance as well as a FamaDFA first prize and three second prizes for articles in the Journal of Financial Economics.  Before joining Wharton in 1988, he was Professor of Finance at the University of Chicago, where he received his PhD in 1981.   Professor Stambaugh visited Harvard University as a Marvin Bower Fellow in 199798.

Robert F. Stambaugh and Yu Yuan (2017), Mispricing Factors, Review of Financial Studies (forthcoming).

Abstract: A fourfactor model with two “mispricing” factors, in addition to market and size factors, accommodates a large set of anomalies better than notable four and fivefactor alternative models. Moreover, our size factor reveals a smallfirm premium nearly twice usual estimates. The mispricing factors aggregate information across 11 prominent anomalies by averaging rankings within two clusters exhibiting the greatest comovement in longshort returns. Investor sentiment predicts the mispricing factors, especially their short legs, consistent with a mispricing interpretation and the asymmetry in ease of buying versus shorting. Replacing booktomarket with a single composite mispricing factor produces a betterperforming threefactor model.

Robert F. Stambaugh, Lubos Pastor, Lucian A. Taylor (2017), Do Funds Make More When They Trade More?, Journal of Finance (forthcoming).

Abstract: We find that active mutual funds perform better after trading more.  This timeseries relation between a fund's turnover and its subsequent benchmarkadjusted return is especially strong for small, highfee funds.   These results are consistent with highfee funds having greater skill to identify timevarying profit opportunities and with small funds being more able to exploit those opportunities.   In addition to this novel evidence of managerial skill and fundlevel decreasing returns to scale, we find evidence of industrylevel decreasing returns:   The positive turnoverperformance relation weakens when funds act more in concert.   We also identify a common component of fund trading that is correlated with mispricing proxies and helps predict fund returns.

Jianan Liu, Robert F. Stambaugh, Yu Yuan (2017), Absolving Beta of Volatility's Effects, Journal of Financial Economics (forthcoming).

Robert F. Stambaugh, Jianfeng Yu, Yu Yuan (2015), Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle, Journal of Finance, 70, pp. 19031948.

Robert F. Stambaugh, Luke Taylor, Lubos Pastor (2015), Scale and Skill in Active Management, Journal of Financial Economics, 116, pp. 2345.

Abstract: We empirically analyze the nature of returns to scale in active mutual fund management. We find strong evidence of decreasing returns at the industry level. As the size of the active mutual fund industry increases, a fund?s ability to outperform passive benchmarks declines. At the fund level, all methods considered indicate decreasing returns, though estimates that avoid econometric biases are insignificant. We also find that the active management industry has become more skilled over time. This upward trend in skill coincides with industry growth, which precludes the skill improvement from boosting fund performance. Finally, we find that performance deteriorates over a typical fund?s lifetime. This result can also be explained by industrylevel decreasing returns to scale.

Robert F. Stambaugh, Jianfeng Yu, Yu Yuan (2014), The Long of It: Odds That Investor Sentiment Spuriously Predicts Anomaly Returns, Journal of Financial Economics, 114, pp. 613619.

Abstract: Extremely long odds accompany the chance that spuriousregression bias accounts for investor sentiment's observed role in stockreturn anomalies.   We replace investor sentiment with a simulated persistent series in regressions reported by Stambaugh, Yu, and Yuan (2012), who find higher longshort anomaly profits following high sentiment, due entirely to the short leg.  Among 200 million simulated regressors, we find none that support those conclusions as strongly as investor sentiment.  The key is consistency across anomalies.  Obtaining just the predicted signs for the regression coefficients across the 11 anomalies examined in the above study occurs only once for every 43 simulated regressors.

Robert F. Stambaugh (2014), Investment Noise and Trends, Journal of Finance, 69 (4), pp. 14151453.

Abstract: During the past few decades, the fraction of the equity market owned directly by individuals declined significantly. The same period witnessed investment trends that include the growth of indexing as well as shifts by active managers toward lower fees and more indexlike investing. I develop an equilibrium model linking these investment trends to the decline in individual ownership, interpreting the latter as a reduction in noise trading. Active management corrects most noisetrader induced mispricing, and the fraction left uncorrected shrinks as noise traders' stake in the market declines. Less mispricing then dictates a smaller footprint for active management.

Lubos Pastor and Robert F. Stambaugh (2012), On the Size of the Active Management Industry, Journal of Political Economy.

Robert F. Stambaugh, Jianfeng Yu, Yu Yuan (2012), The Short of It: Investor Sentiment and Anomalies, Journal of Financial Economics, 288302.

Lubos Pastor and Robert F. Stambaugh (2012), Are Stocks Really Less Volatile in the Long Run?, Journal of Finance, 431478.

Past Courses

FNCE205 INVESTMENT MANAGEMENT

This course studies the concepts and evidence relevant to the management of investment portfolios. Topics include diversification, asset allocation, portfolio optimization, factor models, the relation between risk and return, trading, passive (e.g., indexfund) and active (e.g., hedgefund, longshort) strategies, mutual funds, performance evaluation, longhorizon investing and simulation. The course deals very little with individual security valuation and discretionary investing (i.e., "equity research" or "stock picking").

FNCE720 INVESTMENT MANAGEMENT

This course studies the concepts and evidence relevant to the management of investment portfolios. Topics include diversification, asset allocation, portfolio optimization, factor models, the relation between risk and return, trading, passive (e.g., indexfund) and active (e.g., hedgefund, longshort) strategies, mutual funds, perfermance evaluation, longhorizon investing and simulation. The course deals very little with individual security valuation and discretionary investing (i.e., "equity research" or "stock picking").

FNCE921 INTRO EMPIR METHODS FIN

This course is an introduction to empirical methods commonly employed in finance. It provides the background for FNCE 934, Empirical Research in Finance. The course is organized around empirical papers with an emphasis on econometric methods. A heavy reliance will be placed on analysis of financial data.

FNCE934 EMPIRICAL METH IN ASSET

This course has three main objectives: The first object is to introduce students to the fundamental works and the frontier of research in dynamic asset pricing. We will cover recent models that have been proposed to shed light on intreguing and important empirical patterns in the cross section and in the time series. Topics include nonseparable utilities, market incompleteness, learning, uncertainty, differences of opionions, exante and expost asymmetric information, ambiguity and Knightian uncertainty. The second objective is to teach students how to think of asset pricing research under a bigger or richer framework. We shall focus on the interactions between asset pricing and other fields such as macroeconomics, corporate finance, financial institutions, and international finance. The goal of inventigating the joint dynamics is not only to better understand how asset prices are determined, but also (maybe more importantly) how would asset pricing dynamics affect other important economic vaiables such as investment, corporate payout and financing, unemployment, risk sharing, and international capital flows. Students will learn productionbased asset pricing models, particularly the asset pricing models with investmentspecific technology shocks, risk shocks, financial friction, searching frictions and information ,frictions. Of course, the advanced solution methods will focus too. The third objective is to introduce advanced empirical methods to analyze the data and the quantitative dynamic models. It includes how to estimate structural dynamic models, how evaluate structural models beyond goodnessoffit tests, how confront the models predictions with empirical data by simulation and resampling techniques, and how to efficiently test models and explore new patterns using asset pricing and macro data.

FamaDFA Prize (firstplace paper, Journal of Financial Economics), 2016 Marshall E. Blume Prize Honorable Mention, 2016 Best Paper, Jacobs Levy Equity Managment Center for Quantitative Financial Research, 2015 Marshall E. Blume Prize honorable mention, 2014 Fellow of the American Finance Association, 2014 Whitebox Advisors first prize, 2012 AQR Insight Award honorable mention, 2012 Marshall E. Blume Prize honorable mention, 2012 Fellow of the Financial Management Association, 2010 Goldman Sachs Asset Management Award (Western Finance Association), 2007 Moskowitz Prize honorable mention, 2003 GeewaxTerker Prize honorable mention, 2002 FamaDFA Prize (secondplace paper, Journal of Financial Economics), 2002 FamaDFA Prize (secondplace paper, Journal of Financial Economics), 1999 FamaDFA Prize (secondplace paper, Journal of Financial Economics), 1997 Marvin Bower Fellow, Harvard University Graduate School of Business, 1997 SmithBreeden Prize (firstprize paper, Journal of Finance), 1996 Batterymarch Fellow, 1985

Are Younger Managers Better – Or Younger Strategies?, Morningstar 03/11/2014 The Argument That Fund Managers Are Improving, Morningstar 03/07/2014 New Mutual Funds Better Than Older Ones?, CNN Money 03/02/2014 Has Your Fund Become Too Large, Or Is Industry Size the Problem?, Morningstar 02/28/2014 Are Young Managers All That?, Morningstar 02/27/2014 Why New Mutual Funds are Better, Wall Street Journal 02/21/2014 Description

For Older Investors, Old Rules May Not Apply, New York Times 06/19/2009 Now the Long Run Looks Riskier, Too, New York Times 03/28/2009 Yes, History Has Much to Say About This Market, New York Times 12/27/2008

Knowledge @ Wharton

Has the Hedge Fund Industry Lost Its Way?, Knowledge @ Wharton 11/06/2015 Why Youth Matters in Actively Managed Funds, Knowledge @ Wharton 05/14/2015 ‘Scale and Skill’: Why It’s Hard for Managed Funds to Beat the Indexers, Knowledge @ Wharton 04/29/2014 Wake Me up When September Ends, Knowledge @ Wharton 09/07/2011 If Index Funds Perform Better, Why Are Actively Managed Funds More Popular?, Knowledge @ Wharton 02/02/2011 Efficient Markets or Herd Mentality? The Future of Economic Forecasting, Knowledge @ Wharton 11/11/2009 The Impact of Highfrequency Trading: Manipulation, Distortion or a Betterfunctioning Market?, Knowledge @ Wharton 09/30/2009 Why Stockprice Volatility Should Never Be a Surprise, Even in the Long Run, Knowledge @ Wharton 04/29/2009 What’s Ahead for the Stock Market — and Quant Funds, Knowledge @ Wharton 08/22/2007 How Can Employers Improve Defined Contribution Plans?, Knowledge @ Wharton 10/18/2006 Don’t Sweat the Inverted Yield Curve: No One Really Knows What It Means, Knowledge @ Wharton 01/25/2006 Risks and Costs of Socially Responsible Investing, Knowledge @ Wharton 08/13/2003 Are Analysts Playing Us for Suckers?, Knowledge @ Wharton 07/04/2001 A Fresh Look At Mutual Funds’ Performance Data, Knowledge @ Wharton 03/28/2001