Information driving force and its application in agent-based modeling

Authored by Bo Zheng, Xiong-Fei Jiang, Yan Li, Ting-Ting Chen

Date Published: 2018

DOI: 10.1016/j.physa.2017.12.128

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Exploring the scientific impact of online big-data has attracted much attention of researchers from different fields in recent years. Complex financial systems are typical open systems profoundly influenced by the external information. Based on the large-scale data in the public media and stock markets, we first define an information driving force, and analyze how it affects the complex financial system. The information driving force is observed to be asymmetric in the bull and bear market states. As an application, we then propose an agent-based model driven by the information driving force. Especially, all the key parameters are determined from the empirical analysis rather than from statistical fitting of the simulation results. With our model, both the stationary properties and non-stationary dynamic behaviors are simulated. Considering the mean-field effect of the external information, we also propose a few-body model to simulate the financial market in the laboratory. (C) 2017 Elsevier B.V. All rights reserved.

Tags

econophysics behavior Complex systems systems Volatility Financial-markets Agent-based modeling Information driving force Experimental asset markets