Financial market opinion dynamics in complex networks
Complex network theory describes real-world systems through networks consisting of nodes and edges between nodes at the topological level by efficient abstract representations. Complex network-based modeling of financial market trader systems evolved from the majority-vote model can effectively char...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Thesis-Master by Coursework |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/175793 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Summary: | Complex network theory describes real-world systems through networks consisting of nodes and edges between nodes at the topological level by efficient abstract representations. Complex network-based modeling of financial market trader systems evolved from the majority-vote model can effectively characterize multiple properties of real financial markets. Previous research has used Erdős-Rényi random networks to characterize trader networks. Due to the scale-free feature of Barabási-Albert scale-free networks, in order to make the model more valuable for research on human social networks, this dissertation proposes and completes this financial market modeling using Barabási-Albert scale-free networks.
This dissertation finds that in financial market modeling, the critical noise value of the ordered-disordered phase transition in the standard majority-vote model corresponding to the Barabási-Albert scale-free networks is higher than that of the Erdős-Rényi random networks under the same average nodal degree. This dissertation analyzes the characteristics of the topologies of the Erdős-Rényi random networks and the Barabási-Albert scale-free networks, compares the degrees of instability tolerance of the system under the two networks, finds the reason why the critical noise value of the ordered-disordered phase transition in the standard majority-vote model corresponding to the Barabási-Albert scale-free networks is higher than that of the Erdős-Rényi random networks under the same average nodal degree from the perspective of the efficiency of the information diffusion with related proofs provided. |
---|