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作者:Bertomeu, Jeremy; Cheynel, Edwige; Floyd, Eric; Pan, Wenqiang
作者单位:Washington University (WUSTL); University of California System; University of California San Diego; Columbia University
摘要:Machine learning offers empirical methods to sift through accounting datasets with a large number of variables and limiteda prioriknowledge about functional forms. In this study, we show that these methods help detect and interpret patterns present in ongoing accounting misstatements. We use a wide set of variables from accounting, capital markets, governance, and auditing datasets to detect material misstatements. A primary insight of our analysis is that accounting variables, while they do n...
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作者:Truong, Cameron; Nguyen, Thu Ha; Huynh, Thanh
作者单位:Monash University; Monash University
摘要:Using a sample of U.S. firms from 1995 through 2015 and the customer satisfaction scores from the American Customer Satisfaction Index, we find strong evidence that firms with higher customer satisfaction scores enjoy lower cost of equity capital, even after controlling for other factors that determine the cost of equity. In addition, results from a propensity score matched sample analysis, a difference-in-differences analysis, and instrumental variable regressions suggest that our findings ar...
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作者:Christ, Margaret H.; Emett, Scott A.; Summers, Scott L.; Wood, David A.
作者单位:University System of Georgia; University of Georgia; Arizona State University; Arizona State University-Tempe; Brigham Young University
摘要:Auditors increasingly employ technologies to improve audit quality. Using a design science approach, we examine whether using drones and automated counting software can improve audit quality and thus financial reporting. We assess three dimensions of audit quality-efficiency, effectiveness, and quality of documentation. We show that auditors can perform inventory counts with these technologies much more efficiently than they can with manual techniques, decreasing count time in our study from 6...
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作者:Bertomeu, Jeremy; Vaysman, Igor; Xue, Wenjie
作者单位:Washington University (WUSTL); City University of New York (CUNY) System; Baruch College (CUNY); National University of Singapore
摘要:We develop a theory of asymmetries between voluntary and mandatory disclosure. Efficiently designed mandatory disclosure policies are substitutes for excessive voluntary disclosures. The efficient policy takes the form of a lower threshold below which firms must disclose bad news and an upper threshold above which firms voluntarily disclose good news. Hence mandatory disclosures are asymmetric and feature conservative reporting of bad news. The threshold to recognize bad news increases when in...
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作者:Ellahie, Atif
作者单位:Utah System of Higher Education; University of Utah
摘要:The literature on cash flow or earnings beta is theoretically well-motivated in its use of fundamentals, instead of returns, to measure systematic risk. However, empirical measures of earnings beta based on either log-linearizing the return equation or log-linearizing the clean-surplus accounting identity are often difficult to construct. I construct simple earnings betas based on various measures of realized and expected earnings and find that an earnings beta based on price-scaled expectatio...
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作者:Lundholm, Russell J.
作者单位:University of British Columbia
摘要:This paper models the value of conducting financial statement analysis (FSA) in the presence of an electronically traded fund (ETF) that gives exposure to the firm's systematic value. FSA is characterized as a costly process that yields a private signal about the idiosyncratic portion of a firm's future payoffs. The value of this signal depends on how efficiently price transmits information to uninformed traders. A popular argument is that ETFs are attracting noise traders away from the underl...
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作者:Holzman, Eric R.; Marshall, Nathan T.; Schroeder, Joseph H.; Yohn, Teri Lombardi
作者单位:University System of Ohio; Ohio State University; University of Colorado System; University of Colorado Boulder; Indiana University System; Indiana University Bloomington; Emory University
摘要:Research suggests that greater earnings disaggregation in financial statements leads to favorable market outcomes. This perspective is based on a presumption that the disaggregation separates earnings components with heterogeneous characteristics. We hypothesize that the disaggregation of homogeneous earnings components is associated with greater investor disagreement and a less efficient market response to the earnings announcement. We estimate persistence regressions at the industry level an...
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作者:Kang, Jung Koo; Williams, Christopher D.; Wittenberg-Moerman, Regina
作者单位:University of Southern California; University of Michigan System; University of Michigan
摘要:We investigate how credit default swaps (CDSs) affect lenders' incentives to initiatenewlending relationships. We predict that CDSs reduce adverse selection that nonrelationship lead arrangers face when competing for loans. Consistently, we find that a loan is more likely to be syndicated by a nonrelationship lead arranger following CDS trading initiation on a borrower's debt. We also show that borrowers that obtain loans from nonrelationship lead arrangers in the post-CDS trading initiation p...
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作者:Crawford, Steve; Markarian, Garen; Muslu, Volkan; Price, Richard
作者单位:University of Houston System; University of Houston; WHU - Otto Beisheim School of Management; University of Oklahoma System; University of Oklahoma - Norman
摘要:Research has failed to document a consistent association between oil prices and stock prices. We propose and examine whether that failure is due to the need to link oil price changes to firm-level changes in earnings and investments. We find that the impact of oil prices on a firm's earnings and investments varies significantly by industry and by whether the firm is an oil producer or oil consumer. Nevertheless, firm fixed effects explain more than 10 times the variation between oil prices and...
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作者:Bertomeu, Jeremy
作者单位:Washington University (WUSTL)
摘要:Machine learning has been growing in importance in empirical accounting research. In this opinion piece, I review the unique challenges of going beyond prediction and leveraging these tools into generalizable conceptual insights. Taking as springboard Machine learning improves accounting estimates presented at the 2019 Conference of the Review of Accounting Studies, I propose a conceptual framework with various testable implications. I also develop implementation considerations panels with acc...