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This study investigates the dynamic interdependence between Islamic and conventional stock markets in the Gulf Cooperation Council (GCC) economies and the influence of global financial uncertainties on this interconnection.

The study employs the time-varying parameter vector autoregressions (TVP-VAR) technique and analyzes daily data from December 1, 2008 to July 14, 2021.

The research reveals robust interconnectedness within individual countries between Islamic and conventional stock markets, particularly during crises. Islamic stock markets exhibit greater susceptibility to spillover effects compared to conventional stocks. The UAE and Kingdom of Saudi Arabia (KSA) stock markets are identified as net transmitters of spillovers, while Oman, Bahrain and Kuwait receive more spillovers than they transmit. Global financial uncertainty measures (GVZ, USEPU and UKEPU) positively influence financial market interconnectedness, with EVZ exhibiting a negative impact while VIX and OVX remain statistically insignificant.

Investors and portfolio managers in Oman, Bahrain and Kuwait should carefully evaluate the UAE and KSA markets before making investment decisions due to the latter's role as net transmitters in the region. Additionally, it is emphasized that Islamic and conventional stocks should not be considered interchangeable asset classes for risk hedging.

Investors must be aware that Islamic and conventional stocks cannot be used as an alternative asset class to hedge risk.

The present article offers valuable insights for practitioners and researchers delving into the comparative analysis of Islamic and conventional stock markets within the GCC context. It enhances our comprehension of the dynamic interdependence between Islamic and conventional stock markets in the GCC economies and the impact of global financial uncertainties on this intricate relationship.

We investigate connections between the development of Fintech and the blue economy from September 14th, 2020, to August 11th, 2023.

In this research, we use a cutting-edge model-free connectedness approach to investigate the relationships between FinTech and blue bond volatility. Our work is the first to investigate the effects of unknown events, such as the COVID-19 pandemic and Ukraine–Russia conflicts, on the interconnection of volatility derived from FinTech development and blue bond volatility.

Our results highlight the two-way relationship between the development of Fintech and the blue economy during our sample period. The net total connectedness shows that the blue economy index is a net shock receiver, especially in late 2021 and the second half of 2022, while most of the fintech indexes in our sample are mainly net shock transmitters. The Ukraine–Russia tension threatens the development of a sustainable blue economy. The development of Fintech plays an important role in promoting the blue economy.

Our results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.

Our paper contributes to the literature in at least four ways. First, as previously stated, our article is the first to investigate the relationship between FinTech and blue bond volatility. Second, this study presented a framework for studying volatility interconnections between distinct variables that is more suited to analyzing these interconnections. In this research, we use a cutting-edge model-free connectedness approach to investigate the relationships between FinTech and blue bond volatility. Third, our work is the first to investigate the effects of unknown events such as the COVID-19 pandemic and Ukraine–Russia conflicts on the interconnection of volatility deriving from FinTech development and blue bond volatility. Lastly, our research provides a daily dataset for the BNP Paribas Easy ECPI Global ESG Blue Economy UCITS ETF to analyze 50 businesses from various markets that are at the forefront of the responsible application of ocean resources and other ESG standards. The Global X FinTech ETF (FINX) and the ARK FinTech Innovation ETF (ARKF) seek exposure to companies developing financial technology innovations. The development sectors include insurance, investment, fundraising and third-party lending by utilizing cutting-edge mobile and digital technologies. Our time series runs from September 14th, 2020, to August 11th, 2023. By using this database, we provide a comprehensive analysis of the link between the volatilities arising from various markets.

In this paper, we aim to provide an extensive analysis to understand how various factors influence electricity prices in competitive markets, focusing on the day-ahead electricity market in Romania.

Our study period began in January 2019, before the COVID-19 pandemic, and continued for several months after the onset of the war in Ukraine. During this time, we also consider other challenges like reduced market competitiveness, droughts and water scarcity. Our initial dataset comprises diverse variables: prices of essential energy sources (like gas and oil), Danube River water levels (indicating hydrological conditions), economic indicators (such as inflation and interest rates), total energy consumption and production in Romania and a breakdown of energy generation by source (coal, gas, hydro, oil, nuclear and renewable energy sources) from various data sources. Additionally, we included carbon certificate prices and data on electricity import, export and other related variables. This dataset was collected via application programming interface (API) and web scraping, and then synchronized by date and hour.

We discover that the competitiveness significantly affected electricity prices in Romania. Furthermore, our study of electricity price trends and their determinants revealed indicators of economic health in 2019 and 2020. However, from 2021 onwards, signs of a potential economic crisis began to emerge, characterized by changes in the normal relationships between prices and quantities, among other factors. Thus, our analysis suggests that electricity prices could serve as a predictive index for economic crises. Overall, the Granger causality findings from 2019 to 2022 offer valuable insights into the factors driving energy market dynamics in Romania, highlighting the importance of economic policies, fuel costs and environmental regulations in shaping these dynamics.

We combine principal component analysis (PCA) to reduce the dataset’s dimensionality. Following this, we use continuous wavelet transform (CWT) to explore frequency-domain relationships between electricity price and quantity in the day-ahead market (DAM) and the components derived from PCA. Our research also delves into the competitiveness level in the DAM from January 2019 to August 2022, analyzing the Herfindahl-Hirschman index (HHI).

The purpose of the study is to investigate, synthesize and critically evaluate empirical research findings on the behavioral traits of fund managers from 1994 to 2024. The ultimate goal is to provide a unified body of literature on three broad topics: first, fund managers' demographic and professional characteristics, such as age, gender, level of education and years of industry experience; second, fund managers' social and political connections; and third, fund managers' behavioral biases that lead to irrational investment decisions.

The relevant papers from selected journals were discovered and manually validated using the Scopus database. From 317 retrieved documents, 57 relevant articles were chosen and analyzed after the forward and backward search of the existing articles.

This paper presents a categorized summary of behavioral factors that have gained a foothold in influencing the behavior of fund managers in fund management research, with several studies demonstrating their significance leading to improved prediction and model precision, as this review indicates. In addition, the study summarized the contributions of prior empirical studies within the aforementioned three major categories and illustrated their consequences.

The present study contributes to the understanding of the effects of behavioral finance theories on fund managers by providing meaningful explanations of their behavioral traits based on empirical evidence and existing trends and knowledge gaps, both of which can influence the future direction of research.

This study seeks to examine the relationship between macroeconomic shock indicators, namely geopolitical risk (GPR), global economic policy uncertainty (GEPU) and financial stress (FS), and returns as well as volatilities on seven carefully selected stock markets in Africa. Specifically, the study intends to unravel the co-movement and interdependence between the respective macroeconomic shock indicators and each of the stock markets under consideration across time and frequency.

This study employed wavelet coherence approach to examine the strength and stability of the relationships across different time scales and frequency components, thereby providing valuable insights into specific periods and frequency ranges where the relationships are particularly pronounced.

The study found that GEPU, Financial Stress (FS) and GPR failed to induce significant influence on African stock market returns in the short term (0–4 months band), but tend to intensify in the long-term band (after 6th month). On the contrary, stock market volatilities exhibited strong coherence and interdependence with GEPU, FSI and GPR in the short-term band.

This study happens to be the first of its kind to comprehensively consider how the aforementioned macro-economic shock indicators impact stock markets returns and volatilities over time and frequency. Further, none of the earlier studies has attempted to examine the relationship between macro-economic shocks, stock returns and volatilities in different crisis periods. This study is the first of its kind in to employ data spanning from May 2007 to April 2023, thereby covering notable crisis periods such as global financial crisis (GFC) and the COVID-19 pandemic episodes.

This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions.

This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis.

In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles.

First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

The purpose of this study is to comprehensively analyse and compare equity crowdfunding (ECF) regulations across 26 countries, shedding light on the diverse regulatory frameworks, investor and issuer limits and the evolution of ECF globally. By addressing this research gap and providing consolidated insights, the study aims to inform policymakers, researchers and entrepreneurs about the regulatory landscape of ECF, fostering a deeper understanding of its potential and challenges in various economies. Ultimately, the study contributes to the advancement of ECF as an alternative financing method for small and medium enterprises (SMEs) and startups, empowering them to access much-needed capital for growth.

The study used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model for a systematic literature review on global ECF regulations. Starting with 74 initial articles from Web of Sciences and Scopus databases, duplicates were removed and language criteria applied, leaving 42 articles. After a thorough full-text screening, 20 articles were excluded, resulting in the review of 22 papers from 2016 to 2022. PRISMA’s structured framework enhances the quality of systematic reviews, ensuring transparency and accessibility of findings for various stakeholders, including researchers, practitioners and policymakers, in the field of ECF regulations.

This study examines ECF regulations across various countries. Notably, the UK has advanced regulations, while the USA adopted them later through the Jumpstart Our Business Startups Act. Canada regulates at the provincial level. Malaysia and China were early adopters in Asia, but Hong Kong, Japan, Israel and India have bans. Turkey introduced regulations in 2019. New Zealand and Australia enacted laws, with Australia referring to it as “crowd-sourced equity funding”. Italy, Austria, France, Germany and Belgium have established regulations in Europe. These regulations vary in investor and issuer limits, disclosure requirements and anti-corruption measures, impacting the growth of ECF markets.

This study’s findings underscore the diverse regulatory landscape governing ECF worldwide. It reveals that regulatory approaches vary from liberal to protectionist, reflecting each country’s unique economic and political context. The implications of this research highlight the need for cross-country analysis to inform practical implementation and the effectiveness of emerging ECF ecosystems. This knowledge can inspire regulatory adjustments, support startups and foster entrepreneurial growth in emerging economies, ultimately reshaping early-stage funding for new-age startups and SMEs on a global scale.

This study’s originality lies in its comprehensive analysis of ECF regulations across 26 diverse countries, shedding light on the intricate interplay between regulatory frameworks and a nation’s political-economic landscape. By delving into the nuanced variations in investor limits, investment types and regulatory strategies, it unveils the multifaceted nature of ECF regulation globally. Furthermore, this research adds value by comparing divergent perspectives on investment constraints and offering an understanding of their impact on ECF efficacy. Ultimately, the study’s unique contribution lies in its potential to inform practical implementation, shape legislative frameworks and catalyse entrepreneurial ecosystems in emerging economies, propelling the evolution of early-stage funding practices.

This paper aims to examine the relationships among environmental, social and governance (ESG) practices, innovation and economic growth in five Asian countries from 1990 to 2020.

The study innovatively constructed the ESG index at the country level by using frequency statistics on text mining and factor analysis for each country over time. In addition, this study used the autoregressive distributed lag method to establish a long-term relationship.

The authors discovered that ESG practices among corporate entities significantly impact economic growth in Malaysia, the Philippines and Singapore. Specifically, the environmental component positively affects the growth of Malaysia, Thailand and the Philippines, while the governance components of ESG contribute to Thailand’s economic growth. The authors also discovered that innovation improves countries’ economic growth, thus offering policy insights into promoting ESG practices and stimulating the ecosystem for innovation.

The paper fills the gap left in previous inconclusive findings on the association between ESG practices and country growth.

In recent years, US firms have increasingly integrated ESG performance goals into their executive remuneration packages. This study examines the relationship between board gender diversity and the tendency of firms to incorporate ESG metrics in performance-based compensation using data from US firms. The key questions this study addresses are: Are firms with more females on the board more likely to link executive compensation metrics? What components and types of ESG metrics are more likely to be adopted by firms with more females on the board?.

This study employs OLS regression, logistic regression, as well as instrumental variable, propensity score matching, and entropy balance methods to establish causality.

This study finds that firms with gender-diverse boards are more likely to shape their executive remuneration plans to be more ESG-oriented. The most significant positive relationship is observed with environmental and social sub-categories. The results also demonstrate that female directors are more likely to encourage firms to evaluate managers based on absolute and short-term ESG goals.

This study is one of the early studies that examine the adoption of ESG performance goals into executive compensation plans. It contributes to the existing literature by exploring the relationship between board gender diversity and the probability of firms incorporating ESG performance goals into executive compensation packages using a sample of US firms.

This study aims to identify necessary conditions for innovative entrepreneurship in cities and determine similarities in entrepreneurial configurations among them.

The authors assessed the necessary conditions for various levels of entrepreneurial output and categorized cities based on similar patterns by applying necessary condition analysis (NCA) and cluster analysis in a sample comprised of 101 cities from the entrepreneurial cities index, representing a diverse range of urban environments in Brazil. A comprehensive data set, including both traditional indicators from official Bureau of statistics and nontraditional indicators from new platforms of science, technology and innovation intelligence, was compiled for analysis.

Bureaucratic complexity, urban conditions, transport infrastructure, economic development, access to financial capital, secondary education, entrepreneurial intention, support organizations and innovation inputs were identified as necessary for innovative entrepreneurship. Varying levels of these conditions were found to be required for different entrepreneurial outputs.

The static nature of the data limits understanding of dynamic interactions among dimensions and their impact on entrepreneurial city performance.

Policymakers can use the findings to craft tailored support policies, leveraging the relationship between city-level taxonomy and direct outputs of innovative entrepreneurial ecosystems (EEs).

The taxonomy and nontraditional indicators sheds light on the broader societal benefits of vibrant EEs, emphasizing their role in driving socioeconomic development.

The cluster analysis combined with NCA’s bottleneck analysis is an original endeavor which made it possible to identify performance benchmarks for Brazilian cities, according to common characteristics, as well as the required levels of each condition by each city group to achieve innovative entrepreneurial outputs.