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The purpose of this paper is to investigate the effect of long horizon institutional ownership on CEO career concerns to meet the short-term earnings benchmark.

Using a sample of 10,565 firm-year observations in the USA, the paper examines the extent to which long horizon institutional investors mitigate the positive relation between CEO turnover and missing the quarterly consensus analyst forecast.

After controlling for the general performance-turnover relation, this paper finds that long horizon institutional investors mitigate the positive relation between CEO turnover and missing the quarterly consensus analyst forecast. This finding is stronger when CEOs focus on long-term value creation and do not sacrifice long-term value to boost current earnings and is stronger when the monitoring intensity by long horizon institutional investors is greater.

The results suggest that long horizon institutional investors serve a monitoring role in alleviating CEO career concerns to meet the short-term earnings benchmark.

This paper contributes to the literature on the relation between long horizon institutional ownership and attenuated managerial short-termism. The literature is silent about why long horizon institutional investors alleviate managerial short-termism. This paper fills this void in the literature by documenting that long horizon institutional investors mitigate CEO career concerns for managerial short-termism. Moreover, this paper contributes to the literature on the monitoring role of institutional investors by documenting the incremental effect of institutional ownership on CEO career concerns to meet the short-term earnings benchmark.

Whether institutional investors monitor corporations and improve firm value is a key question for corporate governance and investment management. I find little empirical support for the hypothesis that institutions undertake monitoring that increases firm quality and valuation. Granger causation tests show that while quality firms do attract institutional investment, institutions do not monitor and firm value subsequently declines. Instead, institutional incentives are critical; some institutions with strong incentives to monitor do, indeed, monitor. Institutions with concentrated portfolios successfully monitor while institutions with a larger percentage stake do not. Pensions and endowments are better monitors than insurers, banks and mutual funds.

Research on the significance of corporate social responsibility (CSR) and value creation is nascent as compared to CSR and financial performance. The concept of value is also evolving because of changing business environments, globalization and the expanded idea of CSR. Nowadays, managers expect a more quick, pragmatic approach to satisfy valid stakeholder claims while simultaneously creating competitive advantage through reputation and investor value. The paper aims to examine the impact of CSR on the market and sustainable value creation through CSR expenditure in India and the moderating role of pressure-sensitive institutional investors (PSII).

The study used panel data regression methodology on a sample of 1,845 non-financial Indian firms from 2015 to 2021.

CSR creates market and sustainable value for non-financial Indian firms in line with stakeholder theory. The authors find a positive moderating role of governance represented by PSII on CSR and market value creation but not on sustainable value.

The study is based on secondary data. CSR, despite being a regulatory obligation, provided long-term benefits that increased their sustainable growth rate. The results highlight the importance given by financial markets to CSR activities. Other types of institutional investors can also be examined in future research. CSR can be embedded in the core operations of the firm, which can help in fostering a culture of sustainability and responsible business practices that benefit firms and society as a whole. Tax incentives can be provided to firms investing in CSR.

CSR provides long-term benefits to the firm, which enhances the goodwill and integrity of the firm in the market. The results reveal that besides capital market investors, firms are subject to the scrutiny of consumers, communities and the government as expectations rise and information spreads faster, which can have repercussions. CSR helps in meeting such expectations and the perceived value of the firms. Managers and chief executive officers (CEOs) can pay attention to the type of institutional investors like PSII, which can be formed as a part of the firm’s CSR strategy.

The positive impact of CSR on sustainable value expresses a long-term management orientation based on the improvement of stakeholder relations and the associated environmental impacts referring to cohesion and consensus, market opportunities and strengthened reputation and image. A sustainable company involves a conscious and continuing effort in the equilibrium between contrasting stakeholders’ expectations in an attempt to optimize value creation. Tax exemption can be provided for CSR activities.

The authors contribute to the scant literature on CSR and value creation, especially sustainable value, as most of the prior studies are not empirical on sustainable value in the Indian context. Managers and CEOs can pay attention to the types of institutional investors like PSII, which can be formed as a part of the firm’s strategy.

In this study, we investigate whether higher institutional ownership is related to better internal controls and whether better internal control is associated with a higher quality of transparency.

This study aims to examine the reaction of anchor investors (AIs) to pre-IPO earnings management (EM). The authors use the unique detailed bid data from the Indian anchor experiment. The authors also study the reputed AIs’ EM detection ability and pricing behavior in response to pre-IPO EM.

The authors use unique AI bid data for 169 Indian IPO firms. Utilizing the logistic regression and Tobit regression models with industry and year-fixed effects, the authors examine the relationship between various measures of AI participation and proxies of short-term and long-term discretionary accruals.

The authors document that pre-IPO EM is positively associated with the likelihood of anchor backing but negatively related to the likelihood of reputed anchor backing. The findings indicate that AIs are misled by pre-IPO EM, but reputed AIs are not. The authors also observe that reputed AIs, compared to the non-reputed, pay less than the upper band with increasing EM. The findings are robust to using various AI measures and EM proxies.

The findings have significant implications for regulators in the implementation of AI concept in non-anchor markets and better implementation of policies in existing anchor settings. Findings can also be relevant for non-institutional investors in the IPO domain.

This is one of the few studies on institutional investors' IPO bidding behavior in response to pre-IPO EM. However, this is the first study to analyze AIs' IPO bidding behavior in response to pre-IPO EM.

This study explores the association between individual investor information demand and two measures of market uncertainty – aggregate market uncertainty and disaggregate industry-specific market uncertainty. It extends the literature by being the first to empirically examine investor information demand and disaggregate market uncertainty.

This paper constructs a measure of information search by using the Google Search Volume Index and computes measures of aggregate and disaggregate market uncertainty using institutional investors' trading data from Ancerno Ltd. The relation between market uncertainty, as measured by trading disagreements among institutional investors, and information search is analyzed using an OLS (Ordinary Least Squares) regression model.

This paper finds that individual investor information demand is significantly and positively correlated with aggregate market uncertainty but not associated with disaggregated industry uncertainty. The findings suggest that individual investors may not fully incorporate all relevant uncertainty information and that ambiguity-related market pricing anomalies may be more associated with disaggregate market uncertainty.

This study presents an examination of aggregate and disaggregate measures of market uncertainty and individual investor demand for information, shedding light on the efficiency of the market in incorporating information. A limitation of our study is that our data for market uncertainty is based on investor trading disagreement from Ancerno, Ltd. which is only available till 2011. However, we believe the implications are generalizable to the current time period.

This study provides the first concurrent empirical assessment of investor information search and aggregate and disaggregate market uncertainty. Prior research has separately examined information demand in these two types of market uncertainty. Thus, this study provides information to investors regarding the importance of assessing disaggregate component measures of the market.

This paper is the first to empirically examine investor information search and disaggregate market uncertainty. It also employs a unique data set and method to determine disaggregate, and aggregate, market uncertainty.

This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.

This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.

There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.

The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.

The purpose of this paper is to investigate the effect of share pledging by controlling shareholders on earnings informativeness.

Using a sample of 23,120 firm-year observations from 2003 to 2019 in China, this paper examines how share pledging by controlling shareholders affects earnings informativeness, measured by earnings persistence and earnings response coefficients.

This paper finds that share pledging by controlling shareholders makes earnings less informative. The adverse impacts are more pronounced when share pledging distorts incentives of controlling shareholders to a greater extent and when the signaling of share pledging about a firm’s weak future performance is stronger. Finally, this paper further shows that the 2018 new regulation on share pledging effectively alleviates the negative impacts of share pledging on earnings informativeness.

First, this paper adds to the growing literature on the economic consequence of share pledging by documenting the adverse impacts of share pledging on earnings informativeness. The literature on the economic consequence of share pledging is often mixed, which justifies further research on the impacts of share pledging on earnings informativeness. Second, this paper documents a new signaling channel through which share pledging affects earnings informativeness. Third, the finding of this paper on the 2018 new regulation on share pledging may be interesting to research agencies, such as the Chartered Financial analyst institute and Institutional Shareholder Services institute that recommend tightening regulations on share pledging.

This analysis is the first to explore the overall roles of the offsetting attraction and distraction influences of earnings news in shaping the level of attention given to the equity market by market participants.

We use multivariate regression approach and examine how trading activity levels within the set of non-announcing firms varies with respect to collective measures of contemporaneous earnings announcement visibility. We employ attention and information transfer theories in our hypothesis development.

This analysis is the first to explore the overall roles of the offsetting attraction and distraction influences of earnings news in shaping the level of attention given to the equity market by market participants. Specifically, we examine how the number of earnings announcement activity affects investor attention as measured by trading volume given to the set of non-announcing firms. We find that while earnings announcement numbers lower trading volume responses to earnings news among announcing firms (consistent with Hirshleifer et al., 2009), their distractive influence does not carry over into the market as a whole. More importantly, investor attention to both the overall market and the larger subset of non-announcing firms increase in response to earnings news activity levels. However, after decomposing the announcers as same-industry and different-industry announcers, we find that investor attention to the non-announcing segment of the market increases with the number of same-industry announcers, but actually seems to decrease (i.e. they distract attention) with the number of different-industry announcers. We also find that the associated earnings surprise brings attention to non-announcing firms (consistent with earnings news is relevant to overall market price movements). Finally, we find that distraction effects are attenuated in the financial crisis period.

A promising area of future research is to examine the relation between market pricing efficiency and aggregate earnings activity for the set of non-announcing firms. Although it will be a challenging task to measure pricing efficiency for the non-announcers, this will complement the prior literature only focusing on the announcing segment of the market.

First, instead of assessing the impact of number of earnings announcements on the subset of announcing firms, which is a micro-level perspective, we identify the impact of news arrivals on all firms in the market including the vastly larger set of non-announcing firms. Second, by decomposing the number of announcements into industry-related and -unrelated news we show that different types of news arrivals spark investor attention differently, suggesting the importance of categorizing the news into related and unrelated industries.

A potential future area of research identified by our analysis is to investigate what type of investors' attention is distracted or attracted during the earnings announcements. A promising area of future research is to examine the relation between market pricing efficiency and aggregate earnings activity for the set of non-announcing firms.

This paper is the first one exploring the overall roles of the offsetting attraction and distraction influences of earnings announcements in shaping the level of investor attention given to the equity market by market participants. Our findings should be of interest to investors, analysts, security market regulators and researchers.

This paper aims to examine the monitoring role of institutional investors in corporate decision-making by classifying financial institutions based on geographical proximity and investment horizon from 1980 to 2014.

By using unique data sets on firm and institution location and investor horizon measure (Gaspar et al., 2005), the authors categorize institutional investors into six proximity-horizon classifications. This method captures the heterogeneity of investors. The corporate decisions assessed include firm investment, financing, payout policy, misbehavior, takeover defenses and profitability.

Both geographical proximity and investment horizon are directly related to institutional investors' monitoring cost. As a result, the effectiveness of institutional monitoring may vary based on geographical proximity and investment horizon. This paper collectively examines both dimensions of financial institutions and provides evidence that institutional investors present different preferences for corporate policies. Given stronger information advantage, both local and nonlocal investors that are long-term oriented fulfill better roles in monitoring corporate decisions but from different perspectives.

Different from previous studies that treat institutional investors homogeneously, this paper provides empirical support that investors are indeed different in influencing firm policies.

To the authors’ best knowledge, this is the first study that classifies investors based on two dimensions, geographical proximity and investment horizon, and examines their joint effects on corporate policies. This proximity-horizon classification allows the authors to better disentangle the effects of institutional ownership structure on the monitoring outcomes.