The Journal of Finance

The Business Cycle, Investor Sentiment, and Costly External Finance

Published: 5/8/2014,  Volume: 69,  Issue: 3  |  DOI: 10.1111/jofi.12047  |  Cited by: 324

R. DAVID MCLEAN, MENGXIN ZHAO

The recent financial crisis shows that financial markets can impact the real economy. We investigate whether access to finance typically time‐varies and, if so, what are the real effects. Consistent with time‐varying external finance costs, both investment and employment are less sensitive to Tobin's q and more sensitive to cash flow during recessions and low investor sentiment periods. Share issuance plays a bigger role than debt issuance in causing these effects. Alternative tests that do not rely on q and cash flow sensitivities suggest that recessions and low sentiment increase external finance costs, thereby limiting investment and employment.

CEO Turnover after Acquisitions: Are Bad Bidders Fired?

Published: 8/2006,  Volume: 61,  Issue: 4  |  DOI: 10.1111/j.1540-6261.2006.00889.x  |  Cited by: 309

KENNETH M. LEHN, MENGXIN ZHAO

We examine the relation between bidder returns and the probability of chief executive officer (CEO) turnover in acquiring firms. Using a sample of 714 acquisitions during 1990 to 1998, we find that 47% of CEOs of acquiring firms are replaced within 5 years, including 27% by internal governance, 16% by takeovers, and 4% by bankruptcy. A significant inverse relation exists between bidder returns and the likelihood of CEO turnover. This relation is not associated with governance structure. It also is not significantly different in stock versus cash acquisitions, which appears to be inconsistent with Shleifer and Vishny's theory of “stock market driven” acquisitions.

Why Does the Law Matter? Investor Protection and Its Effects on Investment, Finance, and Growth

Published: 1/17/2012,  Volume: 67,  Issue: 1  |  DOI: 10.1111/j.1540-6261.2011.01713.x  |  Cited by: 430

R. DAVID MCLEAN, TIANYU ZHANG, MENGXIN ZHAO

Investor protection is associated with greater investment sensitivity to q and lower investment sensitivity to cash flow. Finance plays a role in causing these effects; in countries with strong investor protection, external finance increases more strongly with q, and declines more strongly with cash flow. We further find that q and cash flow sensitivities are associated with ex post investment efficiency; investment predicts growth and profits more strongly in countries with greater q sensitivities and lower cash flow sensitivities. The paper's findings are broadly consistent with investor protection promoting accurate share prices, reducing financial constraints, and encouraging efficient investment.

Neglected Risks in the Communication of Residential Mortgage‐Backed Securities Offerings

Published: 9/23/2023,  Volume: 79,  Issue: 1  |  DOI: 10.1111/jofi.13278  |  Cited by: 11

HAROLD H. ZHANG, FENG ZHAO, XIAOFEI ZHAO

Examining the contractual disclosures during the sale of private‐label residential mortgage‐backed securities before the 2008 financial crisis, we find that textual contents in the risk‐factor section predict subsequent losses and yet were not reflected in pricing. Insurance companies, especially life insurers and insurers with low regulatory capital ratios, are more exposed to textual risks. Consistent with issuers hedging litigation risks with disclosure, we find that textual contents are associated with second‐lien underreporting and preissuance written communications. Overall, we find that investors neglected risks in the purportedly safe assets before the crisis.

Artificial Intelligence, Education, and Entrepreneurship

Published: 12/23/2023,  Volume: 79,  Issue: 1  |  DOI: 10.1111/jofi.13302  |  Cited by: 109

MICHAEL GOFMAN, ZHAO JIN

We document an unprecedented brain drain of Artificial Intelligence (AI) professors from universities from 2004 to 2018. We find that students from the affected universities establish fewer AI startups and raise less funding. The brain‐drain effect is significant for tenured professors, professors from top universities, and deep‐learning professors. Additional evidence suggests that unobserved city‐ and university‐level shocks are unlikely to drive our results. We consider several economic channels for the findings. The most consistent explanation is that professors' departures reduce startup founders' AI knowledge, which we find is an important factor for successful startup formation and fundraising.

Unspanned Stochastic Volatility: Evidence from Hedging Interest Rate Derivatives

Published: 1/20/2006,  Volume: 61,  Issue: 1  |  DOI: 10.1111/j.1540-6261.2006.00838.x  |  Cited by: 133

HAITAO LI, FENG ZHAO

Most existing dynamic term structure models assume that interest rate derivatives are redundant securities and can be perfectly hedged using solely bonds. We find that the quadratic term structure models have serious difficulties in hedging caps and cap straddles, even though they capture bond yields well. Furthermore, at‐the‐money straddle hedging errors are highly correlated with cap‐implied volatilities and can explain a large fraction of hedging errors of all caps and straddles across moneyness and maturities. Our results strongly suggest the existence of systematic unspanned factors related to stochastic volatility in interest rate derivatives markets.

The Misallocation of Finance

Published: 5/8/2021,  Volume: 76,  Issue: 5  |  DOI: 10.1111/jofi.13031  |  Cited by: 101

TONI M. WHITED, JAKE ZHAO

We estimate real losses arising from the cross‐sectional misallocation of financial liabilities. Extending a production‐based framework of misallocation measurement to the liabilities side of the balance sheet and using manufacturing firm data from the United States and China, we find significant misallocation of debt and equity in China but not the United States. Reallocating liabilities of firms in China to mimic U.S. efficiency would produce gains of 51% to 69% in real value‐added, with only 17% to 21% stemming from inefficient debt‐equity combinations. For Chinese firms that are large or in developed cities, we estimate lower distortionary financing costs.

On Comparing Asset Pricing Models

Published: 11/21/2019,  Volume: 75,  Issue: 1  |  DOI: 10.1111/jofi.12854  |  Cited by: 85

SIDDHARTHA CHIB, XIAMING ZENG, LINGXIAO ZHAO

Revisiting the framework of (Barillas, Francisco, and Jay Shanken, 2018, Comparing asset pricing models, The Journal of Finance 73, 715–754). BS henceforth, we show that the Bayesian marginal likelihood‐based model comparison method in that paper is unsound : the priors on the nuisance parameters across models must satisfy a change of variable property for densities that is violated by the Jeffreys priors used in the BS method. Extensive simulation exercises confirm that the BS method performs unsatisfactorily. We derive a new class of improper priors on the nuisance parameters, starting from a single improper prior, which leads to valid marginal likelihoods and model comparisons. The performance of our marginal likelihoods is significantly better, allowing for reliable Bayesian work on which factors are risk factors in asset pricing models.

Interest Rate Caps “Smile” Too! But Can the LIBOR Market Models Capture the Smile?

Published: 1/11/2007,  Volume: 62,  Issue: 1  |  DOI: 10.1111/j.1540-6261.2007.01209.x  |  Cited by: 97

ROBERT JARROW, HAITAO LI, FENG ZHAO

Using 3 years of interest rate caps price data, we provide a comprehensive documentation of volatility smiles in the caps market. To capture the volatility smiles, we develop a multifactor term structure model with stochastic volatility and jumps that yields a closed‐form formula for cap prices. We show that although a three‐factor stochastic volatility model can price at‐the‐money caps well, significant negative jumps in interest rates are needed to capture the smile. The volatility smile contains information that is not available using only at‐the‐money caps, and this information is important for understanding term structure models.

Cautious Risk Takers: Investor Preferences and Demand for Active Management

Published: 2/19/2019,  Volume: 74,  Issue: 2  |  DOI: 10.1111/jofi.12747  |  Cited by: 22

VALERY POLKOVNICHENKO, KELSEY D. WEI, FENG ZHAO

Despite their mediocre mean performance, actively managed mutual funds are distinct from passive funds in their return distributions. Active value funds better hedge downside risk, while active growth funds better capture upside potential. Since such performance features may appeal to investors with tail‐overweighting preferences, we show that preferences for downside protection and upside potential estimated from the empirical pricing kernel can help explain active fund flows in the value and growth categories, respectively. This effect of investor risk preferences varies significantly with funds' downside‐hedging and upside‐capturing ability, with levels of active management, and across retirement and retail funds.

Family‐Controlled Firms and Informed Trading: Evidence from Short Sales

Published: 1/17/2012,  Volume: 67,  Issue: 1  |  DOI: 10.1111/j.1540-6261.2011.01714.x  |  Cited by: 194

RONALD C. ANDERSON, DAVID M. REEB, WANLI ZHAO

We investigate the relation between organization structure and the information content of short sales, focusing on founder‐ and heir‐controlled firms. Our analysis indicates that family‐controlled firms experience substantially higher abnormal short sales prior to negative earnings shocks than nonfamily firms. Supplementary testing indicates that family control characteristics intensify informed short selling. Further analysis suggests that daily short‐sale interest in family firms contains useful information in forecasting stock returns; however, we find no discernable effect for nonfamily firms. This analysis provides compelling evidence that informed trading via short sales occurs more readily in family firms than in nonfamily firms.

Do Women Receive Worse Financial Advice?

Published: 7/5/2024,  Volume: 79,  Issue: 5  |  DOI: 10.1111/jofi.13366  |  Cited by: 23

UTPAL BHATTACHARYA, AMIT KUMAR, SUJATA VISARIA, JING ZHAO

We arranged for trained undercover men and women to pose as potential clients and visit all 65 local financial advisory firms in Hong Kong. At financial planning firms, but not at securities firms, women were more likely than men to receive advice to buy only individual or only local securities. Female clients who signaled high confidence, high risk tolerance, or a domestic outlook were especially likely to receive this suboptimal advice. Our theoretical model explains these patterns as a result of statistical discrimination interacting with advisors’ incentives. Taste‐based discrimination is unlikely to explain the results.

Subprime Mortgage Defaults and Credit Default Swaps

Published: 3/12/2015,  Volume: 70,  Issue: 2  |  DOI: 10.1111/jofi.12221  |  Cited by: 37

ERIC ARENTSEN, DAVID C. MAUER, BRIAN ROSENLUND, HAROLD H. ZHANG, FENG ZHAO

We offer the first empirical evidence on the adverse effect of credit default swap (CDS) coverage on subprime mortgage defaults. Using a large database of privately securitized mortgages, we find that higher defaults concentrate in mortgage pools with concurrent CDS coverage, and within these pools the loans originated after or shortly before the start of CDS coverage have an even higher delinquency rate. The results are robust across zip code and origination quarter cohorts. Overall, we show that CDS coverage helped drive higher mortgage defaults during the financial crisis.

Nonstandard Errors

Published: 4/17/2024,  Volume: 79,  Issue: 3  |  DOI: 10.1111/jofi.13337  |  Cited by: 107

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.