Abstract
We propose an artificial financial market where three types of investors compete. Value investors, that use information to align the asset’s price with it’s value are called YODA. SITH is our name for the investors who hold information but decide not to use it right away, and instead act as non-informed investors. All other agents trade without information. We show that SITH agents can make better risk-adjusted gains than YODA agents. Consequently we prove that informed investors have incentives to withhold information and act like chartist traders. Our observations lead us to state that financial markets are consistently overpricing assets and can be regarded as seldom efficient.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
This first price can be considered as an exogenous IPO price.
- 2.
As used by the Australian Stock Exchange and explained in http://www.asx.com.au/products/calculate-open-close-prices.htm
- 3.
By setting the asset’s fundamental growth to 0 % we ensure that investors can make money only at the expense of others, and not from fundamental growth.
References
Allen F, Gale D (2000) Asset price bubbles and monetary policy. Center for Financial Institutions working papers, Wharton School Center for Financial Institutions, University of Pennsylvania, May, No. 01–26
Beaufils B, Brandouy O, Ma L, Mathieu P (2010) Simuler pour comprendre: un éclairage sur les dynamiques de marchés financiers à l’aide des systèmes multi agents. Systemes d’Information et management 14(4):51–70
Beja A, Goldman MB (1980) On the dynamic behavior of prices in disequilibrium. J Financ 35:235–248
Farmer JD, Joshi S (2002) The price dynamics of common trading strategies. J Econ Behav Organ 49:149–171
Grossman SJ, Stiglitz JE (1980) On the impossibility of informationally efficient markets. Am Econ Rev 70(3):393–408
Kahneman D, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica 47(2):263–291
LeBaron B (1999) Evolution and time horizons in an agent-based stock market. Macroecon Dyn 5:225–254
LeBaron B (2006) Agent-based computational finance. In: Tesfatsion L, Judd KL (eds) Handbook of computational economics, vol. 2. Elsevier, North-Holland, pp 1187–1232
LiCalzi M, Pellizzari P (2007) Simple market protocols for efficient risk sharing. J Econ Dyn Control 31(11):3568–3590
Muth JF (1961) Rational expectations and the theory of price movement. Econometrica 29(3):315–335
Toth B, Scalas E (2007) The value of information in financial markets: an agent-based simulation. Papers 0712.2687, arXiv.org
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Stanciu-Viziteu, L.D. (2014). Who Wins: Yoda or Sith? A Proof that Financial Markets Are Seldom Efficient. In: Leitner, S., Wall, F. (eds) Artificial Economics and Self Organization. Lecture Notes in Economics and Mathematical Systems, vol 669. Springer, Cham. https://doi.org/10.1007/978-3-319-00912-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-00912-4_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00911-7
Online ISBN: 978-3-319-00912-4
eBook Packages: Business and EconomicsEconomics and Finance (R0)