Financial technology, or Fintech, has captured the attention of scholars, students, and institutions across worldwide for over a decade. With a plethora of new financial services, products, and innovative methods to engage with clients, the impact of technology on the financial sector has been extensively studied. This research paper provides a summary of scientific research on FinTech by using bibliometric analysis. Using the Scopus database, the paper analyzed 665 publications and identified research gaps and new study topics through “VOS-Viewer” software and “Biblioshiny” using RStudio. The study focused on FinTech’s functions and research constraints in digital finance by assessing citation links between the most significant articles. The findings provide a starting point for further investigation and offer opportunities for researchers to expand their expertise in exciting and innovative studies. Overall, this study seeks to help researchers discover new avenues for exploration in Fintech while advancing their present understanding. There exists much scope in the area of Digital Lending, Supply Chain Finance, the Internet of Things, and RoboAdvisers.

This study aims to investigate the dynamic conditional correlation and volatility spillover between the conventional and Islamic stock markets in developed and emerging countries in order to develop better portfolio and asset allocation strategies. We used both multivariate GARCH (MGARCH) and multi-scales-based maximal overlap discrete wavelet transform (MODWT) approaches to investigate dynamic conditional correlation and volatility spillover between conventional and Islamic stock markets in developed and emerging countries. The results show that conventional and Islamic markets move together in the long run for a specific time horizon and present time-varying volatility and dynamic conditional correlation, while volatility movement changes due to financial catastrophes and market conditions. Further, the findings point out that Chinese conventional and Islamic stock indexes showed higher volatility, whereas Malaysian conventional and Islamic stock indexes showed comparatively lower volatility during the global financial crisis. This study provides fresh insights and practical implications for risk management, asset allocation, and portfolio diversification strategies that evaluate stock market reactions to the crisis in the international avenues of finance literature.

The current study aims to explore the role of various macroeconomic factors in determining corporate investment. Using firm-level data of six Gulf Cooperation Council (GCC) region countries for a 14 year period (2007–2020), the current study establishes the empirical analysis by employing the system generalized method of moments (GMM) technique. The empirical results reveal the negative impact of foreign direct investment whilst the positive impact of economic growth, financial development, and inflation rate on corporate investment decisions. Due to high market competition, foreign direct investment can hamper the growth of domestic industrial sectors. However, economic growth, financial development, and inflation rate positively drive the investment by enhancing the demand for industrial products, cheap financing, and price appreciation effect on production enrichment respectively. Based on results, it is suggested that corporate managers should consider the economic sensitivity of investment. The novelty of study can be listed, as the current analysis presents the dynamic role of various economic factors in determining the corporate investment decisions specifically in GCC region countries.

The aim of this study was to evaluate whether trading experience reduces exposure to heuristic-driven biases, namely availability bias, anchoring and adjustments bias, representativeness bias, and confirmation biases of individual investors operating in the Indian stock market, through the moderating role of the Big Five personality traits. To achieve these research objectives, primary data were collected through a structured questionnaire. The sample consisted of 408 individual investors trading on the Indian stock market, who were selected on a convenient basis. Confirmatory factor analysis and Cronbach’s alpha were used to measure the validity and reliability of the data. Further analysis was conducted using Pearson’s correlation and multiple regression. The results of this study prove that increased trading experience does not always reduce the susceptibility to heuristic biases. Increased trading experience reduces the susceptibility to availability, and anchoring and adjustment heuristics of individual investors operating on the Indian stock market. The present study has some relevant implications for investors, portfolio managers, financial advisors, and other interested persons in the stock market.

The purpose of this study is to find symmetries and asymmetries in the exchange rate and macroeconomic fundamentals of advanced European markets, namely Denmark, the Euro Area, and United Kingdom, for the period of 2011 to 2022 via application of the NARDL technique. The findings reveal that interest rate affects DKK exchange rate asymmetrically in the long and short run, whereas money supply affects it in the short run. Foreign reserves are found to be helpful for all three currencies in stabilizing the exchange rate. A decline in gold price weakens GBP, DKK, and EUR in the long run. Previous studies suggest that the existence of asymmetrical relationships justifies the selection of NARDL for empirical analysis. This study makes a contribution to the existing literature, as it proves that forecasting via NARDL is also robust for analysis. The findings have significant policy implications for financial applications.

Working capital management requires careful attention from corporate managers because it plays an important role in corporate stability. The social belongingness of managers induced them to learn from their society, colleagues, and overall industrial movement. They also learn from their peers that have more strategic efficiency. In line with these arguments, the objective of the current study is to explore the peer influence on corporate working capital management practices. For regression analysis, we utilized ten years of data (2009–2018) of non-financial publicly listed firms at PSX (Pakistan Stock Exchange). We used the cash conversion cycle (CCC) as a proxy variable to measure working capital management (WCM). We employed panel fixed effect and system GMM (generalized method of moments) models to estimate regression between the variables of the study. The empirical findings suggest the significant impact of peer WCM on corporate WCM. They also suggest the significant impact of other variables that determine the WCM. This study recommends social learning policy for corporate managers. They can learn from their peers to manage the working capital. Most previous studies discuss peer influence on investment decisions, corporate cash holding, financing policy, etc., but no study explores such a relationship specifically in the case of Pakistan.