Pages: 1-4 | Published: 1/2022 | DOI: 10.1111/jofi.12915 | Cited by: 0
Predictably Unequal? The Effects of Machine Learning on Credit Markets
Pages: 5-47 | Published: 12/2021 | DOI: 10.1111/jofi.13090 | Cited by: 44
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.
Pages: 49-83 | Published: 12/2021 | DOI: 10.1111/jofi.13097 | Cited by: 7
ISAAC HACAMO, KRISTOPH KLEINER
Conventional wisdom suggests that labor market distress drives workers into temporary self‐employment, lowering entrepreneurial quality. Analyzing employment histories for 640,000 U.S. workers, we document that graduating college during a period of high unemployment does increase entry to entrepreneurship. However, compared to voluntary entrepreneurs, firms founded by forced entrepreneurs are more likely to survive, innovate, and receive venture backing. Explaining these results, we confirm that labor shocks disproportionately impact high earners, with these workers starting more successful firms. Overall, we document untapped entrepreneurial potential across the top of the income distribution and the role of recessions in reversing this missing entrepreneurship.
The Loan Covenant Channel: How Bank Health Transmits to the Real Economy
Pages: 85-128 | Published: 8/2021 | DOI: 10.1111/jofi.13074 | Cited by: 22
GABRIEL CHODOROW‐REICH, ANTONIO FALATO
We document the importance of covenant violations in transmitting bank health to nonfinancial firms. Roughly one‐third of loans in our supervisory data breach a covenant during the 2008 to 2009 period, allowing lenders to force a renegotiation of loan terms or to accelerate repayment of otherwise long‐term credit. Lenders in worse health are more likely to force a reduction in the loan commitment following a violation. The reduction in credit to borrowers who violate a covenant can account for the majority of the cross‐sectional variation in credit supply during the 2008 to 2009 crisis.
Monetary Policy Spillovers through Invoicing Currencies
Pages: 129-161 | Published: 8/2021 | DOI: 10.1111/jofi.13071 | Cited by: 3
This paper explores the role of trade invoicing currencies in the international spillover of monetary policy. Using high‐frequency measures of Federal Reserve monetary policy shocks, I show that exchange rates, interest rates, and equity returns in countries with a larger share of dollar‐invoiced imports systematically respond more to U.S. monetary policy. I document similar transmission effects from European Central Bank (ECB) monetary policy shocks to countries with euro‐invoiced imports. I rationalize these findings within a New Keynesian framework. As a result of these spillovers, domestic monetary policy should be less effective in countries with traded goods invoiced in foreign currencies.
Cultural Biases in Equity Analysis
Pages: 163-211 | Published: 12/2021 | DOI: 10.1111/jofi.13095 | Cited by: 10
A more positive cultural trust bias by an equity analyst's country of origin toward a firm's headquarter country is associated with significantly more positive stock recommendations. The cultural bias effect is stronger for eponymous firms whose names mention their home country and varies over time, increasing with negative sentiment. I find evidence of a negative North‐South bias during the European debt crisis and United Kingdom‐Europe divergence amid Brexit. Share price reactions to recommendations by more biased analysts are weaker, and more biased recommendations are worse predictors of monthly stock returns. More positively biased analysts also assign higher target prices.
Institutional Investors and Corporate Governance: The Incentive to Be Engaged
Pages: 213-264 | Published: 10/2021 | DOI: 10.1111/jofi.13085 | Cited by: 12
JONATHAN LEWELLEN, KATHARINA LEWELLEN
This paper studies institutional investors’ incentives to be engaged shareholders. In 2017, the average institution gains an extra $129,000 in annual management fees if a stockholding increases 1% in value, considering both the direct effect on assets under management and the indirect effect on subsequent fund flows. The estimates range from $19,600 for investments in small firms to $307,600 for investments in large firms. Institutional shareholders in one firm often gain when the firm's competitors do well, by virtue of institutions’ holdings in those firms, but the impact of common ownership is modest in the most concentrated industries.
Non‐Deal Roadshows, Informed Trading, and Analyst Conflicts of Interest
Pages: 265-315 | Published: 11/2021 | DOI: 10.1111/jofi.13089 | Cited by: 7
DANIEL BRADLEY, RUSSELL JAME, JARED WILLIAMS
Non‐deal roadshows (NDRs) are private meetings between management and institutional investors, typically organized by sell‐side analysts. We find that around NDRs, local institutional investors trade heavily and profitably, while retail trading is significantly less informed. Analysts who sponsor NDRs issue significantly more optimistic recommendations and target prices, together with more “beatable” earnings forecasts, consistent with analysts issuing strategically biased forecasts to win NDR business. Our results suggest that NDRs result in a substantial information advantage for institutional investors and create significant conflicts of interests for the analysts who organize them.
Female Representation in the Academic Finance Profession
Pages: 317-365 | Published: 12/2021 | DOI: 10.1111/jofi.13094 | Cited by: 8
MILA GETMANSKY SHERMAN, HEATHER E. TOOKES
We present new data on female representation in the academic finance profession. In our sample of finance faculty at top‐100 U.S. business schools during 2009 to 2017, only 16.0% are women. The gender imbalance manifests in several ways. First, after controlling for research productivity, women hold positions at lower ranked institutions and are less likely to be full professors. Results also suggest that they are paid less. Second, women publish fewer papers. This gender gap exists in research quantity, not quality. Third, women have more female coauthors, suggesting smaller publication networks. Time‐series data suggest shrinking gender gaps in recent years.
Increasing Enrollment in Income‐Driven Student Loan Repayment Plans: Evidence from the Navient Field Experiment
Pages: 367-402 | Published: 11/2021 | DOI: 10.1111/jofi.13088 | Cited by: 7
HOLGER MUELLER, CONSTANTINE YANNELIS
We report evidence from a randomized field experiment conducted by a major student loan servicer, Navient, in which student loan borrowers received prepopulated applications for income‐driven repayment (IDR) plans. Treatment increased IDR enrollment by 34 percentage points relative to the control group. Using the random treatment assignment as an instrument for IDR enrollment, we furthermore provide local average treatment effect (LATE) estimates of the effects of IDR enrollment on new delinquencies, monthly student loan payments, and consumer spending. Our study is the first field‐experimental evaluation of a U.S. government program designed to address the soaring debt burdens of U.S. households.
Borrowing to Save? The Impact of Automatic Enrollment on Debt
Pages: 403-447 | Published: 8/2021 | DOI: 10.1111/jofi.13069 | Cited by: 7
JOHN BESHEARS, JAMES J. CHOI, DAVID LAIBSON, BRIGITTE C. MADRIAN, WILLIAM L. SKIMMYHORN
Does automatic enrollment into a retirement plan increase financial distress due to increased borrowing outside the plan? We study a natural experiment created when the U.S. Army began automatically enrolling newly hired civilian employees into the Thrift Savings Plan. Four years after hire, automatic enrollmentincreases cumulative contributions to the plan by 4.1% of annual salary, but we find little evidence ofincreased financial distress. Automatic enrollment causes no significant change in credit scores, debt balances excluding auto debt and first mortgages, or adverse credit outcomes, with the possible exception of increasedfirst‐mortgage balances in foreclosure.
How Do Financial Constraints Affect Product Pricing? Evidence from Weather and Life Insurance Premiums
Pages: 449-503 | Published: 12/2021 | DOI: 10.1111/jofi.13093 | Cited by: 9
I identify the effects of financial constraints on firms' product pricing decisions, using insurance groups containing both life and property & casualty (P&C) divisions. Following P&C divisions' losses, life divisions change prices in a manner that can generate more immediate financial resources: premiums fall (rise) for life policies that immediately increase (decrease) insurers' financial resources. Premiums change more in groups that are more constrained. Life divisions increase transfers to P&C divisions, suggesting P&C divisions' shocks are transmitted to life divisions. Results hold when instrumenting for P&C divisions' losses with exposure to unusual weather damages, implying that the effects are causal.
Clients' Connections: Measuring the Role of Private Information in Decentralized Markets
Pages: 505-544 | Published: 12/2021 | DOI: 10.1111/jofi.13087 | Cited by: 4
PÉTER KONDOR, GÁBOR PINTÉR
We propose a new measure of private information in decentralized markets—connections—which exploits the time variation in the number of dealers with whom a client trades in a time period. Using trade‐level data for the U.K. government bond market, we show that clients perform better when having more connections as their trades predict future price movements. Time variation in market‐wide connections also helps explain yield dynamics. Given our novel measure, we present two applications suggesting that (i) dealers pass on information, acquired from their informed clients, to their affiliates, and (ii) informed clients better predict the orderflow intermediated by their dealers.
Stock Market and No‐Dividend Stocks
Pages: 545-599 | Published: 12/2021 | DOI: 10.1111/jofi.13098 | Cited by: 2
ADEM ATMAZ, SULEYMAN BASAK
We develop a stationary model of the aggregate stock market featuring both dividend‐paying and no‐dividend stocks within a familiar, parsimonious consumption‐based equilibrium framework. We find that such a simple feature leads to profound implications supporting several stock market empirical regularities that leading consumption‐based asset pricing models have difficulty reconciling. Namely, the presence of no‐dividend stocks in the stock market leads to a lower correlation between stock market returns and the aggregate consumption growth rate, a nonmonotonic and even negative relation between the stock market risk premium and its volatility, and a downward‐sloping term structure of equity risk premia.
Skill, Scale, and Value Creation in the Mutual Fund Industry
Pages: 601-638 | Published: 11/2021 | DOI: 10.1111/jofi.13096 | Cited by: 7
LAURENT BARRAS, PATRICK GAGLIARDINI, OLIVIER SCAILLET
We develop a flexible and bias‐adjusted approach to jointly examine skill, scalability, and value‐added across individual funds. We find that skill and scalability (i) vary substantially across funds, and (ii) are strongly related, as great investment ideas are difficult to scale up. The combination of skill and scalability produces a value‐added that (i) is positive for the majority of funds, and (ii) approaches its optimal level after an adjustment period (possibly due to investor learning). These results are consistent with theoretical models in which funds are skilled and able to extract economic rents from capital markets.
Anomalies and the Expected Market Return
Pages: 639-681 | Published: 12/2021 | DOI: 10.1111/jofi.13099 | Cited by: 18
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.
Pages: 683-683 | Published: 1/2022 | DOI: 10.1111/jofi.13103 | Cited by: 0
Preliminary Program AFA 2022 ANNUAL MEETING EIGHTY‐SECOND ANNUAL MEETING AMERICAN FINANCE ASSOCIATION
Pages: 684-735 | Published: 1/2022 | DOI: 10.1111/jofi.13101 | Cited by: 0
Participant Schedule for the AFA 2022 Preliminary Program January 7–9, 2022 : January 7–9, 2022
Pages: 736-805 | Published: 1/2022 | DOI: 10.1111/jofi.13102 | Cited by: 0
Pages: 806-806 | Published: 1/2022 | DOI: 10.1111/jofi.13104 | Cited by: 0
Pages: 807-808 | Published: 1/2022 | DOI: 10.1111/jofi.12916 | Cited by: 0