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Abstract This review synthesizes 48 academic studies on Initial Coin Offerings (ICOs) from 2018 to 2023, employing bibliometric and content analyses to illuminate their complexities and innovation in entrepreneurial finance. It identifies four key themes: (1) regulatory intricacies, market transformation, and strategic implications for emerging ventures; (2) the opportunities and challenges presented, and key factors influencing the success of ICOs; (3) ICOs and entrepreneurial finance; and finally, (4) review of reviews. By examining the intersection of legal frameworks, disruptive potential, and stakeholder challenges, this interdisciplinary perspective captures the essence of ICOs and charts a course for future inquiry. It serves as a pivotal reference for researchers, practitioners, and regulators to understand the multifaceted ICO landscape and its implications for the future of finance.

This study investigates the changes and persistence in dynamic connectedness between stock market performance and exchange rate fluctuations, comparing conventional and Islamic financial systems. With an eye on a global financial landscape characterized by the integration of capital markets and the adoption of floating exchange rate regimes, it examines the effects of exchange rate variations on the dynamics of the stock market in nine different countries - the United Kingdom, Australia, Japan, Singapore, Canada, China, India, Korea, and South Africa. The study employs daily data spanning from November 2015 to July 2023 and uses a comprehensive analysis of three-step methodology, including nonparametric causality-in-quantiles tests, asymmetric slope Conditional Autoregressive Value-at-Risk (CAViaR), and Time-Varying Parameter Vector Autoregressive (TVP-VAR) Connectedness measure. Our results underline the asymmetric impact of exchange rate fluctuations on stock markets and highlights the distinctive characteristics of Islamic financial markets. Comparing Islamic and conventional stock markets in the context of exchange rate fluctuations, this study not only serves to fill a gap in the existing literature but also emphasizes the significance of currency exchange rate swings for global investors, policymakers, and practitioners trying to understand the intricacies of global financial markets.

This research explores the interdependence within the international logistics sector among 17 nations, utilizing a quantile-based technique to assess the transmission of returns. By analyzing daily data from DataStream spanning from 1 June 2016, to 12 August 2024, we apply the Quantile Vector Autoregression framework to examine the synchronous behavior of variables, considering the magnitude of shocks. Our findings reveal varying degrees of linkage at the lower, median, and upper quantiles of the conditional distribution. The results show that extreme events, such as the COVID-19 pandemic and the Russia-Ukraine war, significantly amplified spillovers across logistics markets, while the impact of the Israel-Hamas conflict was more regionally contained. Regional clustering and geographical proximity play a crucial role, with stronger interconnections observed among neighboring countries, such as the US and Canada, and Germany and France. The US stands out as a dominant transmitter of shocks, while countries in Asia and Oceania tend to be net receivers, highlighting their vulnerability to external disruptions. These results underscore the need for quantile-based risk assessments in regulatory frameworks and risk management strategies to better manage asymmetric risk transmissions during global crises.

This study investigates the multidimensional connectedness between various Fourth Industrial Revolution assets and global commodities to analyze their role in portfolio diversification. Using dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH), Baruník and Křehlík (BK) frequency connectedness, and quantile connectedness, we estimate the time-frequency connectedness involved in the transmission mechanism at the upper, middle, and lower quantiles, using empirical data from April 30, 2018, to January 9, 2023, which incorporates data before and during the pandemic and consider the impact of the Russia-Ukraine conflict. Our findings reveal that Fourth Industrial Revolution assets are highly correlated, especially during periods of stress and crisis, which necessitates portfolio diversification during such periods. We also find that holding these assets over the long run is better than holding them in the short run. Our results indicate that the connectedness network assessed at the conditional median quantile is not reflective of the level of connectedness associated with substantial positive or negative shocks. This study is of high importance to investors in Fourth Industrial Revolution assets.

The study examines the spillover between Twitter Uncertainty Indexes (TUI) and 10 US sectors. Our methodology is twofold: a time-varying parameter vector autoregression (TVP-VAR) to explore the dynamic connectedness among sectoral returns and a regression, mainly ordinary least squares (OLS) and quantile, to explore the role of TUI in explaining the total connectedness and the net connectedness of each sector. First, our results indicate that industrials and materials are the main net transmitters of shocks, and utilities and energy are the main recipients. Second, TUI increases total connectedness only at higher values of connectedness, suggesting that more diversification benefits are available at low levels of connectedness and TUI. Third, the direction of the TUI's effect on net connectedness changes from one sector to another, indicating that TUI can signal either good or bad news, depending on the sector.