Network formation in a multi-asset artificial stock market

Authored by Songtao Wu, Jianmin He, Chao Wang, Shouwei Li

Date Published: 2018

DOI: 10.1140/epjb/e2018-80384-6

Sponsors: Chinese National Natural Science Foundation Humanities and Social Sciences Foundation of Ministry of Education of the PR China

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

A multi-asset artificial stock market is developed. In the market, stocks are assigned to a number of sectors and traded by heterogeneous investors. The mechanism of continuous double auction is employed to clear order book and form daily closed prices. Simulation results of prices at the sector level show an intra-sector similarity and inter-sector distinctiveness, and returns of individual stocks have stylized facts that are ubiquitous in the real-world stock market. We find that the market risk factor has critical impact on both network topology transition and connection formation, and that sector risk factors account for the formation of intra-sector links and sector-based local interaction. In addition, the number of community in threshold-based networks is correlated negatively and positively with the value of correlation coefficients and the ratio of intra-sector links, which are respectively determined by intensity of sector risk factors and the number of sectors.

Tags

Agent-based models time-series emergence Long memory Volatility Overconfidence Financial-markets Returns Spanning tree Ising-model