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4th International Conference on Emerging Research in Electronics, Computer Science and Technology, ICERECT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2257769
26th World Multi-Conference on Systemics, Cybernetics and Informatics, WMSCI 2022 ; 3:52-57, 2022.
Article in English | Scopus | ID: covidwho-2235802


Global financial assets behaviour has become highly volatile during the pandemic period, especially the highly risky assets. Financial instruments like cryptocurrencies are basically speculative and the investors basically trade on these anomalies. Even though the entire world has come to standstill these markets were never. In order to understand the market anomalies during the COVID pandemic the popular asset in cryptos which is bitcoin along with the global market index such as S&P 500, Global Crude Oil prices and gold prices daily trading data are taken into consideration during and post covid. Some of the interesting aspects of Machine Learning (ML) such as variety of techniques, parameter selection, nonlinearity and generalization ability make it well suited for the problems of uncertain functional structure. Price prediction of stock markets is a challenging problem because of unpredictable noise and the number of potential variables that may impact on the prices. The research work presented in this paper involves the development of a ML algorithm which will throw light on the price behaviour of these instruments during and post crisis. © 2022 WMSCI.All rights reserved.