Fear Risk transmission to AI Stocks, Tokens and Energy Investments: Connectedness in pre and post availability of COVID-19 Vaccine

Abstract

The study aims to explore the COVID-19 risk transmission to AI, Tokens, AI stocks, and Fossil fuels during the vaccine non-availability and availability periods using the extended GFI. The outcomes of the GARCH-BEKK model reveal that lag shocks in the extended GFI significantly enhance the conditional volatility of FET-Fetch in both pre- and post-vaccine periods, and also enhance the conditional volatilities of Ocean-protocol, AMZN-Amazon, and all fossil fuel markets in the post-vaccine period. However, AGIX-Singularity NET and MSFT-Microsoft remain unaffected during both periods. With the application of the TVP-VAR model, the study uncovers the extent of connectedness. Similar spillovers are observed between GFI and AI tokens, AI stocks, and fossil fuel markets. The risk transmission character of such investments helps investors to avoid uncertainties during trading. The connectedness of GFI with AI tokens, stocks, and fossil fuel investments may uncover diversification opportunities for investors, especially during ups and downs in markets.