Advanced Search
MyIDEAS: Login to save this article or follow this journal

Information contagion within small worlds and changes in kurtosis and volatility in financial prices

Contents:

Author Info

  • Bowden, Mark P.

Abstract

An agent based artificial market is developed to determine the impact of the interaction between investors on prices. It consists of sentiment investors, a single fundamental investor and a market maker. Sentiment investors live in a small world network and have limited liquidity. They trade based on their assessment of the future direction of the market. Consistent with the social learning literature, there are two types of sentiment investors; social learners and experts. Experts only consider private information while social learners also consider the views of neighbours. It is found that the interaction between the agents generate kurtosis and persistence characteristics of volatility in returns. In addition, the level of kurtosis and volatility depends on the inter-connectedness of the network as well as the number of experts and the number of connections from these experts to social learners. Cluster coefficient and characteristic path length analysis show that kurtosis and volatility are lowest within the small world region of the network. This effect is negated as the number of experts increases beyond a threshold.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.sciencedirect.com/science/article/pii/S0164070412000055
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Elsevier in its journal Journal of Macroeconomics.

Volume (Year): 34 (2012)
Issue (Month): 2 ()
Pages: 553-566

as in new window
Handle: RePEc:eee:jmacro:v:34:y:2012:i:2:p:553-566

Contact details of provider:
Web page: http://www.elsevier.com/locate/inca/622617

Related research

Keywords: Agent based financial markets; Network economics; Information contagion; Volatility; Kurtosis;

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
  2. Mark Bowden & Stuart McDonald, 2008. "The Impact of Interaction and Social Learning on Aggregate Expectations," Computational Economics, Society for Computational Economics, vol. 31(3), pages 289-306, April.
  3. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-96, July.
  4. Andrew W. Lo, 1989. "Long-term Memory in Stock Market Prices," NBER Working Papers 2984, National Bureau of Economic Research, Inc.
  5. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186 Elsevier.
  6. Dieci, Roberto & Westerhoff, Frank, 2010. "Heterogeneous speculators, endogenous fluctuations and interacting markets: A model of stock prices and exchange rates," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 743-764, April.
  7. Shiller, 021Robert J. & Pound, John, 1989. "Survey evidence on diffusion of interest and information among investors," Journal of Economic Behavior & Organization, Elsevier, vol. 12(1), pages 47-66, August.
  8. Michael Milakovic & Simone Alfarano, 2007. "Should Network Structure Matter in Agent-Based Finance?," Working Papers wp07-02, Warwick Business School, Finance Group.
  9. Brock, W.A. & Hommes, C.H., 1996. "Hetergeneous Beliefs and Routes to Chaos in a Simple Asset Pricing Model," Working papers 9621, Wisconsin Madison - Social Systems.
  10. Day, R. & Huang, W., 1988. "Bulls, Bears And Market Sheep," Papers m8822, Southern California - Department of Economics.
  11. Malkiel, Burton & Campbell, John & Lettau, Martin & Xu, Yexiao, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Scholarly Articles 3128707, Harvard University Department of Economics.
  12. Chiarella, C. & He, X.-Z. & Hommes, C.H., 2004. "A Dynamic Analysis of Moving Average Rules," CeNDEF Working Papers 04-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  13. Chang, Sheng-Kai, 2007. "A simple asset pricing model with social interactions and heterogeneous beliefs," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1300-1325, April.
  14. Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2004. "Social Interaction and Stock-Market Participation," Journal of Finance, American Finance Association, vol. 59(1), pages 137-163, 02.
  15. J. Doyne Farmer & Shareen Joshi, 2000. "The price dynamics of common trading strategies," Papers cond-mat/0012419, arXiv.org.
  16. Jeffrey R. Brown & Zoran Ivkovic & Paul A. Smith & Scott Weisbenner, 2008. "Neighbors Matter: Causal Community Effects and Stock Market Participation," Journal of Finance, American Finance Association, vol. 63(3), pages 1509-1531, 06.
  17. Steven X. Wei & Chu Zhang, 2006. "Why Did Individual Stocks Become More Volatile?," The Journal of Business, University of Chicago Press, vol. 79(1), pages 259-292, January.
  18. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233 Elsevier.
  19. Bischi, Gian-Italo & Gallegati, Mauro & Gardini, Laura & Leombruni, Roberto & Palestrini, Antonio, 2006. "Herd Behavior And Nonfundamental Asset Price Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 10(04), pages 502-528, September.
  20. Manzan, S. & Westerhoff, F., 2002. "Heterogeneous Expectations, Exchange Rate Dynamics and Predictability," CeNDEF Working Papers 02-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  21. Carl Chiarella & Roberto Dieci & Laura Gardini, 2005. "The Dynamic Interaction of Speculation and Diversification," Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(1), pages 17-52.
  22. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
  23. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.
  24. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Zhao, Laijun & Wang, Jiajia & Huang, Rongbing & Cui, Hongxin & Qiu, Xiaoyan & Wang, Xiaoli, 2014. "Sentiment contagion in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 17-23.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:eee:jmacro:v:34:y:2012:i:2:p:553-566. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.