We analyze over 27,000 social media livestreams by Chinese mutual funds to investigate whether they achieve regulators’ goal of improving retail investment decisions. Our findings indicate that livestreams generate significant inflows, often within minutes of their start times. Yet rather than educating investors, livestreams amplify return-chasing behavior and predict sharp declines in fund performance. Investors who buy in response to livestreams would earn higher returns by holding index funds or even cash. Further analyses using deep learning algorithms reveal that livestreams are more persuasive when speakers are more physically attractive, use more positive language, and sound more excited. We conclude that livestreams primarily function as persuasive advertising and that regulators should be wary of educational efforts led by sellers of consumer financial products. We also conclude that prior evidence on the benefits of firms’ social media use in equity markets does not extend to financial product markets in this setting.

In 2005, the SEC mandated that firms disclose risk factors to provide useful information about firm risk. An unintended effect of the mandate is that mandatory risk factor (RF) disclosure may constitute “meaningful cautionary language” as defined in the Private Securities Litigation Reform Act, and may therefore provide legal protection for forward-looking statements (FLSs). Using both a difference-in-differences design and a two-stage least squares approach, we find that, following the mandate, firms that had not previously disclosed risk factors (late RF disclosers) became more willing to provide qualitative FLSs, particularly positive ones, than other firms. This finding is consistent with our prediction that, for late RF disclosers, the mandate reduces managers’ perceived litigation risk. We also find that these firms experience improvement in their information environment. A path analysis reveals that the mandate improves firms’ information environment not only directly but also indirectly by prompting more disclosure of positive FLSs, illustrating an unintended benefit of the 2005 RF mandate. Cross-sectional tests show that the RF mandate induces a larger increase in positive FLSs for firms whose managers perceive a higher level of benefit from safe harbor protection arising from meaningful cautionary statements.

We develop FinBERT, a state‐of‐the‐art large language model that adapts to the finance domain. We show that FinBERT incorporates finance knowledge and can better summarize contextual information in financial texts. Using a sample of researcher‐labeled sentences from analyst reports, we document that FinBERT substantially outperforms the Loughran and McDonald dictionary and other machine learning algorithms, including naïve Bayes, support vector machine, random forest, convolutional neural network, and long short‐term memory, in sentiment classification. Our results show that FinBERT excels in identifying the positive or negative sentiment of sentences that other algorithms mislabel as neutral, likely because it uses contextual information in financial text. We find that FinBERT's advantage over other algorithms, and Google's original bidirectional encoder representations from transformers model, is especially salient when the training sample size is small and in texts containing financial words not frequently used in general texts. FinBERT also outperforms other models in identifying discussions related to environment, social, and governance issues. Last, we show that other approaches underestimate the textual informativeness of earnings conference calls by at least 18% compared to FinBERT. Our results have implications for academic researchers, investment professionals, and financial market regulators.

We identify a specific organizational resource in brokerage houses—information sharing among analyst colleagues who cover economically related industries along a supply chain. After controlling for brokerage selection effects, we show evidence consistent with the benefit of this resource to analyst research performance. Specifically, we find that analysts whose colleagues cover more economically connected industries have better research performance, especially when their colleagues produce higher-quality research. We further show that colleagues' coverage of downstream (upstream) industries is positively related to the accuracy of only analysts’ revenue (expense) forecasts and that analysts and their highly connected colleagues tend to issue earnings forecast revisions contemporaneously. Last, we find that analysts with economically connected colleagues tend to have a higher level of industry specialization. Overall, our findings suggest that analysts rely on organizational resources to produce high-quality research. Hence, a portion of their performance and reputation is not transferable across employers.

This paper studies the long‐term consequences of actions induced by vesting equity, a measure of short‐term incentives. Vesting equity is positively associated with the probability of a firm repurchasing shares, the amount of shares repurchased, and the probability of the firm announcing a merger and acquisition (M&A). However, it is also associated with more negative long‐term returns over two to three years following repurchases and four years following M&A, as well as future M&A goodwill impairment. These results are inconsistent with CEOs buying underpriced stock or companies to maximize long‐run shareholder value, but consistent with these actions being used to boost the short‐term stock price and thus equity sale proceeds. CEOs sell their own stock shortly after using company money to buy the firm's stock, also inconsistent with repurchases being motivated by undervaluation.

Drawing on the political theory of judicial decision making, our paper proposes a new and parsimonious ex ante litigation risk measure: federal judge ideology. We find that judge ideology complements existing measures of litigation risk based on industry membership and firm characteristics. Firms in liberal circuits (the third quartile in ideology) are 33.5% more likely to be sued in securities class action lawsuits than those in conservative circuits (the first quartile in ideology). This result is stronger after the U.S. Supreme Court's ruling in the Tellabs case. We next show that the effect of judge ideology on litigation risk is greater for firms with more sophisticated shareholders and with higher expected litigation costs. Furthermore, judicial appointments affect litigation risk and the value of firms in the circuit, highlighting the economic consequences of political appointments of judges. Finally, using our new measure, we document that litigation risk deters managers from providing long‐term earnings guidance, a result that existing measures of litigation risk cannot show.

Errors and bias are both inherent features of accounting. In theory, while errors discourage bias by lowering the value relevance of accounting, they can also facilitate bias by providing camouflage. Consistent with theory, we find a hump‐shaped relation between a firm's propensity to engage in intentional misstatement and the prevalence of unintentional misstatements in the firm's industry for the whole economy and a majority of the industries. The result is robust to using firms’ number of items in financial statements and exposure to complex accounting rules as alternative proxies for errors and to using the restatement amount in net income to quantify the magnitude of bias and errors. To directly test for the two effects of errors, we show that when errors are more prevalent, the market reacts less to firms’ earnings surprises and bias is more difficult to detect. Our results highlight the imperfectness of accounting, advance understanding of firms’ reporting incentives, and shed light on accounting standard setting.

In common-law systems, firms’ litigation risk depends both on written laws and how courts interpret these laws. Using 321 US circuit court rulings, we introduce a novel measure capturing courts’ attitudes toward defendants in securities lawsuits. Our results confirm that financial misreporting firms in more defendant-friendly circuits face fewer lawsuits. Consistent with lower expected litigation costs, firms in these circuits face less negative market reactions when misreporting is revealed, invest less in preventing misreporting, and are more likely to engage in aggressive misreporting. We conclude that defendant-friendly precedents reduce firms’ legal liability and worsen their financial reporting quality.

Although federal judges are the ultimate arbiters of insider trading enforcement, the role of their political ideology in insider trading is unclear. Using the partisanship of judges’ nominating presidents to measure judge ideology, we first document that liberal judges are associated with heavier penalties in insider trading lawsuits than conservative judges. Next, we find that firms located in circuits with more liberal judges have fewer opportunistic insider sales. Cross-sectional analyses show that this deterrent effect is stronger when managers face a higher risk of insider trading lawsuits. Finally, we find that the Securities and Exchange Commission considers judges’ ideology when selecting litigation forums.

This article uses the enactment of China’s 2007 Property Law (the Law), which reduces the risk of expropriation by local governments, as the setting to investigate the importance of property rights protection for private firm investment. Using propensity score matching and a difference-in-differences design, we find that firms facing weaker property rights protection prior to the Law significantly increase their investment and investment efficiency after the Law. Cross-sectional analyses document evidence consistent with a decrease in firms’ perceived expropriation risk as the main mechanism underlying the Law’s effect. Finally, we show that the Law improves local economic outcomes and employment.