The Stock Market Model with Delayed Information Impact from a Socioeconomic View
| Autor: | Guiyuan Shi, Zhiting Wang, Mingsheng Shang, Yuxia Zhang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Collective behavior
Science QC1-999 General Physics and Astronomy Astrophysics financial complexity 01 natural sciences Article 010305 fluids & plasmas Microeconomics 0103 physical sciences Economics 010306 general physics stock correlation Econophysics Physics Financial market Collective intelligence collective intelligence emergent property QB460-466 Core (game theory) econophysics Information and Communications Technology Financial modeling Stock market detrended cross-correlation analysis |
| Zdroj: | Entropy Volume 23 Issue 7 Entropy, Vol 23, Iss 893, p 893 (2021) |
| ISSN: | 1099-4300 |
| DOI: | 10.3390/e23070893 |
| Popis: | Finding the critical factor and possible “Newton’s laws” in financial markets has been an important issue. However, with the development of information and communication technologies, financial models are becoming more realistic but complex, contradicting the objective law “Greatest truths are the simplest.” Therefore, this paper presents an evolutionary model independent of micro features and attempts to discover the most critical factor. In the model, information is the only critical factor, and stock price is the emergence of collective behavior. The statistical properties of the model are significantly similar to the real market. It also explains the correlations of stocks within an industry, which provides a new idea for studying critical factors and core structures in the financial markets. |
| Databáze: | OpenAIRE |
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