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Volume 78: Issue 3 (June 2023)


ISSUE INFORMATION FM

Pages: 1227-1229  |  Published: 5/2023  |  DOI: 10.1111/jofi.13044  |  Cited by: 0


Andrew W. Lo

Pages: 1231-1234  |  Published: 5/2023  |  DOI: 10.1111/jofi.13230  |  Cited by: 0


CLO Performance

Pages: 1235-1278  |  Published: 4/2023  |  DOI: 10.1111/jofi.13224  |  Cited by: 5

LARRY CORDELL, MICHAEL R. ROBERTS, MICHAEL SCHWERT

We study the performance of collateralized loan obligations (CLOs) to understand the market imperfections giving rise to these vehicles and their corresponding economic costs. CLO equity tranches earn positive abnormal returns from the risk‐adjusted price differential between leveraged loans and CLO debt tranches. Debt tranches offer higher returns than similarly rated corporate bonds, making them attractive to banks and insurers that face risk‐based capital requirements. Temporal variation in equity performance highlights the resilience of CLOs to market volatility due to their closed‐end structure, long‐term funding, and embedded options to reinvest principal proceeds.


Pockets of Predictability

Pages: 1279-1341  |  Published: 5/2023  |  DOI: 10.1111/jofi.13229  |  Cited by: 21

LELAND E. FARMER, LAWRENCE SCHMIDT, ALLAN TIMMERMANN

For many benchmark predictor variables, short‐horizon return predictability in the U.S. stock market is local in time as short periods with significant predictability (“pockets”) are interspersed with long periods with no return predictability. We document this result empirically using a flexible time‐varying parameter model that estimates predictive coefficients as a nonparametric function of time and explore possible explanations of this finding, including time‐varying risk premia for which we find limited support. Conversely, pockets of return predictability are consistent with a sticky expectations model in which investors slowly update their beliefs about a persistent component in the cash flow process.


The Pollution Premium

Pages: 1343-1392  |  Published: 4/2023  |  DOI: 10.1111/jofi.13217  |  Cited by: 118

PO‐HSUAN HSU, KAI LI, CHI‐YANG TSOU

This paper studies the asset pricing implications of industrial pollution. A long‐short portfolio constructed from firms with high versus low toxic emission intensity within an industry generates an average annual return of 4.42%, which remains significant after controlling for risk factors. This pollution premium cannot be explained by existing systematic risks, investor preferences, market sentiment, political connections, or corporate governance. We propose and model a new systematic risk related to environmental policy uncertainty. We use the growth in environmental litigation penalties to measure regime change risk and find that it helps price the cross section of emission portfolios' returns.


Duration‐Driven Returns

Pages: 1393-1447  |  Published: 3/2023  |  DOI: 10.1111/jofi.13216  |  Cited by: 20

NIELS JOACHIM GORMSEN, EBEN LAZARUS

We propose a duration‐based explanation for the premia on major equity factors, including value, profitability, investment, low‐risk, and payout factors. These factors invest in firms that earn most of their cash flows in the near future and could therefore be driven by a premium on near‐future cash flows. We test this hypothesis using a novel data set of single‐stock dividend futures, which are claims on dividends of individual firms. Consistent with our hypothesis, the expected Capital Asset Pricing Model alpha on individual cash flows decreases in maturity within a firm, and the alpha is not related to the above characteristics when controlling for maturity.


Firm‐Level Climate Change Exposure

Pages: 1449-1498  |  Published: 3/2023  |  DOI: 10.1111/jofi.13219  |  Cited by: 175

ZACHARIAS SAUTNER, LAURENCE VAN LENT, GRIGORY VILKOV, RUISHEN ZHANG

We develop a method that identifies the attention paid by earnings call participants to firms' climate change exposures. The method adapts a machine learning keyword discovery algorithm and captures exposures related to opportunity, physical, and regulatory shocks associated with climate change. The measures are available for more than 10,000 firms from 34 countries between 2002 and 2020. We show that the measures are useful in predicting important real outcomes related to the net‐zero transition, in particular, job creation in disruptive green technologies and green patenting, and that they contain information that is priced in options and equity markets.


Macroeconomic News in Asset Pricing and Reality

Pages: 1499-1543  |  Published: 3/2023  |  DOI: 10.1111/jofi.13218  |  Cited by: 0

GREGORY R. DUFFEE

Revisions in successive Greenbook forecasts of quarterly real GDP growth proxy for news of current and expected future economic growth. In the sample 1975 through 2015, news of future growth is slightly negatively related to contemporaneous changes in Treasury bond yields, while news of current growth is strongly positively related to changes in these yields. Both results are difficult to reconcile with a representative agent's bondholding first‐order condition. A continuous‐time dynamic model of output attributes almost all of the covariation with yields to martingale innovations in log output and a minimal amount to innovations in the conditional drift of log output.


Who Owns What? A Factor Model for Direct Stockholding

Pages: 1545-1591  |  Published: 3/2023  |  DOI: 10.1111/jofi.13220  |  Cited by: 22

VIMAL BALASUBRAMANIAM, JOHN Y. CAMPBELL, TARUN RAMADORAI, BENJAMIN RANISH

We build a cross‐sectional factor model for investors' direct stockholdings and estimate it using data from almost 10 million retail accounts in the Indian stock market. Our model identifies strong investor clienteles for stock characteristics, most notably firm age and share price, and for particular clusters of stock characteristics. These clienteles are intuitively associated with investor attributes such as account age, size, and diversification. Coheld stocks tend to have higher return covariance, inconsistent with simple models of diversification but suggestive that clientele demands influence stock returns.


Integrating Factor Models

Pages: 1593-1646  |  Published: 4/2023  |  DOI: 10.1111/jofi.13226  |  Cited by: 13

DORON AVRAMOV, SI CHENG, LIOR METZKER, STEFAN VOIGT

This paper develops a comprehensive framework to address uncertainty about the correct factor model. Asset pricing inferences draw on a composite model that integrates over competing factor models weighted by posterior probabilities. Evidence shows that unconditional models record near‐zero probabilities, while postearnings announcement drift, quality‐minus‐junk, and intermediary capital are potent factors in conditional asset pricing. Out‐of‐sample, the integrated model performs well, tilting away from subsequently underperforming factors. Model uncertainty makes equities appear considerably riskier, while model disagreement about expected returns spikes during crash episodes. Disagreement spans all return components involving mispricing, factor loadings, and risk premia.


Visibility Bias in the Transmission of Consumption Beliefs and Undersaving

Pages: 1647-1704  |  Published: 4/2023  |  DOI: 10.1111/jofi.13223  |  Cited by: 3

BING HAN, DAVID HIRSHLEIFER, JOHAN WALDEN

We model visibility bias in the social transmission of consumption behavior. When consumption is more salient than nonconsumption, people perceive that others are consuming heavily, and infer that future prospects are favorable. This increases aggregate consumption in a positive feedback loop. A distinctive implication is that disclosure policy interventions can ameliorate undersaving. In contrast with wealth‐signaling models, information asymmetry about wealth reduces overconsumption. The model predicts that saving is influenced by social connectedness, observation biases, and demographic structure, and provides new insight into savings rates. These predictions are distinct from other common models of consumption distortions.


Naïve Buying Diversification and Narrow Framing by Individual Investors

Pages: 1705-1741  |  Published: 4/2023  |  DOI: 10.1111/jofi.13222  |  Cited by: 4

JOHN GATHERGOOD, DAVID HIRSHLEIFER, DAVID LEAKE, HIROAKI SAKAGUCHI, NEIL STEWART

We provide the first tests to distinguish whether individual investors equally balance their overall portfolios (naïve portfolio diversification, NPD) or, in contrast, equally balance the values of same‐day purchases of multiple assets (naïve buying diversification, NBD). We find NBD in purchases of multiple stocks, and in mixed purchases of individual stocks and funds. In contrast, there is little evidence of NPD. Evidence suggests that NBD arises due to stock picking behavior and neglect of diversification. These findings suggest that behavioral finance theory should incorporate transaction, as well as portfolio, framing.


Model Comparison with Transaction Costs

Pages: 1743-1775  |  Published: 4/2023  |  DOI: 10.1111/jofi.13225  |  Cited by: 25

ANDREW DETZEL, ROBERT NOVY‐MARX, MIHAIL VELIKOV

Failing to account for transaction costs materially impacts inferences drawn when evaluating asset pricing models, biasing tests in favor of those employing high‐cost factors. Ignoring transaction costs, Hou, Xue, and Zhang (2015, Review of Financial Studies, 28, 650–705) q‐factor model and Barillas and Shanken (2018, TheJournal of Finance, 73, 715–754) six‐factor models have high maximum squared Sharpe ratios and small alphas across 205 anomalies. They do not, however, come close to spanning the achievable mean‐variance efficient frontier. Accounting for transaction costs, the Fama and French (2015, Journal of Financial Economics, 116, 1–22; 2018, Journal of Financial Economics, 128, 234–252) five‐factor model has a significantly higher squared Sharpe ratio than either of these alternative models, while variations employing cash profitability perform better still.


Did FinTech Lenders Facilitate PPP Fraud?

Pages: 1777-1827  |  Published: 2/2023  |  DOI: 10.1111/jofi.13209  |  Cited by: 27

JOHN M. GRIFFIN, SAMUEL KRUGER, PRATEEK MAHAJAN

In the $793 billion Paycheck Protection Program, we examine metrics related to potential misreporting including nonregistered businesses, multiple businesses at residential addresses, abnormally high implied compensation per employee, and large inconsistencies with jobs reported in another government program. These measures consistently concentrate in certain FinTech lenders and are cross‐verified by seven additional measures. FinTech market share increased significantly over time, and suspicious lending by FinTechs in 2021 is four times the level at the start of the program. Suspicious loans are being overwhelmingly forgiven at rates similar to other loans.


ANNOUNCEMENTS

Pages: 1829-1829  |  Published: 5/2023  |  DOI: 10.1111/jofi.13234  |  Cited by: 0


AMERICAN FINANCE ASSOCIATION

Pages: 1830-1831  |  Published: 5/2023  |  DOI: 10.1111/jofi.13045  |  Cited by: 0