Impact of information cost and switching of trading strategies in an artificial stock market
Yi-Fang Liu,
Wei Zhang,
Chao Xu,
J{\o}rgen Vitting Andersen and
Hai-Chuan Xu
Papers from arXiv.org
Abstract:
This paper studies the switching of trading strategies and its effect on the market volatility in a continuous double auction market. We describe the behavior when some uninformed agents, who we call switchers, decide whether or not to pay for information before they trade. By paying for the information they behave as informed traders. First we verify that our model is able to reproduce some of the stylized facts in real financial markets. Next we consider the relationship between switching and the market volatility under different structures of investors. We find that there exists a positive relationship between the market volatility and the percentage of switchers. We therefore conclude that the switchers are a destabilizing factor in the market. However, for a given fixed percentage of switchers, the proportion of switchers that decide to buy information at a given moment of time is negatively related to the current market volatility. In other words, if more agents pay for information to know the fundamental value at some time, the market volatility will be lower. This is because the market price is closer to the fundamental value due to information diffusion between switchers.
Date: 2013-11, Revised 2014-07
New Economics Papers: this item is included in nep-cta, nep-fmk and nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://arxiv.org/pdf/1311.4274 Latest version (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1311.4274
Access Statistics for this paper
More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().