The Journal of Finance

Thinking about Prices versus Thinking about Returns in Financial Markets

Published: 9/3/2019,  Volume: 74,  Issue: 6  |  DOI: 10.1111/jofi.12835  |  Cited by: 61

MARKUS GLASER, ZWETELINA ILIEWA, MARTIN WEBER

Prices and returns are alternative ways to present information and to elicit expectations in financial markets. But do investors think of prices and returns in the same way? We present three studies in which subjects differ in the level of expertise, amount of information, and type of incentive scheme. The results are consistent across all studies: asking subjects to forecast returns as opposed to prices results in higher expectations, whereas showing them return charts rather than price charts results in lower expectations. Experience is not a useful remedy but cognitive reflection mitigates the impact of format changes.

Opening the Black Box: Internal Capital Markets and Managerial Power

Published: 7/16/2013,  Volume: 68,  Issue: 4  |  DOI: 10.1111/jofi.12046  |  Cited by: 121

MARKUS GLASER, FLORENCIO LOPEZ‐DE‐SILANES, ZACHARIAS SAUTNER

We analyze the internal capital markets of a multinational conglomerate, using a unique panel data set of planned and actual allocations to business units and a survey of unit CEOs. Following cash windfalls, more powerful managers obtain larger allocations and increase investment substantially more than their less connected peers. We identify cash windfalls as a source of misallocation of capital, as more powerful managers overinvest and their units exhibit lower ex post performance and productivity. These findings contribute to our understanding of frictions in resource allocation within firms and point to an important channel through which power may lead to inefficiencies.

The Insurance Is the Lemon: Failing to Index Contracts

Published: 11/12/2019,  Volume: 75,  Issue: 1  |  DOI: 10.1111/jofi.12856  |  Cited by: 13

BARNEY HARTMAN‐GLASER, BENJAMIN HÉBERT

We model the widespread failure of contracts to share risk using available indices. A borrower and lender can share risk by conditioning repayments on an index. The lender has private information about the ability of this index to measure the true state that the borrower would like to hedge. The lender is risk‐averse and thus requires a premium to insure the borrower. The borrower, however, might be paying something for nothing if the index is a poor measure of the true state. We provide sufficient conditions for this effect to cause the borrower to choose a nonindexed contract instead.

Capital Share Dynamics When Firms Insure Workers

Published: 4/26/2019,  Volume: 74,  Issue: 4  |  DOI: 10.1111/jofi.12773  |  Cited by: 64

BARNEY HARTMAN‐GLASER, HANNO LUSTIG, MINDY Z. XIAOLAN

Although the aggregate capital share of U.S. firms has increased, capital share at the firm‐level has decreased. This divergence is due to mega‐firms that produce a larger output share without a proportionate increase in labor compensation. We develop a model in which firms insure workers against firm‐specific shocks, with more productive firms allocating more rents to shareholders, while less productive firms endogenously exit. Increasing firm‐level risk delays exit and increases the measure of mega‐firms, raising (lowering) the aggregate (average) capital share. An increase in the level of rents magnifies this effect. We present evidence that supports this mechanism.

Understanding Systematic Risk: A High‐Frequency Approach

Published: 5/8/2020,  Volume: 75,  Issue: 4  |  DOI: 10.1111/jofi.12898  |  Cited by: 93

MARKUS PELGER

Based on a novel high‐frequency data set for a large number of firms, I estimate the time‐varying latent continuous and jump factors that explain individual stock returns. The factors are estimated using principal component analysis applied to a local volatility and jump covariance matrix. I find four stable continuous systematic factors, which can be well approximated by a market, oil, finance, and electricity portfolio, while there is only one stable jump market factor. The exposure of stocks to these risk factors and their explained variation is time‐varying. The four continuous factors carry an intraday risk premium that reverses overnight.

Presidential Address: Macrofinance and Resilience

Published: 11/11/2024,  Volume: 79,  Issue: 6  |  DOI: 10.1111/jofi.13403  |  Cited by: 15

MARKUS K. BRUNNERMEIER

This address reviews macrofinance from the perspective of resilience. It argues for a shift in mindset, away from risk management toward resilience management. It proposes a new resilience measure, and contrasts micro‐ and macro‐resilience. It also classifies macrofinance models in first‐ (log‐linearized) and second‐generation models, and links the important themes of macrofinance to resilience.

High‐Frequency Trading and Market Performance

Published: 2/8/2020,  Volume: 75,  Issue: 3  |  DOI: 10.1111/jofi.12882  |  Cited by: 131

MARKUS BALDAUF, JOSHUA MOLLNER

We study the consequences of, and potential policy responses to, high‐frequency trading (HFT) via the tradeoff between liquidity and information production. Faster speeds facilitate HFT, with consequences for this tradeoff: Information production decreases because informed traders have less time to trade before HFTs react, but liquidity (measured by the bid‐ask spread) improves because informational asymmetries decline. HFT also pushes outcomes inside the frontier of this tradeoff. However, outcomes can be restored to the frontier by replacing the limit order book with one of two alternative mechanisms: delaying all orders except cancellations or implementing frequent batch auctions.

Hedge Funds and the Technology Bubble

Published: 10/2004,  Volume: 59,  Issue: 5  |  DOI: 10.1111/j.1540-6261.2004.00690.x  |  Cited by: 793

MARKUS K. BRUNNERMEIER, STEFAN NAGEL

This paper documents that hedge funds did not exert a correcting force on stock prices during the technology bubble. Instead, they were heavily invested in technology stocks. This does not seem to be the result of unawareness of the bubble: Hedge funds captured the upturn, but, by reducing their positions in stocks that were about to decline, avoided much of the downturn. Our findings question the efficient markets notion that rational speculators always stabilize prices. They are consistent with models in which rational investors may prefer to ride bubbles because of predictable investor sentiment and limits to arbitrage.

The Maturity Rat Race

Published: 3/7/2013,  Volume: 68,  Issue: 2  |  DOI: 10.1111/jofi.12005  |  Cited by: 257

MARKUS K. BRUNNERMEIER, MARTIN OEHMKE

Why do some firms, especially financial institutions, finance themselves so short‐term? We show that extreme reliance on short‐term financing may be the outcome of a maturity rat race: a borrower may have an incentive to shorten the maturity of an individual creditor's debt contract because this dilutes other creditors. In response, other creditors opt for shorter maturity contracts as well. This dynamic toward short maturities is present whenever interim information is mostly about the probability of default rather than the recovery in default. For borrowers that cannot commit to a maturity structure, equilibrium financing is inefficiently short‐term.

The Limits of Model‐Based Regulation

Published: 4/12/2022,  Volume: 77,  Issue: 3  |  DOI: 10.1111/jofi.13124  |  Cited by: 87

MARKUS BEHN, RAINER HASELMANN, VIKRANT VIG

Using loan‐level data from Germany, we investigate how the introduction of model‐based capital regulation affected banks' ability to absorb shocks. The objective of this regulation was to enhance financial stability by making capital requirements responsive to asset risk. Our evidence suggests that banks “optimized” model‐based regulation to lower their capital requirements. Banks systematically underreported risk, with underreporting more pronounced for banks with higher gains from it. Moreover, large banks benefitted from the regulation at the expense of smaller banks. Overall, our results suggest that sophisticated rules may have undesired effects if strategic misbehavior is difficult to detect.

Procyclical Capital Regulation and Lending

Published: 3/18/2016,  Volume: 71,  Issue: 2  |  DOI: 10.1111/jofi.12368  |  Cited by: 192

MARKUS BEHN, RAINER HASELMANN, PAUL WACHTEL

We use a quasi‐experimental research design to examine the effect of model‐based capital regulation on the procyclicality of bank lending and firms' access to funds. In response to an exogenous shock to credit risk in the German economy, capital charges for loans under model‐based regulation increased by 0.5 percentage points. As a consequence, banks reduced the amount of these loans by 2.1 to 3.9 percentage points more than for loans under the traditional approach with fixed capital charges. We find an even stronger effect when we examine aggregate firm borrowing, suggesting that microprudential capital regulation can have sizeable real effects.

Forest through the Trees: Building Cross‐Sections of Stock Returns

Published: 9/2/2025,  Volume: 80,  Issue: 5  |  DOI: 10.1111/jofi.13477  |  Cited by: 18

SVETLANA BRYZGALOVA, MARKUS PELGER, JASON ZHU

We build cross‐sections of asset returns for a given set of characteristics, that is, managed portfolios serving as test assets, as well as building blocks for tradable risk factors. We use decision trees to endogenously group similar stocks together by selecting optimal portfolio splits to span the stochastic discount factor, projected on individual stocks. Our portfolios are interpretable and well diversified, reflecting many characteristics and their interactions. Compared to combinations of dozens (even hundreds) of single/double sorts, as well as machine‐learning prediction‐based portfolios, our cross‐sections are low‐dimensional yet have up to three times higher out‐of‐sample Sharpe ratios and alphas.

Predatory Trading

Published: 8/2005,  Volume: 60,  Issue: 4  |  DOI: 10.1111/j.1540-6261.2005.00781.x  |  Cited by: 589

MARKUS K. BRUNNERMEIER, LASSE HEJE PEDERSEN

This paper studies predatory trading, trading that induces and/or exploits the need of other investors to reduce their positions. We show that if one trader needs to sell, others also sell and subsequently buy back the asset. This leads to price overshooting and a reduced liquidation value for the distressed trader. Hence, the market is illiquid when liquidity is most needed. Further, a trader profits from triggering another trader's crisis, and the crisis can spill over across traders and across markets.

Nonstandard Errors

Published: 4/17/2024,  Volume: 79,  Issue: 3  |  DOI: 10.1111/jofi.13337  |  Cited by: 83

ALBERT J. MENKVELD, ANNA DREBER, FELIX HOLZMEISTER, JUERGEN HUBER, MAGNUS JOHANNESSON, MICHAEL KIRCHLER, SEBASTIAN NEUSÜß, MICHAEL RAZEN, UTZ WEITZEL, DAVID ABAD‐DÍAZ, MENACHEM (MENI) ABUDY, TOBIAS ADRIAN, YACINE AIT‐SAHALIA, OLIVIER AKMANSOY, JAMIE T. ALCOCK, VITALI ALEXEEV, ARASH ALOOSH, LIVIA AMATO, DIEGO AMAYA, JAMES J. ANGEL, ALEJANDRO T. AVETIKIAN, AMADEUS BACH, EDWIN BAIDOO, GAETAN BAKALLI, LI BAO, ANDREA BARBON, OKSANA BASHCHENKO, PARAMPREET C. BINDRA, GEIR H. BJØNNES, JEFFREY R. BLACK, BERNARD S. BLACK, DIMITAR BOGOEV, SANTIAGO BOHORQUEZ CORREA, OLEG BONDARENKO, CHARLES S. BOS, CIRIL BOSCH‐ROSA, ELIE BOURI, CHRISTIAN BROWNLEES, ANNA CALAMIA, VIET NGA CAO, GUNTHER CAPELLE‐BLANCARD, LAURA M. CAPERA ROMERO, MASSIMILIANO CAPORIN, ALLEN CARRION, TOLGA CASKURLU, BIDISHA CHAKRABARTY, JIAN CHEN, MIKHAIL CHERNOV, WILLIAM CHEUNG, LUDWIG B. CHINCARINI, TARUN CHORDIA, SHEUNG‐CHI CHOW, BENJAMIN CLAPHAM, JEAN‐EDOUARD COLLIARD, CAROLE COMERTON‐FORDE, EDWARD CURRAN, THONG DAO, WALE DARE, RYAN J. DAVIES, RICCARDO DE BLASIS, GIANLUCA F. DE NARD, FANY DECLERCK, OLEG DEEV, HANS DEGRYSE, SOLOMON Y. DEKU, CHRISTOPHE DESAGRE, MATHIJS A. VAN DIJK, CHUKWUMA DIM, THOMAS DIMPFL, YUN JIANG DONG, PHILIP A. DRUMMOND, TOM DUDDA, TEODOR DUEVSKI, ARIADNA DUMITRESCU, TEODOR DYAKOV, ANNE HAUBO DYHRBERG, MICHAŁ DZIELIŃSKI, ASLI EKSI, IZIDIN EL KALAK, SASKIA TER ELLEN, NICOLAS EUGSTER, MARTIN D. D. EVANS, MICHAEL FARRELL, ESTER FELEZ‐VINAS, GERARDO FERRARA, EL MEHDI FERROUHI, ANDREA FLORI, JONATHAN T. FLUHARTY‐JAIDEE, SEAN D. V. FOLEY, KINGSLEY Y. L. FONG, THIERRY FOUCAULT, TATIANA FRANUS, FRANCESCO FRANZONI, BART FRIJNS, MICHAEL FRÖMMEL, SERVANNA M. FU, SASCHA C. FÜLLBRUNN, BAOQING GAN, GE GAO, THOMAS P. GEHRIG, ROLAND GEMAYEL, DIRK GERRITSEN, JAVIER GIL‐BAZO, DUDLEY GILDER, LAWRENCE R. GLOSTEN, THOMAS GOMEZ, ARSENY GORBENKO, JOACHIM GRAMMIG, VINCENT GRÉGOIRE, UFUK GÜÇBILMEZ, BJÖRN HAGSTRÖMER, JULIEN HAMBUCKERS, ERIK HAPNES, JEFFREY H. HARRIS, LAWRENCE HARRIS, SIMON HARTMANN, JEAN‐BAPTISTE HASSE, NIKOLAUS HAUTSCH, XUE‐ZHONG (TONY) HE, DAVIDSON HEATH, SIMON HEDIGER, TERRENCE HENDERSHOTT, ANN MARIE HIBBERT, ERIK HJALMARSSON, SETH A. HOELSCHER, PETER HOFFMANN, CRAIG W. HOLDEN, ALEX R. HORENSTEIN, WENQIAN HUANG, DA HUANG, CHRISTOPHE HURLIN, KONRAD ILCZUK, ALEXEY IVASHCHENKO, SUBRAMANIAN R. IYER, HOSSEIN JAHANSHAHLOO, NAJI JALKH, CHARLES M. JONES, SIMON JURKATIS, PETRI JYLHÄ, ANDREAS T. KAECK, GABRIEL KAISER, ARZÉ KARAM, EGLE KARMAZIENE, BERNHARD KASSNER, MARKKU KAUSTIA, EKATERINA KAZAK, FEARGHAL KEARNEY, VINCENT VAN KERVEL, SAAD A. KHAN, MARTA K. KHOMYN, TONY KLEIN, OLGA KLEIN, ALEXANDER KLOS, MICHAEL KOETTER, ALEKSEY KOLOKOLOV, ROBERT A. KORAJCZYK, ROMAN KOZHAN, JAN P. KRAHNEN, PAUL KUHLE, AMY KWAN, QUENTIN LAJAUNIE, F. Y. ERIC C. LAM, MARIE LAMBERT, HUGUES LANGLOIS, JENS LAUSEN, TOBIAS LAUTER, MARKUS LEIPPOLD, VLADIMIR LEVIN, YIJIE LI, HUI LI, CHEE YOONG LIEW, THOMAS LINDNER, OLIVER LINTON, JIACHENG LIU, ANQI LIU, GUILLERMO LLORENTE, MATTHIJS LOF, ARIEL LOHR, FRANCIS LONGSTAFF, ALEJANDRO LOPEZ‐LIRA, SHAWN MANKAD, NICOLA MANO, ALEXIS MARCHAL, CHARLES MARTINEAU, FRANCESCO MAZZOLA, DEBRAH MELOSO, MICHAEL G. MI, ROXANA MIHET, VIJAY MOHAN, SOPHIE MOINAS, DAVID MOORE, LIANGYI MU, DMITRIY MURAVYEV, DERMOT MURPHY, GABOR NESZVEDA, CHRISTIAN NEUMEIER, ULF NIELSSON, MAHENDRARAJAH NIMALENDRAN, SVEN NOLTE, LARS L. NORDEN, PETER O'NEILL, KHALED OBAID, BERNT A. ØDEGAARD, PER ÖSTBERG, EMILIANO PAGNOTTA, MARCUS PAINTER, STEFAN PALAN, IMON J. PALIT, ANDREAS PARK, ROBERTO PASCUAL, PAOLO PASQUARIELLO, LUBOS PASTOR, VINAY PATEL, ANDREW J. PATTON, NEIL D. PEARSON, LORIANA PELIZZON, MICHELE PELLI, MATTHIAS PELSTER, CHRISTOPHE PÉRIGNON, CAMERON PFIFFER, RICHARD PHILIP, TOMÁŠ PLÍHAL, PUNEET PRAKASH, OLIVER‐ALEXANDER PRESS, TINA PRODROMOU, MARCEL PROKOPCZUK, TALIS PUTNINS, YA QIAN, GAURAV RAIZADA, DAVID RAKOWSKI, ANGELO RANALDO, LUCA REGIS, STEFAN REITZ, THOMAS RENAULT, REX W. RENJIE, ROBERTO RENO, STEVEN J. RIDDIOUGH, KALLE RINNE, PAUL RINTAMÄKI, RYAN RIORDAN, THOMAS RITTMANNSBERGER, IÑAKI RODRÍGUEZ LONGARELA, DOMINIK ROESCH, LAVINIA ROGNONE, BRIAN ROSEMAN, IOANID ROŞU, SAURABH ROY, NICOLAS RUDOLF, STEPHEN R. RUSH, KHALADDIN RZAYEV, ALEKSANDRA A. RZEŹNIK, ANTHONY SANFORD, HARIKUMAR SANKARAN, ASANI SARKAR, LUCIO SARNO, OLIVIER SCAILLET, STEFAN SCHARNOWSKI, KLAUS R. SCHENK‐HOPPÉ, ANDREA SCHERTLER, MICHAEL SCHNEIDER, FLORIAN SCHROEDER, NORMAN SCHÜRHOFF, PHILIPP SCHUSTER, MARCO A. SCHWARZ, MARK S. SEASHOLES, NORMAN J. SEEGER, OR SHACHAR, ANDRIY SHKILKO, JESSICA SHUI, MARIO SIKIC, GIORGIA SIMION, LEE A. SMALES, PAUL SÖDERLIND, ELVIRA SOJLI, KONSTANTIN SOKOLOV, JANTJE SÖNKSEN, LAIMA SPOKEVICIUTE, DENITSA STEFANOVA, MARTI G. SUBRAHMANYAM, BARNABAS SZASZI, OLEKSANDR TALAVERA, YUEHUA TANG, NICK TAYLOR, WING WAH THAM, ERIK THEISSEN, JULIAN THIMME, IAN TONKS, HAI TRAN, LUCA TRAPIN, ANDERS B. TROLLE, M. ANDREEA VADUVA, GIORGIO VALENTE, ROBERT A. VAN NESS, AURELIO VASQUEZ, THANOS VEROUSIS, PATRICK VERWIJMEREN, ANDERS VILHELMSSON, GRIGORY VILKOV, VLADIMIR VLADIMIROV, SEBASTIAN VOGEL, STEFAN VOIGT, WOLF WAGNER, THOMAS WALTHER, PATRICK WEISS, MICHEL VAN DER WEL, INGRID M. WERNER, P. JOAKIM WESTERHOLM, CHRISTIAN WESTHEIDE, HANS C. WIKA, EVERT WIPPLINGER, MICHAEL WOLF, CHRISTIAN C. P. WOLFF, LEONARD WOLK, WING‐KEUNG WONG, JAN WRAMPELMEYER, ZHEN‐XING WU, SHUO XIA, DACHENG XIU, KE XU, CAIHONG XU, PRADEEP K. YADAV, JOSÉ YAGÜE, CHENG YAN, ANTTI YANG, WOONGSUN YOO, WENJIA YU, YIHE YU, SHIHAO YU, BART Z. YUESHEN, DARYA YUFEROVA, MARCIN ZAMOJSKI, ABALFAZL ZAREEI, STEFAN M. ZEISBERGER, LU ZHANG, S. SARAH ZHANG, XIAOYU ZHANG, LU ZHAO, ZHUO ZHONG, Z. IVY ZHOU, CHEN ZHOU, XINGYU S. ZHU, MARIUS ZOICAN, REMCO ZWINKELS

In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.