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Publication Type : Conference Paper
Publisher : Springer
Source : Communications in Computer and Information Science (2022), 1528, 229-243.
Campus : Coimbatore
School : School of Engineering
Center : Center for Computational Engineering and Networking, Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN)
Year : 2021
Abstract : The impact of covid-19 on the financial market is considered a ‘black swan event’, i.e., the occurrence of a highly unpredictable event with far-reaching consequences. Prediction of such events in prior is essential due to the financial risk associated. In this paper, we study critical slowing down as an early warning signal to forewarn such unpredictable and sudden transitions concerning the Indian stock market for the covid-19 period. This is the first study to predict covid-19 financial crisis based on critical slowing down theory. We analyze the evolution of first-order autocorrelation and standard deviation using the sliding window approach to predict any impending transition. We found that both the early warning measures could forewarn an impending transition for almost all the stock indices considered for the analysis.
Cite this Research Publication : Modi, A., Jyothish Lal, G., Gopalakrishnan, E. A., Sowmya, V., Soman, K. P. and Vinayakumar, R. “Early warning indicators of financial crisis during Covid-19”, Communications in Computer and Information Science (2022), 1528, 229-243.