Advertisement

Evolutionary and Institutional Economics Review

, Volume 14, Issue 2, pp 451–465 | Cite as

Investigation of the rule for investment diversification at the time of a market crash using an artificial market simulation

  • Isao Yagi
  • Atsushi Nozaki
  • Takanobu Mizuta
Article

Abstract

As financial products have grown in complexity and level of risk compounding in recent years, investors have come to find it difficult to assess investment risk. Furthermore, companies managing mutual funds are increasingly expected to perform risk control and thus prevent assumption of unforeseen risk by investors. A related revision to the mutual fund legal system in Japan led to establishing what is known as “the rule for investment diversification” in December 2014, without a clear discussion of its expected effects on market price formation having taken place. In this paper, we therefore, used an artificial market to investigate its effects on price formation in financial markets where investors must follow the rule at the time of a market crash that was caused by the collapse of the asset fundamental price. As results, we found that, in a two-asset market where investors had to follow the rule for investment diversification, when the fundamental price of one asset collapsed and its market price also collapsed, the other asset market price also fell.

Keywords

Artificial market Multi-agent based simulation The rule for investment diversification Leverage Financial market 

JEL Classification

C63 - Computational techniques Simulation modeling · G18 · Government Policy and Regulation · G01 · Financial crises 

Notes

Acknowledgements

This research was supported by JSPS KAKENHI Grant Number 15K01211.

Disclaimer

It should be noted that the opinions contained herein are solely those of the authors and do not necessarily reflect those of SPARX Asset Management Co., Ltd.

References

  1. Arthur W, Holland J, Lebaron B, Palmer R, Tayler P (1997) Asset pricing under endogenous expectations in an artificial stock market. The Economy as an Evolving Complex System II. Addison-Wesley, Menlo Park, pp. 15–44Google Scholar
  2. Chen S-H, Chang C-L, Du Y-R (2012) Agent-based economic models and econometrics. Knowl Eng Rev 27(2):187–219CrossRefGoogle Scholar
  3. Chiarella C, CIori G, Perellò J (2009) The impact of heterogeneous trading rules on the limit order book and order flows. J Econ Dyn Control 33(3):525–537Google Scholar
  4. Cont R (2001) Empirical properties of asset returns: stylized facts and statistical issues. Quant Financ 1:223–236CrossRefGoogle Scholar
  5. Cremers M, Petajisto A (2009) How active is your fund manager? A new measure that predicts performance. Rev Financ Stud 22(9):3329–3365CrossRefGoogle Scholar
  6. Cristelli M (2014) Complexity in financial markets: modeling psychological behavior in agent-based models and order book models. Springer, BerlinGoogle Scholar
  7. LeBaron B (2006) Agent-based financial markets: matching stylized facts with style. Post Walrasian macroeconomics beyound the dynamic stochastic general equilibrium model, vol 3. Cambridge University Press, Cambridge, pp 221–238Google Scholar
  8. Lux T, Marchesi M (1999) Scaling and criticality in a stochastic multiagent model of a financial market. Nature 397:498–500CrossRefGoogle Scholar
  9. Mizuta T, Izumi K, Yagi I, Yoshimura S (2014) Regulations’ effectiveness for market turbulence by large erroneous orders using multi agent simulation. In: Proc. of 2014 IEEE Computational Intelligence for Financial Engineering and Economics (CIFEr2014), pp 138–143Google Scholar
  10. Nakada T, Takadama K (2013) Analysis on the number of XCS agents in agent-based computational finance. In: Proc. of 2013 IEEE Conference on Computational Intelligence for Financial Engineering Economics (CIFEr2013), pp 8–13Google Scholar
  11. Nozaki A, Mizuta T, Yagi I (2015) Investigation of the rule for investment diversification using an artificial market. In: Proc. of The 15th Workshop on JSAI Special Interest Group on Financial Informatics, pp 34–40 (in Japanese)Google Scholar
  12. Sectional Committee of the Financial System of the Financial System Council (2009) Final report by “Working Group on Review of Investment Trust and Investment Corporation Regulation”. Financial Services Agency. Dec. http://www.fsa.go.jp/en/refer/councils/singie_kinyu/20121221.html
  13. Sewell M (2006) Characterization of financial time series. http://finance.martinsewell.com/stylized-facts/
  14. The Investment Trusts Association, Japan (2014) Investment Trusts in Japan 2014. http://www.toushin.or.jp/english/
  15. Yagi I, Mizuta T, Izumi K (2010) A study on the effectiveness of short-selling regulation in view of regulation period using artificial markets. Evol Inst Econ Rev 7(1):113–132CrossRefGoogle Scholar

Copyright information

© Japan Association for Evolutionary Economics 2017

Authors and Affiliations

  1. 1.Faculty of Information TechnologyKanagawa Institute of TechnologyAtsugiJapan
  2. 2.Course of Information and Computer SciencesGraduate School of Kanagawa Institute of TechnologyAtsugiJapan
  3. 3.SPARX Asset Management Co., Ltd.TokyoJapan

Personalised recommendations