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Time and Frequency Connectedness Among Emerging Markets and QGREEN, FinTech and Artificial Intelligence-Based Index: Lessons from the Outbreak of COVID-19
Vision ; 2023.
Article in English | Scopus | ID: covidwho-2245119
ABSTRACT
The study is about contributing to the ongoing discussion on the diversification opportunities for emerging markets with non-conventional asset class. The limited literature in the era of fourth industrial revolution motivates us to gauge diversification opportunities. This study is focusing on identifying diversification opportunities with a set of unique asset classes that are the proxies for Green Funds, FinTech and Artificial Intelligence-based index funds. The method and model applied in the study are time and frequency connectedness in a Wavelet Coherence, and for the robustness check—Network analysis has been applied. The originality of the study lies in identifying the impact of the outbreak of COVID-19. The results captured that FinTech-based asset was the most resilient asset class during the pre- and post-outbreak of COVID-19, followed by AI-based fund and finally by Green fund. Henceforth, FinTech provides superior diversification opportunities among all with MSCI Emerging Market. AI and Green funds are captured to be invested in the long term for diversification, whereas FinTech is suitable for both long- and short-term assets. The results are relevant for investors in emerging markets and for policymakers as well. © 2023 MDI.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Vision Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Vision Year: 2023 Document Type: Article