Abstract
Stock market networks commonly involve uncertainty, and the theory of soft sets emerges as a powerful tool to handle it. In this study, we present a soft analogue of the differential of a vibrational potential function acting on a stock market network as vibrational force. For this purpose, we first study the vibrational potential function operating on each vertex by using the Laplacian of the neighborhood graph, then applied the soft approximator for the soft sets where the data points are embedded to Euclidean n space. We used the data of the globally operating leading stock markets of 17 countries and presented the results respect to them.
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