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Belief merging and revision under social influence: An explanation for the volatility clustering puzzle

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  • Siddiqi, Hammad

Abstract

A share price in a stock market can be thought of as arising out of an aggregation procedure. The price of a stock aggregates many individual beliefs into a collective one, the collective will of the market, so to speak. How does this aggregation come about? And is this aggregation fair in the sense that it correctly reflects the value? Furthermore,in the context of a stock market, it becomes immediately clear that belief merging cannot be separated from belief revision since investors in the market have a direct stake in what others think and clearly find it optimal to revise their beliefs in the light of the information about what others believe. We show that if investors are revising their beliefs not only after receiving new exogenous information but also after their social interactions with other investors and these revised beliefs are getting merged to generate the stock price under the accepted principles of finance (no arbitrage) then the resulting price dynamics explain a long standing puzzle in finance, the volatility clustering puzzle.

Suggested Citation

  • Siddiqi, Hammad, 2006. "Belief merging and revision under social influence: An explanation for the volatility clustering puzzle," MPRA Paper 657, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:657
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    as
    1. C. Chiarella & X-Z. He, 2001. "Asset price and wealth dynamics under heterogeneous expectations," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 509-526.
    2. Kandel, Eugene & Pearson, Neil D, 1995. "Differential Interpretation of Public Signals and Trade in Speculative Markets," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 831-872, August.
    3. Eugene Kandel & Ben-Zion Zilberfarb, 1999. "Differential Interpretation Of Information In Inflation Forecasts," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 217-226, May.
    4. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 95-132, February.
    5. Chiarella, Carl & He, Xue-Zhong, 2003. "Dynamics of beliefs and learning under aL-processes -- the heterogeneous case," Journal of Economic Dynamics and Control, Elsevier, vol. 27(3), pages 503-531, January.
    6. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Farmer, J. Doyne & Joshi, Shareen, 2002. "The price dynamics of common trading strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 149-171, October.
    9. Steven N. Durlauf, 1993. "Nonergodic Economic Growth," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 349-366.
    10. Robert Engle, 2004. "Risk and Volatility: Econometric Models and Financial Practice," American Economic Review, American Economic Association, vol. 94(3), pages 405-420, June.
    11. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    12. Rubinstein, Ariel, 1993. "On Price Recognition and Computational Complexity in a Monopolistic Model," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 473-484, June.
    13. Matthew Rabin, 2000. "Risk Aversion and Expected-Utility Theory: A Calibration Theorem," Econometrica, Econometric Society, vol. 68(5), pages 1281-1292, September.
    14. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    15. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    16. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    17. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    18. Gaunersdorfer, Andrea & Hommes, Cars H. & Wagener, Florian O.O., 2008. "Bifurcation routes to volatility clustering under evolutionary learning," Journal of Economic Behavior & Organization, Elsevier, vol. 67(1), pages 27-47, July.
    19. Paul Davidson, 1991. "Is Probability Theory Relevant for Uncertainty? A Post Keynesian Perspective," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 129-143, Winter.
    20. Ellison, Glenn & Fudenberg, Drew, 1993. "Rules of Thumb for Social Learning," Journal of Political Economy, University of Chicago Press, vol. 101(4), pages 612-643, August.
    21. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
    22. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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    More about this item

    Keywords

    Volatility clustering; Social influence; Agent based simulation; Anomaly;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets

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