The Journal of Finance

Investment, Idiosyncratic Risk, and Ownership

Published: 05/21/2012   |   DOI: 10.1111/j.1540-6261.2012.01743.x

VASIA PANOUSI, DIMITRIS PAPANIKOLAOU

High‐powered incentives may induce higher managerial effort, but they also expose managers to idiosyncratic risk. If managers are risk averse, they might underinvest when firm‐specific uncertainty increases, leading to suboptimal investment decisions from the perspective of well‐diversified shareholders. We empirically document that, when idiosyncratic risk rises, firm investment falls, and more so when managers own a larger fraction of the firm. This negative effect of managerial risk aversion on investment is mitigated if executives are compensated with options rather than with shares or if institutional investors form a large part of the shareholder base.

Growth Opportunities, Technology Shocks, and Asset Prices

Published: 11/29/2013   |   DOI: 10.1111/jofi.12136

LEONID KOGAN, DIMITRIS PAPANIKOLAOU

We explore the impact of investment‐specific technology (IST) shocks on the cross section of stock returns. Using a structural model, we show that IST shocks have a differential effect on the value of assets in place and the value of growth opportunities. This differential sensitivity to IST shocks has two main implications. First, firm risk premia depend on the contribution of growth opportunities to firm value. Second, firms with similar levels of growth opportunities comove with each other, giving rise to the value factor in stock returns and the failure of the conditional CAPM. Our empirical tests confirm the model's predictions.

Organization Capital and the Cross‐Section of Expected Returns

Published: 02/15/2013   |   DOI: 10.1111/jofi.12034

ANDREA L. EISFELDT, DIMITRIS PAPANIKOLAOU

Organization capital is a production factor that is embodied in the firm's key talent and has an efficiency that is firm specific. Hence, both shareholders and key talent have a claim to its cash flows. We develop a model in which the outside option of the key talent determines the share of firm cash flows that accrue to shareholders. This outside option varies systematically and renders firms with high organization capital riskier from shareholders' perspective. We find that firms with more organization capital have average returns that are 4.6% higher than firms with less organization capital.

When It Pays to Pay Your Investment Banker: New Evidence on the Role of Financial Advisors in M&As

Published: 01/17/2012   |   DOI: 10.1111/j.1540-6261.2011.01712.x

ANDREY GOLUBOV, DIMITRIS PETMEZAS, NICKOLAOS G. TRAVLOS

We provide new evidence on the role of financial advisors in M&As. Contrary to prior studies, top‐tier advisors deliver higher bidder returns than their non‐top‐tier counterparts but in public acquisitions only, where the advisor reputational exposure and required skills set are relatively larger. This translates into a $65.83 million shareholder gain for an average bidder. The improvement comes from top‐tier advisors' ability to identify more synergistic combinations and to get a larger share of synergies to accrue to bidders. Consistent with the premium price–premium quality equilibrium, top‐tier advisors charge premium fees in these transactions.

Strategic Trading in a Dynamic Noisy Market

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00321

Dimitri Vayanos

This paper studies a dynamic model of a financial market with a strategic trader. In each period the strategic trader receives a privately observed endowment in the stock. He trades with competitive market makers to share risk. Noise traders are present in the market. After receiving a stock endowment, the strategic trader is shown to reduce his risk exposure either by selling at a decreasing rate over time or by selling and then buying back some of the shares sold. When the time between trades is small, the strategic trader reveals the information regarding his endowment very quickly.

The Dynamics of Financially Constrained Arbitrage

Published: 05/09/2018   |   DOI: 10.1111/jofi.12689

DENIS GROMB, DIMITRI VAYANOS

We develop a model in which financially constrained arbitrageurs exploit price discrepancies across segmented markets. We show that the dynamics of arbitrage capital are self‐correcting: following a shock that depletes capital, returns increase, which allows capital to be gradually replenished. Spreads increase more for trades with volatile fundamentals or more time to convergence. Arbitrageurs cut their positions more in those trades, except when volatility concerns the hedgeable component. Financial constraints yield a positive cross‐sectional relationship between spreads/returns and betas with respect to arbitrage capital. Diversification of arbitrageurs across markets induces contagion, but generally lowers arbitrageurs' risk and price volatility.

Liquidity Risk and the Dynamics of Arbitrage Capital

Published: 02/10/2019   |   DOI: 10.1111/jofi.12757

PÉTER KONDOR, DIMITRI VAYANOS

We develop a continuous‐time model of liquidity provision in which hedgers can trade multiple risky assets with arbitrageurs. Arbitrageurs have constant relative risk‐aversion (CRRA) utility, while hedgers' asset demand is independent of wealth. An increase in hedgers' risk aversion can make arbitrageurs endogenously more risk‐averse. Because arbitrageurs generate endogenous risk, an increase in their wealth or a reduction in their CRRA coefficient can raise risk premia despite Sharpe ratios declining. Arbitrageur wealth is a priced risk factor because assets held by arbitrageurs offer high expected returns but suffer the most when wealth drops. Aggregate illiquidity, which declines in wealth, captures that factor.

Order Flow and Expected Option Returns

Published: 12/21/2015   |   DOI: 10.1111/jofi.12380

DMITRIY MURAVYEV

I show that the inventory risk faced by market‐makers has a first‐order effect on option prices. I introduce a simple approach that decomposes the price impact of trades into inventory risk and asymmetric information components. While both components are large for option trades, the inventory risk component is larger. Using the full panel of daily option returns, I find that option order imbalances attributable to inventory risk have five times larger impact on option prices than previously thought. Finally, I find that past order imbalances have greater predictive power than any other commonly used predictor of option returns.

Financial Markets Where Traders Neglect the Informational Content of Prices

Published: 10/08/2018   |   DOI: 10.1111/jofi.12729

ERIK EYSTER, MATTHEW RABIN, DIMITRI VAYANOS

We model a financial market where some traders of a risky asset do not fully appreciate what prices convey about others' private information. Markets comprising solely such “cursed” traders generate more trade than those comprising solely rationals. Because rationals arbitrage away distortions caused by cursed traders, mixed markets can generate even more trade. Per‐trader volume in cursed markets increases with market size; volume may instead disappear when traders infer others' information from prices, even when they dismiss it as noisier than their own. Making private information public raises rational and “dismissive” volume, but reduces cursed volume given moderate noninformational trading motives.

A Search‐Based Theory of the On‐the‐Run Phenomenon

Published: 05/09/2008   |   DOI: 10.1111/j.1540-6261.2008.01360.x

DIMITRI VAYANOS, PIERRE‐OLIVIER WEILL

We propose a model in which assets with identical cash flows can trade at different prices. Infinitely lived agents can establish long positions in a search spot market, or short positions by first borrowing an asset in a search repo market. We show that short‐sellers can endogenously concentrate in one asset because of search externalities and the constraint that they must deliver the asset they borrowed. That asset enjoys greater liquidity, a higher lending fee (“specialness”), and trades at a premium consistent with no‐arbitrage. We derive closed‐form solutions for small frictions, and provide a calibration generating realistic on‐the‐run premia.

Informed Trading Intensity

Published: 02/27/2024   |   DOI: 10.1111/jofi.13320

VINCENT BOGOUSSLAVSKY, VYACHESLAV FOS, DMITRIY MURAVYEV

We train a machine learning method on a class of informed trades to develop a new measure of informed trading, informed trading intensity (ITI). ITI increases before earnings, mergers and acquisitions, and news announcements, and has implications for return reversal and asset pricing. ITI is effective because it captures nonlinearities and interactions between informed trading, volume, and volatility. This data‐driven approach can shed light on the economics of informed trading, including impatient informed trading, commonality in informed trading, and models of informed trading. Overall, learning from informed trading data can generate an effective informed trading measure.

A Rose.com by Any Other Name

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00408

Michael J. Cooper, Orlin Dimitrov, P. Raghavendra Rau

We document a striking positive stock price reaction to the announcement of corporate name changes to Internet‐related dotcom names. This “dotcom” effect produces cumulative abnormal returns on the order of 74 percent for the 10 days surrounding the announcement day. The effect does not appear to be transitory; there is no evidence of a postannouncement negative drift. The announcement day effect is also similar across all firms, regardless of the firm's level of involvement with the Internet. A mere association with the Internet seems enough to provide a firm with a large and permanent value increase.

Is There a Risk Premium in the Stock Lending Market? Evidence from Equity Options

Published: 04/03/2022   |   DOI: 10.1111/jofi.13129

DMITRIY MURAVYEV, NEIL D. PEARSON, JOSHUA M. POLLET

Recent research argues that uncertainty about future stock borrowing fees hinders short‐selling, and this risk explains the performance of short strategies. One possible mechanism is that borrowing fee risk carries a risk premium. Since the present value of the uncertain borrowing fee is reflected in options prices, the difference between option‐implied and realized fees estimates this premium. We find that the risk premium is small. Moreover, if the risk premium is substantial, it should be reflected in the returns to short‐selling stock after adjusting for stock borrowing fees. However, borrowing fee risk does not predict fee‐adjusted returns.

Nonstandard Errors

Published: 04/17/2024   |   DOI: 10.1111/jofi.13337

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.