Financial Risk Information Spreading on Metapopulation Networks

Min Lin,Li Duan,Wei Wang

doi:10.1155/2021/6654169

Min Lin, Li Duan + Show 1 more

Open Access

https://doi.org/10.1155/2021/6654169

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Abstract

The financial risk information diffuses through various kinds of social networks, such as Twitter and Facebook. Individuals transmit the financial risk information which can migrate among different platforms or forums. In this paper, we propose a financial risk information spreading model on metapopulation networks. The subpopulation represents a platform or forum, and individuals migrate among them to transmit the information. We use a discrete-time Markov chain approach to describe the spreading dynamics’ evolution and deduce the outbreak threshold point. We perform numerical simulation on artificial networks and discover that the financial risk information can be promoted once increasing the information transmission probability and active subpopulation fraction. The weight variance and migration probability cannot significantly affect the financial risk spreading size. The discrete-time Markov chain approach can reasonably predict the above phenomena.

Highlights

Many real-world systems in society, economy, and biological systems can be described as complex networks [1,2,3]. e nodes represent the element, and edges stand for the relationships among nodes
He/she becomes aware if he/she receives at least one piece of financial risk information from neighbors successfully. e contagion process in the depressing subpopulation (DS) is similar to that in the active subpopulation (AS). e only difference is that an unaware individual becoming aware should receive at least θ pieces of information from aware neighbors successfully. (ii) e travelling individuals return to his/her residence, and each aware individual becomes unaware with probability μ. e spreading dynamics evolve until the system reaches a dynamic steady state
When λ > λc, we find that 〈ρ〉 is a finite value, which indicates the global financial risk information outbreak. is phenomenon demonstrates that we can contain the financial risk information spreading by reducing the information transmission probability

Summary

Introduction

Many real-world systems in society, economy, and biological systems can be described as complex networks [1,2,3]. e nodes represent the element, and edges stand for the relationships among nodes. In financial network, the nodes stand for the financial institution, e.g., banks, and edges means the loan relationships among those financial institutions [4,5,6] With such description framework, the dynamics of financial behavior, risk spreading can be mapped into studying the dynamics on financial networks [7,8,9,10,11,12,13]. Some exhibit enthusiasm in the information, while others demonstrate depression To include this factor, Wang et al [41] proposed an informationspreading model on heterogeneous multiplex networks and discussed the system’s spreading size and critical points. Ere is still a mathematical model to describe the financial risk information-spreading dynamics on heterogeneous metapopulation networks to our vast knowledge.

Model Descriptions

Theoretical Analysis

Numerical Results’ Analysis

Conclusions