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This article analyzes the hypothesis that analysts issue higher long-term earnings growth (LTG) forecasts following a market-wide investor sentiment.

This study analyzed 193 publicly traded Brazilian firms listed on B3 (Brasil, Bolsa, Balcão), totaling 2,291 observations. To address the potential selection bias resulting from analysts' preference for more liquid firms, this study used the Heckman model in the analysis with samples with only one analyst and the entire sample. The study also applied other robustness tests to ensure the reliability of the findings.

The results suggest that market-wide investor sentiment influences LTG when the firm's stocks are difficult to value. Market optimism did not reflect five-year profit growth after the forecast issue, suggesting lower forecast accuracy during high investor sentiment values.

Volatile-earnings firms have relevant implications in LTG forecasts during bullish moments. According to the study’s evidence, investors' decisions and policymakers' and regulators' rules should consider analysts' expertise as independent information when considering LTG as input for valuation models, even under market optimism.

This paper contributes to the literature on the influence of investor sentiment on analysts' forecasts by incorporating two crucial elements in the discussion: the scenario free from herding behavior, as usually only one analyst issues LGT forecast for Brazilian firms, and the analysis of research hypotheses incorporates the difficulty of pricing a firm given the uncertainty of its earnings as an explanation to bullish forecast.

This study investigates the diversification benefits of multiple cryptocurrencies and their usefulness as investment assets, individually or combined, in enhancing the performance of a well-diversified portfolio of traditional assets before and during the pandemic COVID-19.

This paper uses two optimization techniques, namely the mean-variance and the maximum Sharpe ratio. The naïve diversification rules are used for comparison. Besides, the Sharpe and the Sortino ratios are used as performance measures.

The results show that cryptocurrencies diversification benefits occur more during the COVID-19 pandemic rather than before it, with the maximum Sharpe ratio portfolio presenting its highest performance. Furthermore, the results suggest that, during COVID-19, the diversification benefits are slightly better when using a combination of cryptocurrencies to an already well-diversified portfolio of traditional assets rather than individual ones. This serves to improve the performance of the maximum Sharpe ratio portfolio, and to some extent, the naïve portfolio. Yet, cryptocurrencies, whether added individually or combined to a well-diversified portfolio of traditional assets, don't fit in the minimum variance portfolio. Besides, the efficient frontier during COVID-19 pandemic dominates the one before COVID-19 pandemic, giving the investor a better risk-return trade-off.

To the best of the author's knowledge, this is the first study that examines the diversification benefits of multiple cryptocurrencies both as individual investments and as additional asset classes, before and during COVID-19 pandemic. The paper covers all analyses performed separately in previous studies, which brings new evidence regarding the potential for cryptocurrencies in portfolio diversification under different portfolio strategies.

The aim of this study is to examine the nature and determinants of stock market integration between India and other Asia–Pacific countries (Malaysia, Hong Kong, Singapore, South Korea, Japan, China, Indonesia, the Philippines, Thailand and Taiwan) over the period 1991–2021.

Unit root tests, the dynamic conditional correlation-Glosten Jagannathan and Runkle-generalized autoregressive conditional heteroscedasticity (DCC-GJR-GARCH), pooled ordinary least squares (OLS) regression and random effects models are employed for the analysis.

The empirical results show that the DCC between each pair of sample countries is less than 0.5, indicating weak ties between the pairs of sample countries. Also, the DCC between India and other Asia–Pacific stock markets is positive and low, implying low level of integration. The correlation between India and China stock markets is found to be the highest, implying significant level of integration. The main reason for it would be strong economic linkages and bilateral trade relationship between India and China. Moreover, gross domestic product (GDP), interest rate (IR), consumer price index (CPI)-inflation and money supply (MS) differentials are the major driver of stock market integration between India and other Asia–Pacific countries.

The findings of the study have important implications for investors, portfolio managers and policymakers. It is found that the DCC between India and other Asia–Pacific countries (considered in the study) except China is low, which indicates weak ties between the pairs of sample countries. This implies that the Indian stock market provides good investment opportunities for foreign investors. Also, investors and portfolio managers can attain more diversified benefits and can minimize country risk by investing across Asia–Pacific countries. Further, knowledge about the factors that integrate the Indian stock market with the other Asia–Pacific stock markets will help policymakers frame suitable economic and financial stabilization policies.

This study contributes to the extant literature: first, by examining the linkages of Indian stock market with other Asia–Pacific countries; second, although previous studies confirmed the existence of linkages among the various stock markets, few researchers pay attention to the factors driving the process of stock market integration. This study provides additional evidence by examining the significant macroeconomic factors driving the process of such integration in the Asia–Pacific region considered under the study.

This study seeks to investigate role of the coronavirus disease 2019 (COVID-19) pandemic on clean energy stocks for the United States for the period 21 January 2020–16 August 2021.

At the empirical stage, the Fourier-augmented vector autoregression approach has been used.

According to the empirical results, the response of the clean energy stocks to the feverish sentiment, lockdown stringency, oil volatility, dirty assets, and monetary policy dies out within a short period of time. In addition, the authors find that there is a unidirectional causality from the feverish sentiment index and the lockdown stringency index to the clean energy stock returns; and from the monetary policy to the clean energy stocks. At the same time, there is a bidirectional causality between the lockdown stringency index and the feverish sentiment index. The empirical findings can be helpful to both practitioners and policy-makers.

Among the COVID-19 variables used in this study is a new feverish sentiment index, which has been constructed using principal component analysis. The importance of the feverish sentiment index is that it allows us to examine the impact of the aggregate level of fear in the economy on clean energy stocks.

This study examined the impact of the Glasgow Climate Pact on the abnormal returns of global clean energy stocks. Further, this study examines which country-specific and firm-specific variables drive the cumulative abnormal returns (CARs) of clean energy stocks.

The authors used the event study method and cross-sectional multivariate regression model. The clean energy stocks in this study are limited to 81 constituent firms of the S&P Global Clean Energy Index across 17 nations. The final sample includes 80 firms and the sample period ranges from January 26, 2021, to December 07, 2021.

The study finds that the Glasgow Climate Pact negatively affects the stock returns of clean energy firms. Moreover, the climate change performance index (CCPI) positively impacts cumulative abnormal returns (CARs), signifying that clean energy investors react positively to firms in nations with good CCPI scores. The environmental, social and governance (ESG) measure for the shorter window (−1, +1) exhibited a negative relationship with CARs. The firm-specific variables (BTM, stock liquidity, size and past returns) exhibit a negative relationship with CARs in different event windows.

The authors use the CCPI as a proxy for the stringency of environmental policies in any nation. The authors extend the existing literature by employing firm-specific variables and supporting previous findings. Their findings have policy implications for clean energy investors, policymakers and other market participants.

Climate risks impact the global financial market, so the findings have implications for global regulatory bodies. Currently, there are bankruptcy cases due to climate risks. Because financial markets must play a critical role in shifting the economy toward a green one, regulators can use the cross-sectional drivers of this study to shape policy. It is also critical for regulators to reduce stock price volatility in the event of the implementation of environmental regulations and improve environmental disclosures by publicly traded companies. Furthermore, governments are interested in researching the effects of environmental regulations to protect stakeholders' interests. These regulations significantly impact emerging markets because they lack the same solid institutional frameworks as developed markets.

The authors provide evidence that firms with better ESG scores and larger firm sizes have experienced fewer abnormal returns, as these firms have stable financial and non-financial fundamentals. This timely study on the ongoing regulatory shift in environmental policy will help investors, policymakers, firms and other stakeholders make relevant decisions.

This study aims to explore the underlying issues of behavioural biases in relation to stock market participation and the challenges of individual investors in Bangladesh. The study identifies behavioural biases affecting individuals’ stock market participation, their circumvention strategies and the importance of financial knowledge in encouraging the participation of individuals in the stock market.

Semi-structured interviews were used in this study to gather information from industry researchers, individual investors, brokers and institutional advisors. Twenty-two experts were contacted, and 13 agreed to participate in the interviews. The study then uses the thematic analysis method to report its findings.

This research shows that investors’ behavioural biases (such as loss aversion, herding, trust, gambler’s fallacy and risk tolerance) are among Bangladesh’s primary drivers of stock market participation. Circumvention strategies (such as poor corporate governance and agency costs) also play a part in individuals’ participation. These influences are in addition to the obvious factors of investment risks, poor infrastructure, poor regulation enforcement and the need for more sufficient investment products.

This study conducted 13 interviews with expert subjects, which is a small sample size. However, the findings achieved saturation and cannot be ignored. Future research should use quantitative or experimental methods with a large sample size to validate the current findings.

This study is pioneering in the Bangladesh stock market, exploring the behavioural biases of investors’ participation in the market. This paper provides valuable insights into investor participation by discovering the underlying behavioural biases that have been continually ignored; these insights may also be relevant in frontier markets in Asian countries.

This paper examines the time-varying efficiency of nine major Middle East and North Africa (MENA) stock markets namely Egypt, Bahrain, UAE, Jordan, Saudi Arabia, Oman, Qatar, Morocco and Tunisia during times of COVID-19 pandemic outbreak and vaccines.

The authors use two econometric approaches: (1) autocorrelation tests including the wild bootstrap automatic variance ratio test, the automatic portmanteau test and the Generalized spectral test, and (2) a non-Bayesian generalized least squares-based time-varying model with statistical inferences.

The results show that the degree of stock market efficiency of Egyptian, Bahraini, Saudi, Moroccan and Tunisian stock markets is influenced by the COVID-19 pandemic crisis. Furthermore, the authors find a tendency toward efficiency in most of the MENA markets after the announcement of the COVID-19's vaccine approval. Finally, the Jordanian, Omani, Qatari and UAE stock markets remain globally efficient during the three sub-periods of the COVID-19 pandemic outbreak.

The results have important implications for asset allocations and financial risk management. Portfolio managers may maximize the benefit of arbitrage opportunities by taking strategic long and short positions in these markets during downward trend periods. Policymakers should implement the action plans and reforms to protect the stock markets from global shocks and ensure the stability of the stock markets.

This study assesses the perception of academics and practitioners of ramifications that may have impacted audit evidence quality during COVID-19 in Egypt.

A questionnaire was collected and designed regarding the factors affecting the quality of audit evidence during the COVID-19 pandemic using a five-point Likert scale, and detailed descriptive statistics and regression analyses were conducted.

The study finds that there is no significant association between social distancing (SD), changing in the economic environment (CEE), time constraint (TC) and stress on audit personnel (SAP) as repercussions of the COVID-19 pandemic with the quality of audit evidence (QAE). The disruption in operational results (DOR), changes in the internal control (CIC) and the stress on client personnel (SCP) significantly affect the quality of audit evidence. Moreover, there is a significant difference between Big and non-Big Four audit firms in terms of changes in economic conditions, internal controls, disruption of operational results and time-constraint variables. The latter has significantly affected the audit evidence quality for both academics and professionals.

Due to the implementation of SD and work-from-home policies, audit firms are highly recommended to invest more in digital programs and to be more adaptable to work-from-home, which policy and enhances the effectiveness and flexibility of communication between auditors and their clients.

This paper is one of the foremost papers that provides empirical evidence for the antecedents or variables that may affect audit quality evidence due to the COVID-19 pandemic.

The objective of this research is to identify the economic, demographic, sanitary and even cultural factors which explain the variability in the cross-section of returns in different markets globally during the first weeks after the outbreak of COVID-19.

Building on the event study methodology and using seemingly unrelated equations, the authors created several indicators on the impact of the pandemic in 75 different markets. Then, and using cross-sectional regressions robust to heteroscedasticity and using an algorithm to select independent variables from more than 30 factors, the authors determine which factors were behind the different stock market reactions to the pandemic.

Higher currency depreciation, inflation, interest rate or government deficit led to higher returns, while higher life expectancy, ageing population, GDP per capita or health spending led to the opposite effect. However, the positive effect of competitiveness and the negative effect of income inequality stand out for their statistical and economic significance.

This research provides a global view of investors' reaction to an extreme and unique event. Using a sample of 75 capital markets and testing the relevance of more than 30 variables from all categories, it is, to the authors' knowledge, the largest and most ambitious study of its kind.

Using a generalized translation operator, this study aims to obtain a generalization of Titchmarsh's theorem for the Laguerre–Bessel transform for functions satisfying the ψ-Laguerre–Bessel–Lipschitz condition in the space L²_α (K), where K=0,+∞×0,+∞[.

The author has employed the results developed by Titchmarsh, of reference number [1].

In this paper, an analogous of Titchmarsh's theorem is established for Laguerre–Bessel transform.

To the best of the authors’ findings, at the time of submission of this paper, the results reported are new and interesting.