Soft Vibrational Force on Stock Market Networks

Balcı, Mehmet Ali; Akgüller, Ömer

doi:10.4236/oalib.1103050

Cited by 3 publications

(4 citation statements)

References 30 publications

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“…Soft set theory may also be applied to multiple-interaction systems. In the work of Balcı and Akgüller [30], the authors produced the soft set model of the metabolic system, and in another piece of research [31], the same authors offered a new methodology for obtaining soft set models of financial systems.…”

Section: Introductionmentioning

confidence: 99%

Network-Induced Soft Sets and Stock Market Applications

2022

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The intricacy of the financial systems reflected in bilateral ties has piqued the interest of many specialists. In this research, we introduce network-induced soft sets, a novel mathematical model for studying the dynamics of a financial stock market with several orders of interaction. To achieve its intelligent parameterization, this model relies on the bilateral connections between economic actors, who are agents in a financial network, rather than relying on any other single feature of the network itself. Our study also introduces recently developed statistical measures for network-induced soft sets and provides an analysis of their application to the study of financial markets. Findings validate the efficacy of this novel method in assessing the effects of various economic stress periods registered in Borsa Istanbul.

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Section: Introductionmentioning

confidence: 99%

Network-Induced Soft Sets and Stock Market Applications

2022

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“…In the complex network model of financial agents the interactions are modelled by the correlations of long time series [13][14][15][16][17][18][19]. Beside the other types of complex systems, financial systems have the strong memory and heredity properties.…”

Section: Introductionmentioning

confidence: 99%

Fractional Interaction of Financial Agents in a Stock Market Network

Balcı

2020

Applied Mathematics and Nonlinear Sciences

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In this study, we present a model which represents the interaction of financial companies in their network. Since the long time series have a global memory effect, we present our model in the terms of fractional integro-differential equations. This model characterize the behavior of the complex network where vertices are the financial companies operating in XU100 and edges are formed by distance based on Pearson correlation coefficient. This behavior can be seen as the financial interactions of the agents. Hence, we first cluster the complex network in the terms of high modularity of the edges. Then, we give a system of fractional integro-differential equation model with two parameters. First parameter defines the strength of the connection of agents to their cluster. Hence, to estimate this parameter we use vibrational potential of each agent in their cluster. The second parameter in our model defines how much agents in a cluster affect each other. Therefore, we use the disparity measure of PMFGs of each cluster to estimate second parameter. To solve model numerically we use an efficient algorithmic decomposition method and concluded that those solutions are consistent with real world data. The model and the solutions we present with fractional derivative show that the real data of Borsa Istanbul Stock Exchange Market always seek for an equilibrium state.

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“…Moreover, the structural analyses such as domination numbers of several types are presented in [15][16][17][18]. Besides, the theory of soft sets is also useful to express such relations [2,6,10,18,29,33].…”

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confidence: 99%

“…It can be also seen that a soft set is not a set but set systems. By the introduction of the theory in [27], its algebraic [1,19] and topological properties [20,33], interlacing with other theories [14] and the application in other fields [2,6,11,21,30] have been studied intensively.…”

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confidence: 99%