This study examines the institutional demand for mispriced stocks with incongruent expectations implied by the book-to-market (BM) ratio and financial strength. Institutional trading (or institutional demand) is calculated by both changes in institutional ownership (percentage of shares held) and the number of institutional investors from the previous to the current quarter. Market mispricing and expectation errors in value/glamour stocks can be identified by analysing firms’ recent financial strength (measured by FSCORE). Firms are sorted into value stocks (top 30%), middle stocks (between 30% and 70%) and glamour stocks (bottom 30%) by distribution of BM ratios at the end of the previous fiscal year. Firms in the sample are then double sorted by FSCORE and BM: in each BM portfolio, firms are further classified into high-, mid- and low-FSCORE groups. Consistent with the argument of expectation errors in value/glamour stocks (Piotroski and So, 2012), institutional investors buy value stocks with strong fundamentals (underpriced) and sell glamour stocks with weak fundamentals (overpriced). Independent institutions are more likely to take advantage of the mispricing in value/glamour firms than passive institutions. Institutional trading on expectation errors could reduce the abnormal returns to mispriced stocks. Institutional trading patterns on mispriced value/glamour stocks are also documented in global markets. Our research provides new evidence that the institutional investors do exploit the BM anomalies if the mispricing can be identified by both the BM and the recent financial strength. Our study differs from Caglayan, Celiker and Sonaer (2018) as we emphasise that financial institutions, in addition to relying on only the BM values, process information from financial statements to infer firms’ financial strength. This study is also the first to document that institutional demand on mispricing could attenuate the BM anomaly.

We investigate the relationship between county-level social capital in the U.S. and asymmetric earnings timeliness (accounting conservatism). We measure social capital by the strength of civic norms and the density of social networks in a community. We find that firms headquartered in regions with higher social capital have earnings that reflect bad news more quickly than good news. Two potential mechanisms driving this connection are evident in our findings. First, the positive link between social capital and asymmetric earnings timeliness is more pronounced in firms with weaker external oversight, suggesting that social capital compensates for weaknesses in these mechanisms by discouraging managers from delaying the recognition of bad news. Second, we illustrate that firms in high social capital regions are more likely to recruit senior executives with higher asymmetric earnings timeliness coefficients. This result implies a preference for managers who adopt more conservative accounting practices. We find similar results using an international sample of firms from 21 countries. Our findings offer new insights into how local social norms influence corporate financial reporting.

Predicting IPO first-day returns is inherently challenging due to the wide range of contributing factors, each with distinct statistical properties. We assess the performance of several machine learning (ML) techniques and identify XGBoost as the most statistically effective model for forecasting first-day returns. Using a comprehensive set of 863 pre-IPO variables, our high-performing predictive model accurately estimates both the direction and magnitude of IPO first-day returns. The most influential predictors include underwriter agency measures, price revision, and the free-float fraction. Using a rolling-window predictive approach, the model demonstrates substantial practical value, generating approximately $300 billion in gains from IPOs with positive first-day returns and avoiding more than $22 billion in losses from those with negative returns over the 2000–2016 period.

This paper examines the impact of climate risks on the debt structure of a sample of U.S. firms from 2002 through 2020. Climate risks—mainly physical, regulatory, and transition risks—are associated with a concentrated debt structure for the affected firms. However, when climate risks propagate through the channels of expected bankruptcy costs and sustainability, they are associated with a more diversified debt structure. Additionally, climate risks asymmetrically impact the relationship between access to finance and debt structure. Results from a quasi-natural experiment reaffirm the impact of climate risks on debt structure.

In this paper, we use granular trading data from Taiwan between 2012 and 2016 to examine how local social capital influences retail investor behavior during corporate social irresponsibility (CSIR) events. Therefore, we are responding to longstanding calls in the international finance literature to explore investor behavior in non-US markets with distinct institutional and cultural characteristics. We find that investors residing in cities with higher social capital are less likely to purchase underpriced stocks following the announcements of negative events despite the potential for positive abnormal returns. This norm-driven restraint reflects a form of socially responsible investing motivated by community-based values rather than economic rationality. By documenting this behavior in an East Asian market, we extend the external validity of social norm theories developed in Western settings and contribute to a more nuanced understanding of how localized social preferences can influence asset pricing and capital allocation in a global context.

Using lenders who become members of the Task Force on Climate-Related Financial Disclosures (TCFD) as an exogenous shock, we examine whether and how lenders’ commitment to transparent climate-related disclosures affects borrowers’ environmental performance. We find that borrowers of TCFD-member lenders, relative to control firms, significantly improve their environmental performance after the TCFD launch. Lenders’ disclosure commitments influence borrowers through credit rationing and monitoring. Specifically, polluting borrowers face higher borrowing costs, reduced access to credit, and greater incorporation of environmental action covenants in loan agreements. Additionally, polluting borrowers of TCFD-member lenders experience heightened financial constraints. Finally, borrowers of TCFD-member lenders are more likely to adopt the TCFD framework for climate-related disclosure after the TCFD establishment. Together, these findings illuminate the role of lenders in driving corporate environmental performance improvement through their commitment to transparent climate-related disclosures.

We assemble data about executives on the boards of national supervisory authorities (NSA) in European banking, which reveal that 40% have an employment history in the financial industry. Appointment patterns to NSA boards differ substantially across countries. Generally, the appointment of former finance professionals as prudential supervisors is inconsequential for banks‘ valuations, capitalization, and asset growth. The exception are positive, but short-lived valuation effects for those banks whose alumni are appointed as executives of directly responsible NSA boards. Circumstantial evidence suggests that a “proximity bias“ is a more likely driver of this effect instead of superior financial expertise or intrinsic skills of the designated NSA executives.