The Journal of Finance

Term Structure of Interest Rates with Regime Shifts

Published: 10/2002,  Volume: 57,  Issue: 5  |  DOI: 10.1111/0022-1082.00487  |  Cited by: 342

Ravi Bansal, Hao Zhou

We develop a term structure model where the short interest rate and the market price of risks are subject to discrete regime shifts. Empirical evidence from efficient method of moments estimation provides considerable support for the regime shifts model. Standard models, which include affine specifications with up to three factors, are sharply rejected in the data. Our diagnostics show that only the regime shifts model can account for the well‐documented violations of the expectations hypothesis, the observed conditional volatility, and the conditional correlation across yields. We find that regimes are intimately related to business cycles.

The Drivers and Implications of Retail Margin Trading

Published: 5/15/2026,  Volume: 81,  Issue: 4  |  DOI: 10.1111/jofi.70049  |  Cited by: 1

JIANGZE BIAN, ZHI DA, ZHIGUO HE, DONG LOU, KELLY SHUE, HAO ZHOU

Using granular data covering both regulated (brokerage‐financed) and unregulated (shadow‐financed) margin accounts in China, we provide novel evidence on retail investors' margin trading behavior and its price implications. We first show that retail investors' decisions to lever up in stock trading despite the hefty borrowing cost is related to their lottery preferences. We then show that margin borrowing affects investors' trading behavior—investors are more likely to liquidate their holdings as they approach margin calls. Finally, we show that margin‐induced trading aggregates to affect asset prices and contributes to shock spillovers across stocks (e.g., from lottery stocks to nonlottery stocks).

On the Foundations of Corporate Social Responsibility

Published: 3/21/2017,  Volume: 72,  Issue: 2  |  DOI: 10.1111/jofi.12487  |  Cited by: 1334

HAO LIANG, LUC RENNEBOOG

Using corporate social responsibility (CSR) ratings for 23,000 companies from 114 countries, we find that a firm's CSR rating and its country's legal origin are strongly correlated. Legal origin is a stronger explanation than “doing good by doing well” factors or firm and country characteristics (ownership concentration, political institutions, and globalization): firms from common law countries have lower CSR than companies from civil law countries, with Scandinavian civil law firms having the highest CSR ratings. Evidence from quasi‐natural experiments such as scandals and natural disasters suggests that civil law firms are more responsive to CSR shocks than common law firms.

Does Herding Behavior Reveal Skill? An Analysis of Mutual Fund Performance

Published: 7/16/2018,  Volume: 73,  Issue: 5  |  DOI: 10.1111/jofi.12699  |  Cited by: 181

HAO JIANG, MICHELA VERARDO

We uncover a negative relation between herding behavior and skill in the mutual fund industry. Our new, dynamic measure of fund‐level herding captures the tendency of fund managers to follow the trades of the institutional crowd. We find that herding funds underperform their antiherding peers by over 2% per year. Differences in skill drive this performance gap: Antiherding funds make superior investment decisions even on stocks not heavily traded by institutions, and can anticipate the trades of the crowd; furthermore, the herding‐antiherding performance gap is persistent, wider when skill is more valuable, and larger among managers with stronger career concerns.

An Equilibrium Analysis of Hedging with Liquidity Constraints, Speculation, and Government Price Subsidy in a Commodity Market

Published: 10/1998,  Volume: 53,  Issue: 5  |  DOI: 10.1111/0022-1082.00069  |  Cited by: 21

Zhongquan Zhou

We develop a simple commodity model to analyze (i) the effects of hedging with liquidity constraints, due to producers' inability to bear unlimited trading losses, (ii) the role of speculation in the process of risk allocation between consumers and producers, and (iii) the equilibrium implications of government price subsidies to the producers. We find that (1) liquidity constraints can cause futures prices to exhibit mean reversion, which then makes speculation profitable; (2) speculation tends to make futures price volatility an increasing function of futures price; and (3) government price subsidy, if actively hedged by the producers, serves to lower the futures risk premium and reduce futures volatility.

Asset‐pricing Tests under Alternative Distributions

Published: 12/1993,  Volume: 48,  Issue: 5  |  DOI: 10.1111/j.1540-6261.1993.tb05134.x  |  Cited by: 84

GUOFU ZHOU

Given the normality assumption, we reject the mean‐variance efficiency of the Center for Research in Security Prices value‐weighted stock index for three of the six consecutive ten‐year subperiods from 1926 to 1986. However, the normality assumption is strongly rejected by the data. Under plausible alternative distributional assumptions of the elliptical class, the efficiency can no longer be rejected. When the normality assumption is violated but the ellipticity assumption is maintained, many tests tend to be biased toward overrejection and both the accuracy of estimated beta and are usually overstated.

Market Making Contracts, Firm Value, and the IPO Decision

Published: 9/3/2015,  Volume: 70,  Issue: 5  |  DOI: 10.1111/jofi.12285  |  Cited by: 63

HENDRIK BESSEMBINDER, JIA HAO, KUNCHENG ZHENG

We examine the effects of secondary market liquidity on firm value and the IPO decision. Competitive aftermarket liquidity provision is associated with reduced welfare and a discounted secondary market price that can dissuade IPOs. The competitive market fails in particular for firms or at times when uncertainty regarding fundamental value and asymmetric information are large in combination. In these cases, firm value and welfare are improved by a contract where the firm engages a designated market maker to enhance liquidity. Such contracts represent a market solution to a market imperfection, particularly for small, growth firms.

A Critique of the Stochastic Discount Factor Methodology

Published: 8/1999,  Volume: 54,  Issue: 4  |  DOI: 10.1111/0022-1082.00145  |  Cited by: 62

Raymond Kan, Guofu Zhou

In this paper, we point out that the widely used stochastic discount factor (SDF) methodology ignores a fully specified model for asset returns. As a result, it suffers from two potential problems when asset returns follow a linear factor model. The first problem is that the risk premium estimate from the SDF methodology is unreliable. The second problem is that the specification test under the SDF methodology has very low power in detecting misspecified models. Traditional methodologies typically incorporate a fully specified model for asset returns, and they can perform substantially better than the SDF methodology.

Model Ambiguity versus Model Misspecification in Dynamic Portfolio Choice

Published: 1/21/2026,  Volume: 81,  Issue: 3  |  DOI: 10.1111/jofi.70027  |  Cited by: 0

PASCAL J. MAENHOUT, HAO XING, ANNE G. BALTER

We study aversion to model ambiguity and misspecification in dynamic portfolio choice. Risk‐averse investors (relative risk aversion ) fear return persistence, while risk‐tolerant investors () fear mean reversion, when confronting model misspecification concerns of identically and independently distributed (IID) returns. The intuition is that risk‐averse investors, who want to hedge intertemporally, endogenously fear return persistence, which precludes hedging. A log investor is myopic and unaffected by model misspecification, therefore only worrying about model ambiguity. Our model can generate belief scarring, nonparticipation in equity markets, and extrapolative return expectations. Extending beyond IID returns, we study model misspecification for a mean‐reverting Sharpe ratio.

The Dark Side of Circuit Breakers

Published: 2/23/2024,  Volume: 79,  Issue: 2  |  DOI: 10.1111/jofi.13310  |  Cited by: 23

HUI CHEN, ANTON PETUKHOV, JIANG WANG, HAO XING

Market‐wide circuit breakers are trading halts aimed at stabilizing the market during dramatic price declines. Using an intertemporal equilibrium model, we show that a circuit breaker significantly alters market dynamics and affects investor welfare. As the market approaches the circuit breaker, price volatility rises drastically, accelerating the chance of triggering the circuit breaker—the so‐called “magnet effect,” returns exhibit increasing negative skewness, and trading activity spikes up. Our empirical analysis supports the model's predictions. Circuit breakers can affect overall welfare negatively or positively, depending on the relative significance of investors' trading motives for risk sharing versus irrational speculation.

Equilibrium Analysis of Portfolio Insurance

Published: 9/1996,  Volume: 51,  Issue: 4  |  DOI: 10.1111/j.1540-6261.1996.tb04073.x  |  Cited by: 171

SANFORD J. GROSSMAN, ZHONGQUAN ZHOU

A martingale approach is used to characterize general equilibrium in the presence of portfolio insurance. Insurers sell to noninsurers in bad states, and general equilibrium requires that the risk premium rises to induce noninsurers to increase their holdings. We show that portfolio insurance increases price volatility, causes mean reversion in asset returns, raises the Sharpe ratio and volatility in bad states, and causes volatility to be correlated with volume. We also explain why out‐of‐the‐money S&P 500 put options trade at a higher volatility than do in‐the‐money puts.

The Virtue of Complexity in Return Prediction

Published: 12/21/2023,  Volume: 79,  Issue: 1  |  DOI: 10.1111/jofi.13298  |  Cited by: 205

BRYAN KELLY, SEMYON MALAMUD, KANGYING ZHOU

Much of the extant literature predicts market returns with “simple” models that use only a few parameters. Contrary to conventional wisdom, we theoretically prove that simple models severely understate return predictability compared to “complex” models in which the number of parameters exceeds the number of observations. We empirically document the virtue of complexity in U.S. equity market return prediction. Our findings establish the rationale for modeling expected returns through machine learning.

International Stock Return Predictability: What Is the Role of the United States?

Published: 7/16/2013,  Volume: 68,  Issue: 4  |  DOI: 10.1111/jofi.12041  |  Cited by: 666

DAVID E. RAPACH, JACK K. STRAUSS, GUOFU ZHOU

We investigate lead‐lag relationships among monthly country stock returns and identify a leading role for the United States: lagged U.S. returns significantly predict returns in numerous non‐U.S. industrialized countries, while lagged non‐U.S. returns display limited predictive ability with respect to U.S. returns. We estimate a news‐diffusion model, and the results indicate that return shocks arising in the United States are only fully reflected in equity prices outside of the United States with a lag, consistent with a gradual information diffusion explanation of the predictive power of lagged U.S. returns.

Momentum, Reversal, and Uninformed Traders in Laboratory Markets

Published: 11/25/2009,  Volume: 64,  Issue: 6  |  DOI: 10.1111/j.1540-6261.2009.01510.x  |  Cited by: 53

ROBERT J. BLOOMFIELD, WILLIAM B. TAYLER, FLORA (HAILAN) ZHOU

We report the results of three experiments based on the model of Hong and Stein (1999). Consistent with the model, the results show that when informed traders do not observe prices, uninformed traders generate long‐term price reversals by engaging in momentum trade. However, when informed traders also observe prices, uninformed traders generate reversals by engaging in contrarian trading. The results suggest that a dominated information set is sufficient to account for the contrarian behavior observed among individual investors, and that uninformed traders may be responsible for long‐term price reversals but play little role in driving short‐term momentum.

Anomalies and the Expected Market Return

Published: 12/21/2021,  Volume: 77,  Issue: 1  |  DOI: 10.1111/jofi.13099  |  Cited by: 205

XI DONG, YAN LI, DAVID E. RAPACH, GUOFU ZHOU

We provide the first systematic evidence on the link between long‐short anomaly portfolio returns—a cornerstone of the cross‐sectional literature—and the time‐series predictability of the aggregate market excess return. Using 100 representative anomalies from the literature, we employ a variety of shrinkage techniques (including machine learning, forecast combination, and dimension reduction) to efficiently extract predictive signals in a high‐dimensional setting. We find that long‐short anomaly portfolio returns evince statistically and economically significant out‐of‐sample predictive ability for the market excess return. The predictive ability of anomaly portfolio returns appears to stem from asymmetric limits of arbitrage and overpricing correction persistence.

Nonstandard Errors

Published: 4/17/2024,  Volume: 79,  Issue: 3  |  DOI: 10.1111/jofi.13337  |  Cited by: 106

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.