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The prediction of stock market (SM) indices is a fascinating task. An in-depth analysis in this field can provide valuable information to investors, traders and policy makers in attractive SMs. This article aims to apply a correlation feature selection model to identify important technical indicators (TIs), which are combined with multiple deep learning (DL) algorithms for forecasting SM indices.

The methodology involves using a correlation feature selection model to select the most relevant features. These features are then used to predict the fluctuations of six markets using various DL algorithms, and the results are compared with predictions made using all features by using a range of performance measures.

The experimental results show that the combination of TIs selected through correlation and Artificial Neural Network (ANN) provides good results in the MADEX market. The combination of selected indicators and Convolutional Neural Network (CNN) in the NASDAQ 100 market outperforms all other combinations of variables and models. In other markets, the combination of all variables with ANN provides the best results.

This article makes several significant contributions, including the use of a correlation feature selection model to select pertinent variables, comparison between multiple DL algorithms (ANN, CNN and Long-Short-Term Memory (LSTM)), combining selected variables with algorithms to improve predictions, evaluation of the suggested model on six datasets (MASI, MADEX, FTSE 100, SP500, NASDAQ 100 and EGX 30) and application of various performance measures (Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error(RMSE), Mean Squared Logarithmic Error (MSLE) and Root Mean Squared Logarithmic Error (RMSLE)).

The aim of this study is to analyse the factors that contribute to the disclosure of relational liabilities (RLs) of the US companies.

The study uses content analysis to examine the disclosure of RLs in annual reports of the US companies listed on the Nasdaq-100 index from 2013 to 2015.

The study finds a positive correlation between the disclosure of RLs and gender diversity of the board of directors as well as the education level of the CEO. By contrast, the disclosure of RLs is negatively associated with the age of the CEO. Companies in knowledge-intensive industries also tend to disclose more information about their RLs than those in other industries.

This study focuses on the determinants of RLs, whereas previous research has mainly examined the positive impact of voluntary disclosure of intellectual capital on financial performance. The main objective of this study is to shed light on the factors that influence the disclosure of RLs.

This research paper aims to analyze the stock exchanges of developed, emerging and developing countries to investigate the volatility in stock markets and to evaluate the rate of mean reversion.

The stock exchanges included in the research are NASDAQ, Tokyo stock exchange, Shanghai stock exchange, Bombay stock exchange, Karachi stock exchange and Jakarta stock exchange. Secondary daily data from Bloomberg are used to conduct the research for the period from January 2011 to December 2018. Generalized autoregressive conditional heteroskedasticity (GARCH) (1,1) model was applied to examine volatility and the half-life formula was used to calculate mean reversion in days.

The research concluded that all the stock exchanges included in the research satisfy the assumptions of mean reversion. Developing countries have the lowest volatility while emerging countries have the highest volatility which means that the rate of mean reversion is fastest in developing countries and slowest in emerging countries.

Future studies can determine the reasons for fastest rate of mean reversion in developing countries and slowest rate of mean reversion in emerging countries.

Developing countries show the lowest mean reversion in days while the emerging countries show the highest mean reversion in days indicating that developing countries take less time to revert to their mean position.

The majority of previous studies on univariate volatility models are mostly on applications of the models. Only a few researchers have taken the robustness of the models into account when applying them in emerging countries and not in developed, developing and emerging countries in one place. This makes the current study unique and more rigorous.

This study aims to examine the relationship between the individual auditor’s industry specialization and the audit report lag (hereafter ARD). Further, it explores whether changing in the audit reporting requirement (i.e. the adoption of ISA701) influences the auditor’s industry specialization effect on the ARD.

A large data set of companies listed on the NASDAQ OMX Stockholm over the period 2010–2019 has been analyzed. Least squares regressions have been estimated to provide empirical evidence for the researched hypotheses.

The research findings indicate that the ARD is shorter for client firms audited by an industry specialist audit partner. Testing for the moderating role of changing in the auditing reporting regulation on the relation between the audit partner’s industry specialization and the ARD, the authors reveal that all client firms (except client firms with industry specialist audit partners) experienced an increase in the ARD. Overall, the baseline regression findings are found to be robust to the endogenous auditor choice and multiple measures of both the ARD and the auditor’s industry specialization.

This paper provides novel evidence on the relationship between the audit reporting lag and industry specialization from the individual auditor perspective, an issue that has hitherto been unexplored. The regression results further contribute to the upsurge debate about the consequences of changing in the audit reporting model by providing consistent support for the importance of industry specialization of the audit partner in minimizing costs derived from the former requirement.

The purpose of this study is to extend the Fraud Diamond Theory to celebrity Special Purpose Acquisition Companies (SPACs) and investigate their post-Initial Public Offering (IPO) stock market performance.

After obtaining a sample of celebrity SPACs from the Spacresearch.com database, fraud risk characteristics were obtained from Lexis Nexus searches. Buy and hold abnormal returns were calculated for celebrity SPACs versus a small-cap equity benchmark for time intervals after IPO, and multiple regression analysis was performed to examine the relationship between fraud risk features and post-IPO returns.

Celebrity SPACs exhibit Fraud Diamond characteristics and significantly underperform a small-cap stock portfolio on a risk-adjusted basis after IPO.

This study only examines celebrity SPACs that conducted IPOs on the NYSE and NASDAQ/AMEX and does not include those that are traded on the Over the Counter Bulletin Board (OTCBB).

Celebrity endorsement of SPAC vehicles attracts investors who may not be properly informed regarding the risk characteristics of SPACs. Accordingly, investors should be warned that celebrity SPACs underperform a small-cap equity portfolio and exhibit significant elements of fraud risk.

The use of celebrity endorsement as a marketing device to attract investment in SPACs has regulatory implications.

To the best of the authors’ knowledge, this paper is the first to examine the fraud risk characteristics and post-IPO performance of celebrity SPACs.

This study aims to unpack the progress of board gender diversity among the 3,000 largest US listed firms by market capitalization (i.e. Russell 3000 Index). This study extrapolates four classifications of firms based on the number of women in the boardroom: zero women, one or two women, three plus women and gender balanced. The purpose of this study is to examine where progress has and has not been made, why firms plateau and an agenda for the future.

This study first provides a summative overview of the literature on the benefits of board gender diversity. It then examines progress according to the four classifications, each of which have theoretical underpinnings for whether or not firms can reap the strategic benefits of gender-diverse boardrooms.

Several indices of US publicly traded companies now have women holding between 30% and 33% of the seats in the boardroom. By examining the spread of women on boards according to the four classifications, this study extrapolates three key insights: firms experiencing tokenism (i.e. one or two women in the boardroom) do not have enough women to reap the strategic benefits of diverse boardrooms; firms that have reached a critical mass (three women in the boardroom) are at an impasse and may risk plateauing; and gender-balanced firms are elevated to the status of being role models for other firms. Calls for action and associated action plans accompany these insights.

This study reminds managers and directors of the strategic benefits of gender-diverse boards and offers three critical insights that boards can use to classify what stage they are at on the path toward board gender equality. Based on their classification, calls for action and action plans offer guidance to firms.

This study shifts away from focusing on the average percentage of board seats held by women across all firms and offers new insights on the progress that firms have made according to the number of women in their boardroom.

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

The rising number of food recalls has raised concerns about complexity, globalization and weak governance in the food supply chain. This paper aims to investigate the recall of plant-based products with data from the US Food and Drug Administration.

Introducing the structural topic modeling method allowed us to test theories on recall in the context of sustainable food consumption, enhancing the understanding of food recall processes. This approach helps identify latent topics of product recalls and their interwoven relationships with various stakeholders.

The results answer a standing research call for empirical investigation in a nascent food industry to identify stakeholders’ engagements for food safety crisis management for corporate social responsibility practices. This finding provides novel insights on managing threats to food safety at an industry level to extend existing antecedents and consequences of product recall at a micro level.

For practitioners, this empirical finding may provide insights into stakeholder management and develop evidence-based strategies to prevent threats to food safety. For public policymakers, this analysis may help identify patterns of recalls and assist guidelines and alarm systems (e.g. EU’s Rapid Alert System for Food and Feed) on threats in the food supply chain.

Two detected clusters, such as opportunisms of market actors in the plant-based food system and food culture, from the analysis help understand corporate social responsibility and food safety in the plant-based food industry.

This paper aims to review and summarize the findings of research dedicated to studying the process of building sustainable business models (BM) triggered by development of COVID-19 pandemic.

Bibliometric analysis is performed to identify the papers most relevant to the topic. The authors review the findings of more than 50 papers from Scopus database published between 2020 and 2022 dedicated to studying BM during COVID-19 pandemic, as well as papers dedicated to sustainability phenomenon and most cited BM research.

The paper identifies the gap in defining BM sustainability and contributes to better understanding of this phenomenon by demarcating it from traditional environment-based United Nations agenda. It also describes why network-based approach to BM helps to better address sustainability aspects. The paper demonstrates how representation of a networked BM by three levels of analysis (namely, structure of a BM, interaction mechanism between BM actors and results of their interaction) is organically connected to the key milestones of the value creation process (value definition, value creation, value distribution and value capture) and shows how these three levels can be used to analyze and structure the practical changes proposed in COVID-19-oriented BM. Finally, the paper summarizes key findings of the studies dedicated to BM during the pandemic and structures key insights in relation to building sustainable BM.

The results of the paper contribute to developing theory around BM sustainability as well as provide insights for business practitioners on how to adjust BM during the crisis. At the same time, many insights shown in the paper are industry specific, which limits their generalizability, as well as consequences of the pandemic are still not fully clear. Therefore, the authors argue that future research should be primarily focused on developing generalizable measurement frameworks to evaluate the antecedents, process and results of BM adaptation.

The paper strengthens theoretical foundations for the research focused on BM sustainability and helps businesses to better manage the adaptation in the fast-changing environment.

This paper aims to focus on the relationship between female leadership and the environmental, social and governance (ESG) performance of firms. Specifically, the study examines if firms with women as chief executive officers (CEOs) and/or board chairpersons have higher environmental and social scores.

The study uses data on publicly listed Nordic firms in a panel regression approach to establish the relationship between female leadership and the environmental and social performance of firms.

The result of this study shows that women have a leadership characteristic that increases the weighted average of environmental (E) and social (S) performance of a firm. In particular, pillar score results indicate a positive relationship between female CEOs and the social scores of a firm but no relationship between a female board chairperson and the environmental or social scores of a firm. This implies that gender-based differences affect the CEO’s success, especially in a firm’s social performance. Further analyses show a more significant impact on the E and S performance when a woman replaces a man as CEO of a firm.

While prior research has explored various aspects of gender diversity in corporate leadership and its potential impact, the focus on the Nordic context in this study provides a unique perspective, given the region’s distinct business environment and societal factors. In addition, by examining the collective influence of female leaders and both female CEOs and board chairpersons separately, this study provides a nuanced understanding of how different leadership roles may impact a firm’s ESG performance.