Name
Title | ||
|---|---|---|
A Bibliometric Analysis on Agent-Based Models in Finance: Identification of Community Clusters and Future Research Trends |
Abstract | ||
|---|---|---|
Agent-based models are computational approaches used to reproduce the interactions between economic agents. These models are widely applied in many contexts to get deeper understanding about agents' behaviors within complex systems. In this paper, we provide a bibliometric analysis about agent-based models in finance and, considering bibliographic coupling, we identify the presence of two distinct clusters of research communities, i.e., financial economics and econophysics. Cluster-specific thematic analyses are conducted to understand if the two communities are characterized by different emerging and motor topics. By highlighting several differences in the clusters, we also show the two research communities specialized in different specific topics. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1155/2022/4741566 | COMPLEXITY |
DocType | Volume | ISSN |
Journal | 2022 | 1076-2787 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan E. Trinidad E. Segovia | 1 | 0 | 0.34 |
| Fabrizio Di Sciorio | 2 | 0 | 0.68 |
| Raffaele Mattera | 3 | 0 | 0.34 |
| Maria Spano | 4 | 0 | 0.34 |