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.
Cite this paper
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