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Market efficiency, strategies and incomes of heterogeneously informed investors in a social network environment

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  • Wang, Zongrun
  • Chen, Songsheng

Abstract

This study introduces a two factor interaction function and a strategy improvement mechanism to construct a heterogeneous information model in a social network environment. Due to the different environmental characteristics of offline and online communication, the Watts Strogatz small world network and the modified Barabási Albert network were used to simulate real-world offline and online environments, respectively, and a market without social networking is added to facilitate comparison. We conducted the market simulation under three different network environments. With simulated market data, the evolution of the investor's strategy, net income, and market efficiency was analyzed. The results show that after three markets reached equilibrium, the number of insider investors and the information cost is the highest in the online environment and the lowest in the noninteractive environment, while market efficiency shows the converse pattern. With social interaction, private signals purchased by investors are publicized in their social circles. This pattern could result in a herd effect of decision making under a false belief, followed by a decrease in market efficiency and an increase in the insider investor ratio. Investors in an online environment have more neighbors and more interlaced social ties than investors in an offline environment. Thus, the increase in information channels facilitates the transformation of private signals into public ones, which further reduces market efficiency and increases the number of insider investors.

Suggested Citation

  • Wang, Zongrun & Chen, Songsheng, 2019. "Market efficiency, strategies and incomes of heterogeneously informed investors in a social network environment," Journal of Economic Behavior & Organization, Elsevier, vol. 158(C), pages 15-32.
  • Handle: RePEc:eee:jeborg:v:158:y:2019:i:c:p:15-32
    DOI: 10.1016/j.jebo.2018.10.017
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    References listed on IDEAS

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    1. Shive, Sophie, 2010. "An Epidemic Model of Investor Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(01), pages 169-198, February.
    2. Jürgen Huber & Matthias Sutter & Michael Kirchler, 2004. "Is more information always better? Experimental financial markets with asymmetric information," Papers on Strategic Interaction 2005-13, Max Planck Institute of Economics, Strategic Interaction Group.
    3. Paolo Colla & Antonio Mele, 2010. "Information Linkages and Correlated Trading," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 203-246, January.
    4. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    5. De Bondt, Werner F M & Thaler, Richard, 1985. " Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    6. Florian Hauser & Jürgen Huber & Bob Kaempff, 2015. "Costly Information in Markets with Heterogeneous Agents: A Model with Genetic Programming," Computational Economics, Springer;Society for Computational Economics, vol. 46(2), pages 205-229, August.
    7. Michael Hanke & Klaus Schredelseker, 2010. "Index funds should be expected to underperform the index," Applied Economics Letters, Taylor & Francis Journals, vol. 17(10), pages 991-994.
    8. Pfeifer, Christian & Schredelseker, Klaus & Seeber, Gilg U.H., 2009. "On the negative value of information in informationally inefficient markets: Calculations for large number of traders," European Journal of Operational Research, Elsevier, vol. 195(1), pages 117-126, May.
    9. Iori, Giulia, 2002. "A microsimulation of traders activity in the stock market: the role of heterogeneity, agents' interactions and trade frictions," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 269-285, October.
    10. Battiston, Pietro & Stanca, Luca, 2015. "Boundedly rational opinion dynamics in social networks: Does indegree matter?," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 400-421.
    11. H. Leibenstein, 1950. "Bandwagon, Snob, and Veblen Effects in the Theory of Consumers' Demand," The Quarterly Journal of Economics, Oxford University Press, vol. 64(2), pages 183-207.
    12. Pietro Battiston & Luca Stanca, 2014. "Boundedly Rational Opinion Dynamics in Directed Social Networks: Theory and Experimental Evidence," Working Papers 267, University of Milano-Bicocca, Department of Economics, revised Jan 2014.
    13. Veronika K. Pool & Noah Stoffman & Scott E. Yonker, 2015. "The People in Your Neighborhood: Social Interactions and Mutual Fund Portfolios," Journal of Finance, American Finance Association, vol. 70(6), pages 2679-2732, December.
    14. Florian Hauser & Bob Kaempff, 2013. "Evolution of trading strategies in a market with heterogeneously informed agents," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 575-607, July.
    15. Cui, Zhiwei & Wang, Rui, 2016. "Collaboration in networks with randomly chosen agents," Journal of Economic Behavior & Organization, Elsevier, vol. 129(C), pages 129-141.
    16. Bing Han & Liyan Yang, 2013. "Social Networks, Information Acquisition, and Asset Prices," Management Science, INFORMS, vol. 59(6), pages 1444-1457, June.
    17. repec:eee:jfinec:v:125:y:2017:i:1:p:26-47 is not listed on IDEAS
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    More about this item

    Keywords

    Online and offline social environments; Heterogeneous information; Market efficiency; Market net return;

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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