In this paper effects of COVID–19 pandemic on stock market network are analyzed by an application of operational research with a mathematical approach For this purpose two minimum spanning trees for each time period namely before and during COVID–19 pandemic are constructed Dynamic time warping algorithm is used to measure the similarity between each time series of the investigated stock markets Then, clusters of investigated stock markets are constructed Numerical values of the topology evaluation for each cluster and time period is computed © 2021 Sciendo All rights reserved
Understanding the impact of COVID–19 on global financial network using graph based algorithm: Minimum spanning tree approach