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This paper investigates the role of economic disagreement in the cross-sectional pricing of individual stocks. Economic disagreement is quantified with ex ante measures of cross-sectional dispersion in economic forecasts from the Survey of Professional Forecasters (SPF), determining the degree of disagreement among professional forecasters over changes in economic fundamentals.

The authors introduce a broad index of economic disagreement based on the innovations in the cross-sectional dispersion of economic forecasts for output, inflation and unemployment so that the index is a shock measure that captures different aspects of disagreement over economic fundamentals and also reflects unexpected news or surprise about the state of the aggregate economy. After building the broad index of economic disagreement, the authors test out-of-sample performance of the index in predicting the cross-sectional variation in future stock returns.

Univariate portfolio analyses indicate that decile portfolios that are long in stocks with the lowest disagreement beta and short in stocks with the highest disagreement beta yield a risk-adjusted annual return of 7.2%. The results remain robust after controlling for well-known pricing effects. The results are consistent with a preference-based explanation that ambiguity-averse investors demand extra compensation to hold stocks with high disagreement risk and the investors are willing to pay high prices for stocks with large hedging benefits. The results also support the mispricing hypothesis that the high disagreement beta provides an indirect way to measure dispersed opinion and overpricing.

Most literature measures disagreement about individual stocks with the standard deviation of earnings forecasts made by financial analysts and examines the cross-sectional relation between this measure and individual stock returns. Unlike prior studies, the authors focus on disagreement about the economy instead of disagreement about earnings growth. The authors' argument is that disagreement about the economy is a major factor that would explain disagreement about stock fundamentals. The authors find that disagreement in economic forecasts does indeed have a significant impact on the cross-sectional pricing of individual stocks.

This study aims to examine the effects of product market competition (PMC) on analysts’ earnings forecast attributes, particularly forecast accuracy and dispersion. The authors also investigate whether investor protection moderates the relationship between PMC and forecast attributes.

The sample covers 49,578 firm-year observations from 38 countries. This study uses an ordinary least squares regression, a Heckman two-stage regression and an instrumental two-stage least squares regression.

This study finds that PMC is associated with higher forecast accuracy and lower dispersion. The results also show that investor protection enhances the effect of PMC on forecast accuracy and dispersion. These findings imply that countries with strong investor protection have a better information environment, as exhibited by the stronger relationship between PMC and analysts’ forecast properties.

The findings highlight the importance of strong governance mechanisms in both the country and industry environments. Policymakers, including government agencies and financial regulators, can leverage these insights to formulate regulations that promote competition, ensure investor protection and facilitate informed investment decisions.

This study advances our understanding of how PMC affects analysts’ earnings forecast attributes. In addition, it pioneers evidence of the moderating role of investor protection in the relationship between PMC and forecast attributes.

The study examines the effect of increased Economic Policy uncertainty on analyst optimism in the Indian market. The study also explores whether the SEBI Research Analyst Regulation, 2014, has effectively contained the optimistic nature of analysts.

The study is based on firms in the Indian market. The sample period is 2003–2020. It runs a linear panel regression to measure the impact of Economic Policy uncertainty on the optimism level of analysts' forecasts and recommendations, controlling for firm fixed effects. Further, the impact of the SEBI Research Analyst Regulation, 2014, has been assessed with the help of the difference-in-difference approach.

The Economic Policy uncertainty is significantly and positively related to the analyst optimism, reflected in the forecast bias and recommendation in the Indian context. The experience of analysts and the age of the firm positively drive optimism. However, introducing the Research Analyst Regulation by SEBI led to a decline in analyst optimism. The regulation decoupled the analysts' compensation from brokerage service transactions. Thus, the results suggest that the regulation has effectively curbed the incentive to produce optimistic output.

This is the first study in the Indian market to assess the impact of uncertainty on analyst output. It also investigates the effectiveness of the first analyst-specific regulation in India, i.e. The Research Analyst Regulation, 2014.

In this study, the authors investigate if analysts, as knowledgeable information intermediaries, can correctly identify bank corporate social responsibility (CSR) activities and can reliably transmit that information to investors. Hence, the authors specifically explore if analysts perceive and behave differentially in the presence of genuine bank CSR activities (strengths). The authors also analyze if financial markets differentially assess bank CSR strengths. The authors further explore the viability of focusing on analyst and financial markets to validate genuine bank CSR strengths.

The authors use COMPUSTAT and CRSP for firm and financial data, I/B/E/S for analyst reporting data and MCSI Research KLD for CSR data. The sample consists of 329 distinct banks and 2,525 bank-year observations from 2003 to 2016. The primary CSR score is the total number of CSR strengths less the total number of CSR concerns, across six of the seven dimensions for each firm in each year of the sample (Adjusted CSR Score). In addition, the authors estimate all the analyses with dis-aggregated measures of total CSR strengths and total CSR concerns (Adjusted Total Strength Score).

The authors find that analysts correctly distinguish and construe bank CSR strengths from CSR concerns. Specifically, bank CSR strengths increase analyst following and forecast accuracy, while decreasing analyst forecast dispersion. The authors further find that bank CSR strengths increase bank market returns. These results are reversed for bank CSR concerns. Additionally, the authors demonstrate that this method using knowledgeable intermediaries can help validate bank CSR strengths.

The sample is limited to US banks and financial markets. The regulatory and information environment is likely to be different from global or emerging markets. However, since banks in many countries aspire to emulate the US banks, these results would be a precursor of banking sectors conditions in emerging markets. Additionally, the availability of data limits the sample to a period that ends in 2016. To the extent that the importance of ESG and CSR concerns has increased in the intervening time, the results may not accurately reflect the current state of the market.

This investigation benefits researchers, customers, banking executives, regulators and activist groups. First, the authors show that in addition to customers, analysts and the financial markets appreciate bank CSR strengths. Second, despite sophisticated financial reporting by banks, analysts correctly distinguish and construe bank CSR strengths. Third, the authors demonstrate a method for bank marketing researchers to validate genuine bank CSR activity, as well as provide additional support for customer related bank CSR outcomes. Fourth, the findings highlight the importance for banks to have high-quality CSR reporting. This might be especially helpful to a bank rebuilding its reputation after a CSR failure. Finally, this investigation using US banks could serve as a precursor for future bank CSR research and help develop CSR reporting guidelines for banks in emerging economies.

This investigation benefits researchers, customers, banking executives, regulators and activist groups.

This investigation benefits researchers, customers, banking executives, regulators and activist groups. First, the authors show that in addition to customers, analysts and the financial market appreciates bank CSR strengths. Second, despite sophisticated financial reporting by banks, analysts correctly distinguish and construe bank CSR strengths. Third, the authors demonstrate a method for bank marketing researchers to validate genuine bank CSR activity, as well as provide additional support for customer related bank CSR outcomes. Fourth, the findings highlight the importance for banks to have high-quality CSR reporting. This might be especially helpful to a bank rebuilding its reputation after a CSR failure. Finally, this investigation using US banks could serve as a precursor for future bank CSR research and help develop CSR reporting guidelines for banks in emerging economies.

This paper aims to examine the extent to which sell-side analysts efficiently incorporate firms’ corporate social responsibility (CSR) activities into their earnings forecasts. In addition, this paper also investigate the CSR information efficiency of analysts vis-à-vis that of investors.

This paper measures CSR activities by using CSR strength and CSR concern scores from the Morgan Stanley Capital International Environmental, Social and Governance database. This paper uses analysts’ earnings forecast errors and dispersion as proxies for their information efficiency. To compare the CSR information efficiency of analysts to that of investors, this paper uses the Vt/Pt ratio, which is the equity value estimates inferred from analysts’ earnings forecasts (a proxy for analysts’ CSR information efficiency) to the stock price of the focal company (a proxy for investors’ CSR information efficiency).

The regression analysis indicates that analysts’ earnings forecasts are optimistically biased and more dispersed for firms with positive CSR activities. The paper also finds that analysts’ forecasts are more optimistically biased than investors in interpreting CSR activities.

The lack of standardized protocols in CSR reporting and activities has raised the risk of mispricing by analysts, threatening the stability of sustainable investments. This paper suggests that regulators and standard-setters should establish a uniform framework governing firms’ CSR activities, along with their reporting and measurement, to ensure more consistent and reliable evaluations of CSR practices.

Analysts’ mispricing of CSR activities may distort sustainable investing, as it can overly focus on the positive impacts of stakeholder theory, overlooking agency theory’s warnings about managerial self-interest. Investors need to assess CSR efforts with a dual perspective, acknowledging their societal value but also examining their alignment with shareholder interests.

To the best of the authors’ knowledge, this research is the first to assess the efficiency of analysts versus investors in processing CSR information amidst growing sustainable investment interests. Furthermore, building on Dhaliwal et al. (2012), which found that voluntary CSR disclosures correlate with more accurate analyst forecasts, this research provides fresh perspectives on the evolving nature of how analysts assimilate CSR information over time.

Both the SEC (Securities and Exchange Commission) and the popular press have routinely criticized firms for the complexity of their financial disclosures. This study aims to investigate how financial analysts respond to the tone complexity of firm disclosures.

Using approximately 20,000 earnings conference call transcripts of S&P 1,500 firms between 2005 and 2015, the authors first calculate the abnormal negative tone, the measure of tone complexity; then use such tone measure in econometric models to examine analyst forecast behavior. The authors also test the robustness of the results under different model specifications, tone word lists and alternative tone measure calculations.

Consistent with the notion that analysts respond to the information demand from investors and incur more costs and effort to analyze firm disclosure when the tone is more complex, the authors find that higher tone complexity is positively and significantly associated with more analyst following, longer report duration, more forecast revisions, larger forecast error and larger forecast dispersion. In addition, the authors find that tone complexity has a long-term impact on analyst following but has a limited long-term impact on analyst report duration, analyst revision, forecast error and dispersion.

This study complements existing literature by highlighting the information role of financial analysts and by providing evidence that analysts incorporate the management tone disclosed during conference calls to adjust their forecasting behaviors. The results can be used by policymakers as evidence and support for further improving firm communication from a new dimension of disclosure tone.

This study aims to examine the mediating role played by corporate governance (CG) in the relationship between corporate social responsibility (CSR) and analyst forecast quality.

The authors raise three specific questions: Does CG play a mediating role in the relationship between CSR and analyst forecast quality? If so, is such mediation effect of CG reduced for firms with weak governance? Do firms with superior CSR performance experience higher analyst forecast quality through the mediation effect of CG?

The present results suggest that CG serves as a partial mediator that facilitates CSR’s positive influence on analyst forecast quality. However, further analyses show that in firms with a low governance score, CG does not have a mediation effect. Conversely, the authors find that firms with superior CSR performance have higher forecast quality through the mediation effect of CG. The authors also find that the mediation effect of CG is more pronounced for the environmental component than for the social component of CSR.

To the best of the authors’ knowledge, this study is the first to investigate the role of CG as a mediator between CSR and analyst forecast quality and to reveal that the strength of this effect varies depending on firms’ CG level and CSR commitment.

This paper aims to investigate the relation between audit firms’ switch to limited liability partnership (LLP) from limited liability company (LLC) and client firms’ earnings comparability. If LLP auditors, who have a higher liability exposure than LLC auditors, are more consistent in implementing generally accepted accounting principles and executing firm-wide audit methodologies, client firms’ earnings comparability will increase.

Using data from China, the authors examine whether client firm-pairs of LLP auditors have higher earnings comparability than client firm-pairs of LLC auditors. The authors also perform cross-sectional tests to shed light on the mechanisms through which auditors’ litigation exposure affects client firms’ comparability.

The authors find that firm-pairs in which both firms are audited by LLP auditors exhibit higher earnings comparability than other firm-pairs. This result is stronger when client firms are audited by the same auditor, when client firms are audited by the top 10 auditors and when the auditors are less dependent on the client firms. The authors also document that firm-pairs in which both firms are audited by LLP auditors have lower average analyst earnings forecast error and forecast dispersion.

To the best of the author’s knowledge, this study is the first to examine the relation between auditor’s litigation exposure and client firms’ earnings comparability. It also extends the literature on audit firm organizational form and audit quality.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

The purpose of this study is to examine the transmission of volatility between business confidence index and stock market indices in Greece. The country remains the riskiest project in European Union (EU) and previous studies fail to reach an accurate conclusion regarding the direction of this transmission.

The study covers the period from January 2013 to August 2022 in monthly basis where important economic events occur. Considering that these economic events derive strong volatility moments, the authors adopt a new methodology that measures the transmission of volatility with higher precision. This is the generalized spillover analysis by Diebold and Yilmaz (2009, 2012).

The results indicate that Business Confidence Index (BCI) is the main receiver of volatility spillovers in Greece under all aspects of the used methodology. The specificity of the results shows that business activity through a green growth model is what drives investor confidence and then their activities.

Although a handful of studies have considered the transmission of volatility between BCI and stock market indices, this study contributes in several ways. This study focuses on one country (Greece), avoiding the dispersion of the results from the examination of the relationship in several countries. The used country remains the riskiest project in EU even nowadays, while other studies fail to confirm the main direction of volatility spillovers from business confidence to stock returns. This study covers a period that is ignored by previous studies and includes important economic events. In addition, considering that these economic events derive strong volatility moments, a new methodology is adopted in this field of research that measures the transmission of volatility with higher accuracy.