We study how foreign investors’ access to corporate information varies with pairwise geopolitical tensions between the investor's and investee's countries. Using a sample of 1,760 country‐pairs, we find that geopolitical tensions between a conference call host firm's country and a foreign country relate negatively with investor participation from that foreign country as well as the quality and tone of management responses in the call, suggesting reduced foreign investor information access with rising tensions. A single‐country analysis of Chinese AB‐share firms produces similar inferences. With higher China–foreign tensions, foreign attendance at private meetings with management declines, and English translations of local language disclosures become less frequent and shorter in length. Curtailment in English translations is more pronounced when local language disclosures contain politically sensitive words, suggesting lower information supply by firm choice. Reduced disclosures from geopolitical tensions are impounded in foreign investors’ asset pricing decisions, resulting in steeper foreign‐share price discounts.

This study examines the spillover effect of bank financial misconduct on the uninsured deposits of peer banks within local markets. We first validate that misconduct banks experience an increase in deposit spreads and a corresponding outflow of deposits following the misconduct. We then show local peer banks exhibit divergent deposit responses, contingent on how misconduct is perceived by information recipients in different economic contexts. During normal periods, depositors receiving a negative signal about bank misconduct reallocate their funds from misconduct banks to local peers, a local reallocation effect that decreases deposit spreads and increases deposit inflows for peer banks. Cross‐sectional analysis further reveals that this local reallocation effect is more pronounced for financially sophisticated depositors, amplified when peer banks have strong fundamentals, but attenuated when misconduct banks are financially sound. During financial crisis periods, however, bank misconduct leads to withdrawals from both misconduct banks and their peer banks, a local contagion effect whereby local peer banks face increased deposit spreads and deposit outflows following the misconduct.

Using the implementation of the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system from 1993 to 1996 as a shock to information dissemination technologies, we examine how a significant reduction in disclosure processing costs affects the real economy. We find that the EDGAR implementation leads to an increase in corporate investment and that this effect is concentrated in value firms. We provide evidence that improved equity financing and enhanced managerial incentives are likely the underlying mechanisms. Specifically, the EDGAR implementation leads to an increase in a firm's stock liquidity, a decrease in the cost of equity capital, and an increase in the level of equity financing. Consistent with the monitoring effect of broad information dissemination, the EDGAR implementation leads to an increase in a firm's operating performance. Our findings suggest that it is important to consider information dissemination beyond information production when examining the real effects of corporate disclosures.

We use machine learning methods and high‐dimensional detailed financial data to predict the direction of one‐year‐ahead earnings changes. Our models show significant out‐of‐sample predictive power: the area under the receiver operating characteristics curve ranges from 67.52% to 68.66%, significantly higher than the 50% of a random guess. The annual size‐adjusted returns to hedge portfolios formed based on the prediction of our models range from 5.02% to 9.74%. Our models outperform two conventional models that use logistic regressions and small sets of accounting variables, and professional analysts’ forecasts. Analyses suggest that the outperformance relative to the conventional models stems from both nonlinear predictor interactions missed by regressions and the use of more detailed financial data by machine learning.

We examine how options trading affects voluntary corporate disclosure, so that we can shed light on whether managers’ potential learning from the options market induces them to withhold disclosure. We find that options trading reduces the likelihood and frequency of management earnings forecasts, suggesting that firms that have active options trading on their stock make fewer voluntary disclosures. This finding is in accordance with the theoretical prediction that managers strategically reduce disclosure to avoid crowding out informed trading, which can give them informative feedback for their decision making. In support of the managerial learning channel, we document a real effect of reduced disclosure: When managers disclose less, options trading has a stronger positive effect on firm investment efficiency. The more pronounced effect of options trading on management earnings forecasts when the need for managerial learning is higher further supports the learning channel.

We study the relation between issuer operating performance and initial public offering (IPO) price formation from the initial price range to the offer price to the closing price on the first trading day. For a post‐bubble sample of 2001–2013 IPOs, we find that pre‐IPO net income and, in particular, operating cash flow are strongly, positively associated with the revision from the mid‐point of the initial price range to the offer price and that the “partial adjustment phenomenon” concentrates among issuers with the strongest operating performance. As for why publicly observable information helps predict changes in valuation from when the initial price range is set to when the offer price is set, our findings suggest that strong‐performing issuers, especially those offering small slices of ownership, have lower bargaining incentives and are susceptible to the underwriter(s) low‐balling the price range. Overall, our results suggest an important role for accounting information in understanding the pricing of book‐built IPOs and are consistent with the presence of agency problems between issuers and underwriters.

This study investigates whether companies engage in audit opinion shopping activities by exerting influence over an audit firm's decision to switch the engagement partner (“partner‐level opinion shopping”) in the Chinese setting, where the identities of engagement partners are publicly disclosed. Adopting the empirical framework developed by Lennox [2000], we show evidence that companies successfully engage in partner‐level opinion shopping. Further, partner‐level opinion shopping is more likely to be successful if a company is economically important to an audit firm, and it is less likely to be successful if the audit firm is formed as a partnership rather than a corporation. We also find that companies successfully engaging in partner‐level opinion shopping exhibit significantly lower earnings quality. Finally, we directly compare audit records between incoming and outgoing partners and find that, for companies that successfully improve audit opinions after partner switching, incoming partners have a significantly higher propensity to issue clean opinions than their outgoing counterparts.

Costs are sticky on average, that is, they fall less for sales decreases than they rise for equivalent sales increases. We examine the effect of this asymmetric cost behavior on a firm's dividend policy. Given investors’ aversion to dividend cuts, we predict that firms with higher resource adjustment costs and stickier costs pay lower dividends than their peers because they are less able to sustain any higher level of dividend payouts in the future. We find evidence consistent with this prediction. Further, using a regression discontinuity design that exploits variation in labor adjustment costs generated by close‐call union elections, we provide evidence suggesting that the negative relation between cost stickiness and dividend payouts is driven by resource adjustment costs. Our paper sheds new light on the determinants of dividend policy and demonstrates the role of cost behavior in corporate decisions.

We examine whether firms that imitate peer companies’ strategies (copycats) profit from such behavior and how their success may cause competitive harm to disclosing companies. We identify copycat companies by tracking the digital footprints of investment companies that view disclosures on the SEC EDGAR Web site. We find that copycat companies are able to identify profitable trades that outperform other trades disclosed by the copycatted companies by 5.5% annually. Such stock‐screening skills are related to investment sophistication and research intensity. Furthermore, copycats inflict greater damage on the performance of disclosing companies when they possess superior copycat skills, when disclosed trading strategies take longer to complete, and when disclosed stock holdings are characterized by high information asymmetry.

We develop a state‐of‐the‐art fraud prediction model using a machine learning approach. We demonstrate the value of combining domain knowledge and machine learning methods in model building. We select our model input based on existing accounting theories, but we differ from prior accounting research by using raw accounting numbers rather than financial ratios. We employ one of the most powerful machine learning methods, ensemble learning, rather than the commonly used method of logistic regression. To assess the performance of fraud prediction models, we introduce a new performance evaluation metric commonly used in ranking problems that is more appropriate for the fraud prediction task. Starting with an identical set of theory‐motivated raw accounting numbers, we show that our new fraud prediction model outperforms two benchmark models by a large margin: the Dechow et al. logistic regression model based on financial ratios, and the Cecchini et al. support‐vector‐machine model with a financial kernel that maps raw accounting numbers into a broader set of ratios.