Search

This research investigates the impact of geopolitical risk, institutional governance and green finance on environmental outcomes, specifically focusing on carbon emissions and ecological footprint. Utilizing the dynamic CS-ARDL method and aggregated mean group analysis on a panel dataset covering 21 nations from 2000 to 2021, our findings reveal that heightened geopolitical risk leads to both short and long run increases in carbon emissions and the ecological footprint. Our study finds both a direct as well as indirect connection between governance, green finance and environmental outcomes in both the short and long run, highlighting the nuanced impact of governance on the formulation of environmental policies and regulatory frameworks. The results emphasize the need for targeted strategies, including focused investments and incentives for sustainable finance, particularly in conflict-affected regions. Furthermore, our research underscores the enduring impact of historical events, such as wars, on contemporary environmental indicators, emphasizing the importance of proactive conflict prevention measures. Our research suggests that policymakers should adopt comprehensive strategies that prioritize emission reduction during short-run spikes in geopolitical risk while maintaining a steadfast commitment to long-run sustainability. • We examine the dynamic impact of geopolitical risk, governance and green finance on carbon emissions & ecological footprint. • We employ co-integration and auto-regressive distributed lag (CS-ARDL) method to analyze the data. • Elevated geopolitical risk results in both short and long term increases in carbon emissions and ecological footprint. • Direct and indirect connection exists between governance, green finance and environmental outcomes in short and long run. [ABSTRACT FROM AUTHOR]

This study investigates calendar anomalies in eight Islamic frontier markets. Our sample consists of the daily closing prices of their stock indices for the period of January 2006 to September 2019. The data are categorized with respect to day-of-the-week and month-of-the-year according to both the Gregorian and Islamic calendars. We control for time-varying systematic risk using Morgan Stanley Capital International (MSCI) index as the proxy for the market portfolio and apply Bonferroni correction to reduce the occurrence of false-positive results. We find little support for the proposition that any of the Islamic calendar months generate abnormal returns, bar a slight negative abnormal return during the holy month of Rajab for Kuwait. We find evidence of a small negative Monday effect for the stock markets of Bangladesh and Pakistan and a small positive January effect for the stock market of Morocco. The results support weak-form market efficiency, suggesting that investors in frontier stock markets should not expect to outperform the market on a consistent basis when trading on particular days of the week or months of the year according to the Islamic or Gregorian calendar. [ABSTRACT FROM AUTHOR]

The article presents information on genetic programming approach to technical trading. The article discusses about small-cap stocks, and their share of responsibility for incorrect pricing and a sufficient condition for profitable technical trading. It also explores the results of applying the technology of genetic programming (GP) to three popular U.S. stock portfolios namely, the large-cap Russell 1000 index, the small-cap Russell 2000 index, and the broad-based Russell 3000 index respectively.