An agent-based approach to financial stylized facts

Tetsuya Shimokawa*, Kyoko Suzuki, Tadanobu Misawa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

An important challenge of the financial theory in recent years is to construct more sophisticated models which have consistencies with as many financial stylized facts that cannot be explained by traditional models. Recently, psychological studies on decision making under uncertainty which originate in Kahneman and Tversky's research attract a lot of interest as key factors which figure out the financial stylized facts. These psychological results have been applied to the theory of investor's decision making and financial equilibrium modeling. This paper, following these behavioral financial studies, would like to propose an agent-based equilibrium model with prospect theoretical features of investors. Our goal is to point out a possibility that loss-averse feature of investors explains vast number of financial stylized facts and plays a crucial role in price formations of financial markets. Price process which is endogenously generated through our model has consistencies with, not only the equity premium puzzle and the volatility puzzle, but great kurtosis, asymmetry of return distribution, auto-correlation of return volatility, cross-correlation between return volatility and trading volume. Moreover, by using agent-based simulations, the paper also provides a rigorous explanation from the viewpoint of a lack of market liquidity to the size effect, which means that small-sized stocks enjoy excess returns compared to large-sized stocks.

Original languageEnglish
Pages (from-to)207-225
Number of pages19
JournalPhysica A: Statistical Mechanics and its Applications
Volume379
Issue number1
DOIs
StatePublished - 2007/06/01

Keywords

  • Agent-based simulation
  • Financial stylized facts
  • Loss-aversion
  • Market liquidity
  • Prospect theory

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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