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Understanding Financial Market States Using an Artificial Double Auction Market SCIE SCOPUS

Title
Understanding Financial Market States Using an Artificial Double Auction Market
Authors
Yim, KOh, GKim, S
Date Issued
2016-03-31
Publisher
PUBLIC LIBRARY SCIENCE
Abstract
The ultimate value of theories describing the fundamental mechanisms behind asset prices in financial systems is reflected in the capacity of such theories to understand these systems. Although the models that explain the various states of financial markets offer substantial evidence from the fields of finance, mathematics, and even physics, previous theories that attempt to address the complexities of financial markets in full have been inadequate. We propose an artificial double auction market as an agent-based model to study the origin of complex states in financial markets by characterizing important parameters with an investment strategy that can cover the dynamics of the financial market. The investment strategies of chartist traders in response to new market information should reduce market stability based on the price fluctuations of risky assets. However, fundamentalist traders strategically submit orders based on fundamental value and, thereby stabilize the market. We construct a continuous double auction market and find that the market is controlled by the proportion of chartists, P-c. We show that mimicking the real state of financial markets, which emerges in real financial systems, is given within the range P-c = 0.40 to P-c = 0.85; however, we show that mimicking the efficient market hypothesis state can be generated with values less than P-c = 0.40. In particular, we observe that mimicking a market collapse state is created with values greater than P-c = 0.85, at which point a liquidity shortage occurs, and the phase transition behavior is described at P-c = 0.85.
Keywords
ORDER-DRIVEN MARKET; BID-ASK SPREAD; STOCK-MARKET; STATISTICAL PROPERTIES; LOSS AVERSION; PRICE IMPACT; LONG-MEMORY; INFORMATION; RETURNS; HETEROGENEITY
URI
https://oasis.postech.ac.kr/handle/2014.oak/29987
DOI
10.1371/JOURNAL.PONE.0152608
ISSN
1932-6203
Article Type
Article
Citation
PLOS ONE, vol. 11, no. 3, 2016-03-31
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