The Journal of Finance

Paying Too Much? Borrower Sophistication and Overpayment in the U.S. Mortgage Market

Published: 12/9/2025,  Volume: 81,  Issue: 1  |  DOI: 10.1111/jofi.70001  |  Cited by: 8

NEIL BHUTTA, ANDREAS FUSTER, AUREL HIZMO

Comparing mortgage rates that borrowers obtain to rates that lenders could offer for the same loan, we find that many homeowners significantly overpay for their mortgage, with overpayment varying across borrower types and with market interest rates. Survey data reveal that borrowers' mortgage knowledge and shopping behavior strongly correlate with the rates they secure. We also document substantial variation in how expensive and profitable lenders are, without any evidence that expensive loans are associated with a better borrower experience. Despite many lenders operating in the U.S. mortgage market, limited borrower sophistication may provide lenders with market power.

The Time‐Varying Price of Financial Intermediation in the Mortgage Market

Published: 6/4/2024,  Volume: 79,  Issue: 4  |  DOI: 10.1111/jofi.13358  |  Cited by: 21

ANDREAS FUSTER, STEPHANIE H. LO, PAUL S. WILLEN

We introduce a new measure of the price charged by financial intermediaries for connecting mortgage borrowers with capital market investors. Based on administrative lender pricing data, we document that the price of intermediation reacts strongly to variation in demand, reflecting capacity constraints of mortgage originators. This positive comovement of price with quantity reduced the pass‐through of quantitative easing. We also find a notable upward trend in this price between 2008 and 2014, likely due to increased legal and regulatory burden in the mortgage market. The trend led to an implicit cost to borrowers of nearly $100 billion over this period.

Predictably Unequal? The Effects of Machine Learning on Credit Markets

Published: 12/16/2021,  Volume: 77,  Issue: 1  |  DOI: 10.1111/jofi.13090  |  Cited by: 512

ANDREAS FUSTER, PAUL GOLDSMITH‐PINKHAM, TARUN RAMADORAI, ANSGAR WALTHER

Innovations in statistical technology in functions including credit‐screening have raised concerns about distributional impacts across categories such as race. Theoretically, distributional effects of better statistical technology can come from greater flexibility to uncover structural relationships or from triangulation of otherwise excluded characteristics. Using data on U.S. mortgages, we predict default using traditional and machine learning models. We find that Black and Hispanic borrowers are disproportionately less likely to gain from the introduction of machine learning. In a simple equilibrium credit market model, machine learning increases disparity in rates between and within groups, with these changes attributable primarily to greater flexibility.

DISCUSSION

Published: 5/1973,  Volume: 28,  Issue: 2  |  DOI: 10.1111/j.1540-6261.1973.tb01789.x  |  Cited by: 0

Andreas G. Papandreou

Subsidizing Liquidity: The Impact of Make/Take Fees on Market Quality

Published: 3/12/2015,  Volume: 70,  Issue: 2  |  DOI: 10.1111/jofi.12230  |  Cited by: 99

KATYA MALINOVA, ANDREAS PARK

Facing increased competition over the last decade, many stock exchanges changed their trading fees to maker‐taker pricing, an incentive scheme that rewards liquidity suppliers and charges liquidity demanders. Using a change in trading fees on the Toronto Stock Exchange, we study whether and why the breakdown of trading fees between liquidity demanders and suppliers matters. Posted quotes adjust after the change in fee composition, but the transaction costs for liquidity demanders remain unaffected once fees are taken into account. However, as posted bid‐ask spreads decline, traders (particularly retail) use aggressive orders more frequently, and adverse selection costs decrease.

Personal Bankruptcy and Credit Market Competition

Published: 3/19/2010,  Volume: 65,  Issue: 2  |  DOI: 10.1111/j.1540-6261.2009.01547.x  |  Cited by: 194

ASTRID A. DICK, ANDREAS LEHNERT

We document a link between U.S. credit supply and rising personal bankruptcy rates. We exploit the exogenous variation in market contestability brought on by banking deregulation—the relaxation of entry restrictions in the 1980s and 1990s—at the state level. We find deregulation explains at least 10% of the rise in bankruptcy rates. We also find that deregulation leads to increased lending, lower loss rates on loans, and higher lending productivity. Our findings indicate that increased competition prompted banks to adopt sophisticated credit rating technology, allowing for new credit extension to existing and previously excluded households.

Is Proprietary Trading Detrimental to Retail Investors?

Published: 5/24/2018,  Volume: 73,  Issue: 3  |  DOI: 10.1111/jofi.12609  |  Cited by: 50

FALKO FECHT, ANDREAS HACKETHAL, YIGITCAN KARABULUT

We study the conflict of interest that arises when a universal bank conducts proprietary trading alongside its retail banking services. Our data set contains the stock holdings of every German bank and those of their corresponding retail clients. We investigate (i) whether banks sell stocks from their proprietary portfolios to their retail customers, (ii) whether those stocks subsequently underperform, and (iii) whether retail customers of banks engaging in proprietary trading earn lower portfolio returns than their peers. We present affirmative evidence for all three questions and conclude that proprietary trading can, in fact, be detrimental to retail investors.

Asset Market Participation and Portfolio Choice over the Life‐Cycle

Published: 3/21/2017,  Volume: 72,  Issue: 2  |  DOI: 10.1111/jofi.12484  |  Cited by: 279

ANDREAS FAGERENG, CHARLES GOTTLIEB, LUIGI GUISO

Using error‐free data on life‐cycle portfolio allocations of a large sample of Norwegian households, we document a double adjustment as households age: a rebalancing of the portfolio composition away from stocks as they approach retirement and stock market exit after retirement. When structurally estimating an extended life‐cycle model, the parameter combination that best fits the data is one with a relatively large risk aversion, a small per‐period participation cost, and a yearly probability of a large stock market loss in line with the frequency of stock market crashes in Norway.

Information Flows in Foreign Exchange Markets: Dissecting Customer Currency Trades

Published: 3/18/2016,  Volume: 71,  Issue: 2  |  DOI: 10.1111/jofi.12378  |  Cited by: 105

LUKAS MENKHOFF, LUCIO SARNO, MAIK SCHMELING, ANDREAS SCHRIMPF

We study the information in order flows in the world's largest over‐the‐counter market, the foreign exchange (FX) market. The analysis draws on a data set covering a broad cross‐section of currencies and different customer segments of FX end‐users. The results suggest that order flows are highly informative about future exchange rates and provide significant economic value. We also find that different customer groups can share risk with each other effectively through the intermediation of a large dealer, and differ markedly in their predictive ability, trading styles, and risk exposure.

Frailty Correlated Default

Published: 9/28/2009,  Volume: 64,  Issue: 5  |  DOI: 10.1111/j.1540-6261.2009.01495.x  |  Cited by: 412

DARRELL DUFFIE, ANDREAS ECKNER, GUILLAUME HOREL, LEANDRO SAITA

The probability of extreme default losses on portfolios of U.S. corporate debt is much greater than would be estimated under the standard assumption that default correlation arises only from exposure to observable risk factors. At the high confidence levels at which bank loan portfolio and collateralized debt obligation (CDO) default losses are typically measured for economic capital and rating purposes, conventionally based loss estimates are downward biased by a full order of magnitude on test portfolios. Our estimates are based on U.S. public nonfinancial firms between 1979 and 2004. We find strong evidence for the presence of common latent factors, even when controlling for observable factors that provide the most accurate available model of firm‐by‐firm default probabilities.

Carry Trades and Global Foreign Exchange Volatility

Published: 3/27/2012,  Volume: 67,  Issue: 2  |  DOI: 10.1111/j.1540-6261.2012.01728.x  |  Cited by: 744

LUKAS MENKHOFF, LUCIO SARNO, MAIK SCHMELING, ANDREAS SCHRIMPF

We investigate the relation between global foreign exchange (FX) volatility risk and the cross section of excess returns arising from popular strategies that borrow in low interest rate currencies and invest in high interest rate currencies, so‐called “carry trades.” We find that high interest rate currencies are negatively related to innovations in global FX volatility, and thus deliver low returns in times of unexpected high volatility, when low interest rate currencies provide a hedge by yielding positive returns. Furthermore, we show that volatility risk dominates liquidity risk and our volatility risk proxy also performs well for pricing returns of other portfolios.

Nonstandard Errors

Published: 4/17/2024,  Volume: 79,  Issue: 3  |  DOI: 10.1111/jofi.13337  |  Cited by: 112

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.