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Our study investigates the influence of peer performance on the earnings management decisions within publicly traded Indian companies. There is mixed evidence in the literature, with the impact of peer performance on earnings management in emerging markets being notably underexplored. Additionally, the study explores whether robust corporate governance mechanisms can mitigate earnings management practices. Our study offers policy insights into these areas.

Our study used a longitudinal panel dataset from 2011 to 2020, utilising idiosyncratic returns of peer firms as an external measure of peer performance. This approach is further enhanced by the usage of alternative discretionary accrual metrics, which could be a robust measure for both market leaders and followers.

Our study employs two distinct methods, accrual and real earnings management, to assess earnings management. The findings indicate that peer performance triggers earnings management within peer groups, showcasing managerial opportunism in financial reporting to align with peer achievements. Furthermore, the evidence suggests that robust corporate governance effectively curtails earnings management, especially in industries where peer influence is significant.

Our study offers valuable insights for regulators, highlighting that enhancing the institutional framework with stringent corporate governance mechanisms can effectively reduce earnings management in companies within emerging markets.

The paper is a novel attempt in emerging markets to show that managers engage in opportunistic reporting to align with the performance of their peers and that governance strategies effectively mitigate these practices in such markets.

The economic development of Bangladesh is heavily reliant on the banking industry, yet it faces numerous hurdles, including liquidity issues, capital shortages, non-performing loans, inefficiencies and so on. Therefore, this study investigated the performance and efficiency of scheduled banks (state-owned, private commercial, foreign commercial and specialized banks) operating in Bangladesh.

The research was conducted using secondary data from annual reports of banks. The CAMELS rating system and Data Envelopment Analysis (DEA) methods were employed to measure the performance and efficiency of banks, respectively.

In the overall bank rankings, results revealed that foreign commercial Standard Chartered Bank and state-owned Sonali Bank Limited came in first and last position, respectively. Among the four categories of banks, foreign commercial banks were the best performer, while state-owned banks were the worst. Only two banks, i.e. Citibank NA and HSBC Bank, were scale efficient while the remaining banks were inefficient. In terms of performance and efficiency, state-owned and specialized banks were deemed wanting.

This study proposes recommendations to the policymakers that could lead to more effective tactics for improving the banking industry's performance and efficiency.

As far as the authors are concerned, this study presents empirical evidence on the performance and efficiency of different types of banks and explores comparisons among them, which has never been done to this extent in the country before.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

This study aims to provide empirical evidence on the return and volatility spillover effects between Southeast Asian stock markets, bitcoin and gold in the periods before and during the COVID-19 pandemic. The interdependence among different asset classes, the two leading stock markets in Southeast Asia (Singapore and Thailand), bitcoin and gold, is analyzed for diversification opportunities.

The vector autoregressive-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity model is used to capture the return and volatility spillover effects between different financial assets. The data cover the period from October 2013 to May 2021. The full period is divided into two sub-sample periods, the pre-pandemic period and the during-pandemic period, to examine whether the financial turbulence caused by COVID-19 affects the interconnectedness between the assets.

The stocks in Southeast Asia, bitcoin and gold become more interdependent during the pandemic. During turbulent times, the contagion effect is inevitable regardless of region and asset class. Furthermore, bitcoin does not provide protection for investors in Southeast Asia. The pricing mechanism and technology behind bitcoin are different from common stocks, yet the results indicate the co-movement of bitcoin and the Singaporean and Thai stocks during the crisis. Finally, risk-averse investors should ensure that gold constitutes a significant proportion of their portfolio, approximately 40%–55%. This strategy provides the most effective hedge against risk.

The mean return and volatility spillover is analyzed between bitcoin, gold and two preeminent stock markets in Southeast Asia. Most prior studies test the spillover effect between the same asset classes such as equities in different regions or different commodities, currencies and cryptocurrencies. Moreover, the time-series data are divided into two groups based on the structural break caused by the COVID-19 pandemic. The findings of this study offer practical implications for risk management and portfolio diversification. Diversification opportunities are becoming scarce as different financial assets witness increasing integration.

This research explores the spillovers and portfolio implications for green bonds and environmental, social and governance (ESG) assets in the context of the rapidly expanding trend in green finance investments and the need for a green recovery in the post-COVID-19 era.

This study utilizes Diebold and Yilmaz’s (2014) spillover method and portfolio strategies (hedge ratio, optimal weights and hedging effectiveness) for the data starting from February 29, 2012, to March 14, 2022.

The study’s findings reveal that the lower volatility spillover is evidenced between the green bonds and ESG stocks during tranquil and turbulent periods (e.g. COVID-19 and Russia-Ukraine War). Furthermore, hedging costs are lower both in normal times and during economic slumps. Investing the bulk of the funds in green bonds makes it possible to achieve maximum hedging effectiveness between the S&P green bond (GB) and the S&P 500 ESG.

Both investors and policymakers may use these findings to make wise investment and policy choices to achieve post-COVID environmental sustainability.

Unlike previous research, this is the first to explore the interconnectedness among the major global and country-specific green bonds and ESG assets. The major findings of this study about the lower volatility spillovers and hedging costs between green bonds and ESG assets during the tranquil and turbulent periods may contribute to the post-COVID investment portfolio for environmental sustainability.

The main objective of this paper is to examine the impact of COVID-19 on the tourism flows of eight Asia-Pacific Countries: Australia, Hong Kong, Malaysia, New Zealand, the Philippines, Singapore, Taiwan and Thailand.

Using monthly data from 2019M1 to 2021M10 and 48 origin and eight destination countries in a panel Poisson pseudo-maximum likelihood (PPML) estimation technique and gravity equation framework, this paper finds that after controlling for gravity determinants, COVID-19 periods have a 0.689% lower tourism inflow than in non-COVID-19 periods. The total observations in this paper are 12,138.

A 1% increase in COVID-19 transmission in the origin country leads to a 0.037% decline in tourism flow in the destination country, while the reduction is just 0.011% from the destination. On the mortality side, the corresponding decline in tourism flows from origin countries is 0.030%, whereas it is 0.038% from destination countries. A 1% increase in vaccine intensity in the destination country leads to a 0.10% improvement in tourism flows, whereas vaccinations at the source have no statistically significant effect. The results are also robust at a 1% level in a pooled OLS and random-effects specification for the same model.

The findings provide insights into managing tourism flows concerning transmission, death and vaccination coverage in destination and origin countries.

The COVID-19-induced tourism decline may also be considered another channel through which the global recession has been aggravated. If we convert this decline in terms of loss of GDP, the global figure will be huge, and airline industries will have to cut down many service products for a long time to recover from the COVID-19-induced tourism decline.

It is to be realized by the policymaker and politicians that infectious diseases have no national boundary, and the problem is not local or national. That’s why it is to be faced globally with cooperation from all the countries.

This is the first paper to address tourism disruption due to COVID-19 in eight Asia-Pacific countries using a gravity model framework.

1. Asia-Pacific countries are traditionally globalized through tourism channels

2. This pattern was severely affected by COVID-19 transmission and mortality and improved through vaccination

3. The gravity model can be used to quantify the loss in the tourism sector due to COVID-19 shocks

4. Transmission and mortality should be controlled both at the origin and the destination countries

5. Vaccinations in destination countries significantly raise tourism flows

Asia-Pacific countries are traditionally globalized through tourism channels

This pattern was severely affected by COVID-19 transmission and mortality and improved through vaccination

The gravity model can be used to quantify the loss in the tourism sector due to COVID-19 shocks

Transmission and mortality should be controlled both at the origin and the destination countries

Vaccinations in destination countries significantly raise tourism flows

The purpose of this study is to present evidence as to whether the use of gold or silver can be justified as an asset to hedge against policy uncertainty and COVID-19 in the Chinese market.

By using a GARCH model with a generalized error distribution (GED), this study specifies that the gold (or silver) return is a function of a set of economic and uncertainty variables, which include volatility from interest rate innovation, a change in economic policy uncertainty (EPU), a change in geopolitical risk (GPR) and volatility due to pandemic diseases, while controlling for stock market returns, inflation rates, economic growth and the Chinese currency value.

This study employs monthly data of gold and silver prices over the period from January 2002 to August 2021 to examine hedging behavior. Estimated results show that the gold return is positively correlated to the stock return and a rise in uncertainty from economic policy innovation, geopolitical risk, volatility due to US interest rate innovation as well as COVID-19 infection. This result suggests that gold cannot be used to hedge against a stock market decline, but can be used to hedge against uncertainty in general. However, the silver return only responds positively to a rise in uncertainty from the inflation rate and geopolitical risk. Evidence shows that silver returns are negatively correlated with stock returns, and display hedging characteristics. However, the evidence lacks statistically significance during the COVID-19 period, suggesting that the role of silver as a safe-haven asset against stock market turmoil is weak for this time period.

More general nonlinear specifications can be developed. The tests may include different measures of uncertainty that interact with each other or with the lagged error terms. An implication of the model is that gold can be used to hedge against a broad range of uncertainties for economic policy change, political risk and/or a pandemic. However, the use of gold as an asset to hedge against a stock downturn in Chinese market should be done with caution.

This study has important policy implications as regards a choice in assets in formatting a portfolio to hedge against uncertainty. Specifically, this study presents empirical evidence on gold and silver return behavior and finds that gold returns respond positively to heightened uncertainty. Thus, gold is a good asset to hedge against uncertainty arising from policy innovations and infectious disease uncertainty.

This paper provides insightful information on the choice of assets toward hedging against risk in the uncertainty market conditions. It provides information to investors and policy makers to use gold price movements as a signal for detecting the arrival of uncertainty. This study also provides information for demanding a risk premium for infectious disease.

This study empirically analyzes and verifies the role that gold serves as a safe haven asset to hedge against uncertainty in the Chinese market. This paper contributes to the literature by presenting evidence of risk/uncertainty premiums for holding gold against various sources of uncertainty such as economic policy uncertainty, geopolitical risk and equity market volatility due to US interest rate innovation and/or COVID-19. This study finds evidence that supports the use of a nonlinear specification, which demonstrates the interaction of uncertainty with the lagged change of infectious disease and helps to explain the gold/silver return behavior. Further, evidence shows that the gold return is positively correlated to the stock return. This finding contrasts with evidence in the US market. However, silver returns are negatively correlated with stock returns, but this correlation becomes insignificant during the period of COVID-19.

Human gait analysis is based on a significant part of the musculoskeletal, nervous and respiratory systems. Gait analysis is widely adopted to help patients increase community involvement and independent living.

This paper presents a system for the classification of abnormal human gaits using a Markerless 3D Motion Capture device. This study aims at examining and estimating the spatiotemporal and kinematic parameters obtained by 3D gait analysis in diverse groups of gait-impaired subjects and compares the parameters with that of healthy participants to interpret the gait patterns.

The classification is based on mathematical models that distinguish between normal and abnormal gait patterns depending on the deviations in the gait parameters. The difference between the gait measures of the control and each disease group was examined using 95% limits of agreement by the Bland and Altman method. The scatter plots demonstrated gait variability in Parkinsonian and ataxia gait and knee joint angle variation in hemiplegic gait when compared with those of healthy controls. To prove the validity of the Kinect camera, significant correlations were detected between Kinect- and inertial-based gait tests.

The various techniques used for gait assessments are often high in price and have existing limitations like the hindrance of components. The results suggest that the Kinect-based gait assessment techniques can be used as a low-cost, less-intrusive alternative to expensive infrastructure gait lab tests in the clinical environment.

In many societies, environmental problems have had some negative impacts on both social and economic features with issues like capital structure seriously affected. In this write-up, an attempt has been made to pinpoint the influence of the combined effects of integrated reporting and financial leverage on the value of a firm. In most emerging markets, investment is heavily dependent on foreign capital inflow which is mainly in the form of financial leverage. It is, therefore, necessary to know how this shapes the net worth of firms in which they are invested. Shareholders' fund is a major factor in determining the level of investment and economic stability of a nation and consequently improvements in sustainable development. Hence, the moderating role of financial leverage in the integrated reporting-shareholders’ funds relationship aims to warrant this research.

All listed firms on the Nigerian Stock Exchange (NSE) as of 31st December 2021 were affected by this research. Filtering resulted in the use of 77 companies as a sample for the study covering a period of 12 years (2010–2021) with a total of 788 observations. Analyses of data were done through line graphs to show the trend and flow of disclosures between 2010 and 2021. Furthermore, linear regression was also applied to help determine the multiple effects of financial leverage and integrated reporting on shareholders' funds.

The outcomes showed that economic disclosure was 100% throughout the period of observation as opposed to environmental and social disclosures which, fluctuate throughout the period with an average of slightly over 55%. It was also discovered that a low but significant financial leverage moderated the interaction of integrated reporting on shareholders' funds.

Stakeholders and policymakers should, therefore, put in place rules, regulations, standards, structures and administrative networks to enable firms to comply with local rules, guidelines and upgraded standards of international worth on sustainability issues.

This research explores the problem of the effects of integrated reporting on investment capital as it affects developing economies. Results from this study could go a long way in narrowing the lack of interest in sustainability issues by prospective investors coupled with the low level of environmental and social reporting by firms in African economies that are mostly underdeveloped.

In this study, the authors examine the relationships between market-based regulations and corporate carbon disclosure and carbon performance. The authors also investigate whether these relationships vary across emission-intensive and non-emission intensive industries.

The study sample consists of the world's 500 largest companies across most major industries over a recent five-year period. Country-specific random effect multiple regression analysis is used to test empirical models that predict relationships between market-based regulations and carbon disclosure and carbon performance.

Results indicate that market-based regulations significantly and positively affect corporate carbon performance. However, market-based regulations do not significantly affect corporate carbon disclosure. This study also finds that the association between regulatory pressures and carbon disclosure and carbon performance varies across emission-intensive and non-emission-intensive industries.

The findings of this study have key implications for policymakers, practitioners and future researchers in terms of understanding the factors that drive businesses to increase their carbon performance and disclosure. The study sample consists of only large firms, and future researchers can undertake similar studies with small and medium-sized firms.

The results of this study are expected to help business managers to identify the benefits of adopting market-based regulations. Regulators can use this study’s results to evaluate if market-based regulations effectively improve corporate carbon performance and disclosure. Furthermore, stakeholders may use this study to evaluate and improve their businesses' reporting of carbon disclosure and performance.

In contrast to current literature that has used command and control regulations as a proxy for regulation, this study uses market-based regulations as a proxy for climate change regulations. In addition, this study uses a more comprehensive measure of carbon disclosure and carbon performance compared to the previous studies. It also uses global multi-sector data from carbon disclosure project (CDP) in contrast to most current studies that use national data from annual reports of sample firms of specific sectors.