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This paper aims to conduct a comparative analysis of the impact of market uncertainty on the degree of accuracy and bias of analysts' earnings forecasts versus four model-based earnings forecasts.

The study employs panel regression analysis on a sample of Egyptian listed companies from 2005 to 2022 to examine the impact of market uncertainty on the accuracy and bias of each type of earnings forecast.

The empirical analysis reveals that market uncertainty significantly affects analysts’ earnings forecast accuracy and bias, while model-based earnings forecasts are less affected. Furthermore, the Earnings Persistence and Residual Income model-based earnings were found to be superior in terms of exhibiting the least susceptibility to the impact of market uncertainty on their forecast accuracy and biasness levels, respectively.

The findings have important implications for stakeholders within the financial realm, including investors, financial analysts, corporate executives and portfolio managers. They emphasize the importance of considering market uncertainty when formulating earnings forecasts, while concurrently highlighting the potential benefits of using alternative forecasting methods.

To our knowledge, the influence of market uncertainty on analysts' earnings forecast accuracy and bias in the MENA region, particularly in the Egyptian market, remains unexplored in existing research. Additionally, this paper contributes to the existing literature by pinpointing the forecasting method, specifically distinguishing between analysts-based and model-based approaches, whose predictive quality is less adversely impacted by market uncertainty in an emerging market.

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 investigate whether the cash flow forecasts (CFF) of analysts can disseminate valuable information to the information environments of companies.

The author uses empirical archival methodology to conduct differences-in-difference analyses.

It is found that information asymmetry decreases in the treatment group following the initiation of CFF during the postperiod, which is consistent with the hypothesis of this paper.

To the best of the author’s knowledge, this study is the first among the cash flow forecast studies to demonstrate the usefulness of CFF in the mitigation of information asymmetry, a friction that is widespread in capital markets.

This study aims to examine whether Chinese firms increase their concerns about analysts’ earnings forecasts following the split-share structure reform (SSR) in 2005, which removed trading restrictions on approximately 70% of the shares of listed firms.

Using data from 2002 to 2019, the authors empirically test the association between meeting or beating analysts’ earnings expectations and the implementation of SSR.

The authors find that firms are more inclined to meet analysts’ earnings expectations after the introduction of SSR. Further analysis shows that firms guide analysts to walk their forecasts down by manipulating third-quarter earnings, suggesting enhanced value relevance between analysts’ forecasts and third-quarter earnings management in the postreform period.

The findings reveal an undesirable side effect of SSR and suggest that policymakers and regulators should consider and carefully manage the complex relationships between firms and analysts.

In contrast to prior studies that predominantly focus on the positive effects of the reform, this study reveals the side effects of SSR and provides new evidence on the mechanisms of meeting or beating analysts’ earnings expectations.

This study aims to provide insights into US and Australian analysts' views regarding the relative importance of disclosing the direct method (DM) or indirect method (IM) statement of cash flows and forecasting firm performance.

Evidence is collected from responses to 104 surveys and 52 interviews completed by US and Australian analysts from 2017 to 2022. The survey and interview questions are developed with reference to the literature.

US and Australian analysts believe that the DM format provides incremental benefits compared to the IM for (1) confirming the reliability of earnings; (2) improving earnings confidence; (3) more accurate ex ante forecasts of operating cash flow and earnings; and (4) identifying opportunistic accruals manipulation. Analysts view that DM disclosure can lower firm-level cost of equity, although US interviewees more uniformly expect lower costs of equity under DM disclosure when firms yield low earnings quality. DM disclosure is also more important during unstable economic periods, as proxied by COVID-19.

Limited research currently exists regarding disclosure of the DM or IM and its impact on analysts' forecasting accuracy, earnings quality, economic uncertainty and cost of equity. Previous research has relied on archival research to examine differences between the DM and IM methods and are limited by data availability. Our findings are particularly relevant to the US market with few US firms reporting the DM format.

In this study, we examine the influence of a firm’s environmental, social, and governance (ESG) performance on analysts’ stock recommendations and earnings forecast accuracy in the Chinese context.

We take a textual analysis approach to analyst research reports issued between 2010 and 2019, and differentiate between two distinct analyst categories: “sustainability analysts,” which refer to those more inclined to incorporate ESG information into their analyses, and “other analysts.”

Our evidence indicates that sustainability analysts tend to be significantly more likely than others to provide positive stock recommendations and demonstrate enhanced accuracy in forecasting earnings for companies with superior ESG performance. Our additional analyses reveal that this finding is particularly prominent for analysts who graduated from institutions emphasizing the protection of the environment, those recognized as star analysts, those affiliated with ESG-oriented brokerages, and forecasts made by analysts in the later part of the sample period. Our findings further indicate that sustainability analysts exhibit a more pronounced negative response when confronted with a negative ESG event.

In general, the evidence from this study reveals the interplay between ESG factors and analyst behavior, offering valuable implications for both financial analysts and sustainable investment strategies.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.

This study examines the connection between investor sentiment and corporate innovation in the United States, considering the magnitude of corporate information asymmetry, the implied cost of capital and the financial constraints.

The authors employ a two-step GMM framework to examine the hypotheses of this study by utilizing annual data from 2001 to 2021 for US corporations.

The empirical evidence demonstrates a significant impact of investor sentiment on corporate innovation for firms with a lower information asymmetry and implied cost of capital than those with a higher information asymmetry and cost of capital. Although the financial constraint channel remained positive, it had little impact on the innovations of US corporations. Overall, the study's results show that companies make more valuable and high-quality patents when investors are optimistic.

This research has policy implications for all managers, investors, analysts and state officers, particularly in the USA and other developed countries. Managers and investors of all types should predict the role of corporate innovation in increasing shareholder wealth.

To the authors' knowledge, this is the first study to examine the relationship between investor sentiment and corporate innovation in the United States, considering the extent of corporate information asymmetry, the implied cost of capital and the financial limitations. The study's empirical findings uniquely contribute to the existing literature on corporate innovation and investor sentiment in the current context.

This study aims to examine stock price synchronicity during the COVID-19 crisis using 32,452 firms from 61 countries. This paper explores the impact of government effectiveness on synchronicity while distinguishing between developed and emerging markets.

The research analysis employs ordinary OLS pooled regression analysis.

This paper presents worldwide evidence that stock price synchronicity was significantly higher during February and March 2020. This paper shows that synchronicity increased with the intensity of the crisis. In addition, the government's role reduced the COVID-19 impact on synchronicity, which was stronger in developed markets than in emerging markets.

The novelty of the study lies in documenting the impact of the COVID-19 pandemic on stock price synchronicity. The findings add to a deeper understanding of market behavior amid significant disruptive shocks.

This study aims to examine the extent to which information asymmetry affects investment efficiency and whether the presence of blockholders moderate this relationship.

We employ the data of firms listed on the Malaysian stock exchange for the period 2010–2018, to compose our sample. Our final sample includes the 100 largest non-financial firms based on market capitalization. Collectively, these 100 companies contribute 84.2% to the total market capitalization (MYR 1,730bn) which is representative of the whole market. The ordinary least squares regressions were used as the main estimation technique. The system generalized method of moments, two-stage least squares and propensity score matching were also used, to address potential endogeneity concerns.

We document a positively significant association of information asymmetry with investment inefficiency. These results imply that information asymmetry reduces investment efficiency and enhances sub-optimal investments. We also document that blockholders negatively moderate the relationship of information asymmetry with investment inefficiency. Further analyses show that investment inefficiency is higher in low-growth firms than in high-growth firms because of higher information asymmetry.

We focus on Malaysia, which is a predominantly common-law Anglo-Saxon country. Graff (2008) documented that the investors are treated differently across legal systems and there are differences between the continental European and Anglo-Saxon countries. La Porta et al. (1999) documented that investors tend to have more legal protection in Anglo-Saxon countries. Therefore, our results may not be generalized to countries with different legal systems.

An important implication of our findings is that stakeholders may encourage the presence of blockholders and give them a voice to weaken the positive relationship between information asymmetry and investment inefficiency.

This study contributes to the contingency literature by investigating the moderating effect of an important governance mechanism, i.e. the presence of blockholders on information asymmetry-investment efficiency nexus. Despite being important, this moderating effect has been largely overlooked in the literature. Our study contributes by providing an understanding of how blockholders can influence investment decisions, offering insights for academics, investors and policymakers focused on improving the efficacy of investment decisions and governance structure.