Influence of individual rationality on continuous double auction markets with networked traders

Authored by Junhuan Zhang

Date Published: 2018

DOI: 10.1016/j.physa.2017.12.098

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

This paper investigates the influence of individual rationality of buyers and sellers on continuous double auction market outcomes in terms of the proportion of boundedly-rational buyers and sellers. The individual rationality is discussed in a social network artificial stock market model by embedding network formation and information set. Traders automatically select the most profitable trading strategy based on individual and social learning of the profits and trading strategies of themselves and their neighbors, and submit orders to markets. The results show that (i) a higher proportion of boundedly-rational sellers induces a higher market price, higher sellers' profits and a higher market efficiency; (ii) a higher proportion of boundedly-rational sellers induces a lower number of trades and lower buyers' profits; (iii) a higher proportion of boundedly-rational buyers induces a lower market price, a lower number of trades, and lower sellers' profits; (iv) a higher proportion of boundedly-rational buyers induces higher buyers' profits and a higher market efficiency. (C) 2017 Elsevier B.V. All rights reserved.

Tags

Social networks Agent-based modeling behavior Expectations Fluctuations System Stock-market Double auctions Individual rationality Algorithmic trading Financial time-series