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Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

The purpose of this study is to examine the impact of firm environmental, social and governance (ESG) rating scores on market perception and stock behavior from 2017 to 2021 while controlling for COVID-19 severity score.

The authors used panel regression models with robust standard errors based on cross-country and cross-industry sample of 1,324 ESG firms from 25 emerging countries across four regions. Four separate regression analyses are used. Hausman test is used to determine whether fixed-effect (FE) or random-effect approaches should be used in regression models. Lagrange multiplier test is used to test for time FEs, and F-test for individual effects to choose between pooled ordinary least squares model and FE. Two-unit root tests are conducted to check stationarity. Heteroskedasticity and serial correlation were controlled through a robust covariance matrix estimation.

The authors provide evidence that the stakeholder theory persists in emerging countries. Overall, the results suggest that firms’ stock behavior is positively associated with the level of environmental and social performance in the region. However, the results do not provide empirical evidence to support the link between ESG performance and stock market perception proxied by the price-to-sales ratio. The results suggest that Refinitiv and Bloomberg ESG rating scores have a positive impact on stock performance in emerging markets, albeit the Bloomberg rating score is insignificant.

Favorable impact of environmental and social performance on stock performance suggests that policymakers should take initiatives to raise awareness toward investments in ESG projects. Evidence shows that ESG stock performance in emerging markets does not insulate firms from the COVID-19 severity. Furthermore, this study highlights the inconsistency in calculating the ESG ratings, therefore, a more standardized approach is recommended to support investors seeking sustainable investments.

The findings have social implications for investors with proenvironmental preferences and nonpecuniary motives for ethical investments. Asset fund managers should develop ESG investment strategies to promote investor preferences that are linked to the proenvironmental and prosocial attitudes by increasing their investments in stocks of firms that behave ethically and support the environment. Furthermore, the findings show that investors pay a price for ethical and socially responsible investments as they are evaluating the environmental and social activities, hence, the firm ESG profile influences equity valuation and risk assessment.

The study extends the literature and provides evidence from the unique setting of emerging markets by analyzing the relationship between ESG rating scores and the COVID-19 severity scores on one hand, and stock behavior and market perception on the other.

This article provides the first empirical study on the effects of the COVID-19 pandemic on sustainability reporting in US financial institutions using institutional, stakeholder and legitimacy theories.

The study used the independent sample t-test and Mann–Whitney U test throughout as well as OLS, random effects, fixed effects and heteroskedasticity corrected model to test the impact of the COVID-19 pandemic on sustainability reporting in the US financial sector. A sample from all listed US financial firms was used after controlling for both the Refinitiv Eikon sector classification and the NAICS sector classification.

Using U Mann–Whitney test and independent sample t-test the study revealed that the average ESG score for the pre-COVID19 period is 53% compared with 62.3% for the COVID-19 period, indicating that the sustainability reporting during COVID-19 is much higher compared with the pre-pandemic period. The findings of regression analysis also confirm that the US financial companies increased their sustainability reporting during the COVID-19 pandemic.

This study is an early attempt to look at how the COVID-19 epidemic has affected financial reporting procedures, although it is focused only on one area and other entity-related factors like stock market implications, company governance, internal audit practice, etc could have been considered.

This research offers useful recommendations for policymakers to create standards for regulators on the significance of raising sustainability awareness. The findings are crucial for accounting regulators as they work to implement COVID-19 and enforce required integrated reporting rules and regulations.

The study provides the first empirical evidence on the impact of the COVID-19 pandemic on sustainability reporting, by examining how US financial institutions approach the topic of sustainability during the COVID-19 pandemic and assessing the pandemic's current consequences on sustainability.

In the research of stock market efficiency, it is argued that the stock market moves randomly and absorbs all the available information. As a result, it is quite impossible to make predictions about the possible future movement by the investors. But literatures have detected certain calendar anomalies where a day(s) in a week or month(s) in a year or a particular event in a year becomes conducive for investors to earn more than the normal. Hence, the purpose of this study is to find out the month of the year effect in the Indian stock market.

In this study, daily time series data of Sensex and Nifty from 1996 to 2021 is used. The study uses month dummies to capture the effect. Different variants of generalised autoregressive conditional heteroskedasticity (GARCH) models, both symmetric and asymmetric, are used in the study to model the conditional volatility in the presence month effect.

This study found the September effect in the return series of both the stock market. Apart from that, asymmetric GARCH models are found to be the best fit model to estimate conditional volatility.

This study is an endeavour to study month of the year effect in the Indian context. This research will provide valuable insight for studying the different calendar anomalies.

This study aims to examine the effect of foreign direct investment (FDI) inflows on tax revenue in 34 developed and developing countries from 2006 to 2020.

Feasible generalised least squares (FGLS), a dynamic panel of a two-step system generalised method of moments (GMM) system and a pool mean group (PMG) panel autoregressive distributed lag (ARDL) approach were used to compare the developed and developing countries. Basic estimators were used as pre-estimators and diagnostic tests were used to increase robustness.

The FGLS, a two-step system of GMM, PMG–ARDL estimator’s results showed that there was a significant negative long and positive short-term in most countries relationship between FDI inflows and tax revenue in developed countries. This study concluded that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue. Meanwhile, there was a significant positive long and negative short-term relationship between FDI inflows and tax revenue in the developing countries. The developing countries sought to attract FDI that could be used to create job opportunities and transfer technology to simultaneously develop infrastructure and impose a tax policy that would achieve high tax revenue.

The present study sheds light on the effect of FDI on tax revenue and compares developed and developing countries through the design and implementation of policies to create jobs, transfer technology and attain economic growth in order to assure foreign investors that they would gain continuous high profits from their investments.

The purpose of this study is to observe the practice of integrated reporting (IR) and investigate the impact of board characteristics on IR in three South Asian economies: Bangladesh, India and Sri Lanka.

The study uses the content analysis approach to measure the integrated reporting index (IRI) based on a structured checklist. To examine the impact of board characteristics (board size, board independence and gender diversity) on IRI, a multivariate analysis using pooled ordinary least square with panel-corrected standard error (PCSE) model has been conducted.

The content analysis findings show that the disclosure practice of IR is highest in India, followed by Sri Lanka and Bangladesh. The regression result indicates that all the proxies of board characteristics have a positive and significant impact on IRI.

The study’s outcomes may not be generalised for every region due to the differences in institutional contexts.

The findings of this study will assist the policymakers in understanding the importance of effective boards in enhancing the IR practice in their respective countries where the adoption of IR is still a voluntary requirement.

To the best of the authors’ knowledge, this is the first study in the field of existing literature to conduct a comparative analysis of IR practice among three South Asian countries. It shows how an effective board improves IR practice using a broader institutional context by underpinning the agency theory and legitimacy theory.

Most research on tax evasion focused on microeconomic variables revolving around perceptions and decisions of individual taxpayers. However, a new wave of research is now investigating the role of macroeconomic variables in inducing tax evasion. This study adds to the limited studies in this new direction of research. Previous studies found that inflation, low gross domestic product (GDP) growth and gross fixed capital formation causes recession, increases unemployment, raise interest rates, hurts both domestic and foreign direct investments. This study examined the relationship between these variables and estimated tax evasion in Sub-Saharan Africa.

The study adopts a correlation research design with 2,300 data points collected from 23 countries in Sub-Saharan Africa. Specifically, tax to GDP ratio, gross fixed capital formation per GDP and the GDP annual growth report from each country for the period 2011–2020 was retrieved. Generalised least square regression technique was employed to analyse the data due to the presence of heteroskedasticity in the model and random effect was utilized based on the Hausman test. To avoid misspecification and biased result; therefore, all relevant test was conducted including the multicollinearity test.

The results indicate that GDP annual growth and gross fixed capital formation have a significant negative impact on estimated tax evasion in Sub-Saharan Africa. The findings further indicate a negative but insignificant relationship between inflation and estimated tax evasion in Sub-Saharan Africa. The study concludes that both GDP annual growth rate and gross fixed capital formation negatively influence estimated tax evasion and the policy implications in the African continent were discussed.

The new findings on the effects of GDP annual growth, growth fixed capital formation and inflation on estimated tax evasion provide novel knowledge that is currently lacking in the current literature, specifically Sub-Saharan African continent.

This paper aims to examine the dynamic conditional correlation (DCC) and hedging ratios between Dow Jones markets and oil, gold and bitcoin. Using daily data, including the COVID-19 pandemic and the Russia–Ukraine war. We employ the DCC-generalized autoregressive conditional heteroskedasticity (GARCH) and asymmetric DCC (ADCC)-GARCH models.

DCC-GARCH and ADCC-GARCH models.

The most of DCCs among market pairs are positive during COVID-19 period, implying the existence of volatility spillovers (Contagion-effects). This implies the lack of additional economic gains of diversification. So, COVID-19 represents a systematic risk that resists diversification. However, during the Russia–Ukraine war the DCCs are negative for most pairs that include Oil and Gold, implying investors may benefit from portfolio-diversification. Our hedging analysis carries significant implications for investors seeking higher returns while hedging their Dow Jones portfolios: keeping their portfolios unhedged is better than hedging them. This is because Islamic stocks have the ability to mitigate risks.

Our paper may make a valuable contribution to the existing literature by examining the hedging of financial assets, including both conventional and Islamic assets, during periods of stability and crisis, such as the COVID-19 pandemic and the Russia–Ukraine war.

This study aims to analyse the intellectual property rights (INPR), foreign direct investment (FDI) inflows and technological exports of 32 developing and developed countries for the period of 2006–2020.

Diagnostic tests were used to confirm the panel least squares, fixed effect, random effect, feasible general least squares, dynamic ordinary least squares and fully modified ordinary least squares estimator results as well as to increase the robustness.

According to the findings for the developing countries, trademark, patent and industrial design applications, each had a significant positive long-run effect on FDI inflows. In addition, there was a significant positive long-run relationship between patent applications and medium- and high-technology exports. Meanwhile, trademark and industrial design applications had a significant negative long-term effect on medium- and high-technology exports. In developed countries, patent and industrial design applications each have a significant negative long-term on medium- and high-technology exports. Furthermore, patent and trademark applications each had a significant negative long-run effect on FDI inflows.

This study contributes significantly to the focus that host countries evaluate the technology gaps between domestic and foreign investors at different industry levels to select the best INPR rules and innovation process by increasing international cooperation. Furthermore, the host countries should follow the structure–conduct–performance paradigm based on analysis of the market structure, strategic firms and industrial dynamics systems.

The study attempts to examine the impact of mandatory corporate social responsibility (CSR) spending and inclusion of firms into the environment, social and governance (ESG) index of BSE India on the performance of firms constituting firms under the Bombay Stock Exchange (BSE) 100 Index.

The stock prices of the firms were collected from the official website of BSE India for a total of 32 firms and the System Generalized Method of Moments (GMM) model was utilized for analyzing the data for the present study.

The study found that the investors in the Indian market do consider the CSR spending and ESG listing as a factor while framing the investment strategy; however, ESG listing is least preferred. Among the other variables, AGE, DPS, EPS and BVPS have a significant positive bearing on the firm's performance, while SIZE has a significant negative impact on the firm's performance.

Further investigation is needed to understand the factors that influence investment decision-making, including why investors tend to overlook CSR and environmental protection. Future research can identify ways to increase the importance of these factors in investment decision-making. Future research can explore the long-term impact of investing in socially responsible companies, including whether such investments lead to better long-term performance.

There is a need for increased awareness of the importance of CSR among investors. Educational programs and campaigns can be used to inform investors about the potential benefits of considering social responsibility factors in investment decision-making. Companies that prioritize CSR and environmental protection should distinguish themselves from competitors in the eyes of investors. This can lead to higher investment and potentially higher returns for these companies.

Since mandatory CSR expenditure and the launch of the ESG index by the BSE have been introduced in India recently, hardly any study in India has examined the impact of the same on the firm's performance.