Examining FinTech Indicators on the Performance of Equity Investment Funds - Baghmirani, Roya (Management Strategies and Engineering Sciences, 2024)
This research examines FinTech indicators on the performance of equity investment funds. With the development of FinTech, new tools have emerged to enhance the efficiency, transparency, and performance management of funds. In this study, the Principal Component Analysis (PCA) method was used to identify key FinTech components, followed by the Markov Switching model to analyze the variable performance patterns of the funds. The results revealed that components of FinTech infrastructure and performance management had the greatest contribution to the improvement of the composite FinTech index. The findings indicated that the FinTech infrastructure component had the most significant impact on the composite FinTech index, followed by performance management and FinTech evaluation in the institutional environment. To analyze different performance states, the Markov Switching model was applied, revealing two main performance states in the funds: a stable state with high returns and a volatile state with lower returns. Practical recommendations for fund managers include strengthening FinTech infrastructure to enhance security and reduce costs, utilizing data mining and behavioral analytics to better identify customer needs, and employing blockchain and automation technologies to improve efficiency and transparency. This study also highlights limitations, such as data restrictions and the generalizability of findings to all institutional environments. These results can assist fund managers in leveraging financial technologies to not only improve fund performance but also increase attractiveness to investors and better manage risks.