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Mass Psychology in Action: Identification of Social Interaction Effects in the German Stock Market

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  • Thomas Lux

Abstract

We use weekly survey data on short-term and medium-term sentiment of German investors to estimate the parameters of a stochastic model of opinion dynamics. The bivariate nature of our data set also allows us to explore the interaction between the two hypothesized opinion formation processes, while consideration of the simultaneous weekly changes of the stock index DAX enables us to study the influence of sentiment on returns within a behavioral model of boundedly rational traders. Technically, we extend the maximum likelihood framework for parameter estimation in agent-based models introduced by Lux (2009a) by generalizing it to bivariate and trivariate settings. As it turns out, short-term sentiment is governed by strong social interaction with abrupt changes of direction while medium-term sentiment is a slowly moving process with more moderate social interaction. The trivariate model can potentially predict stock returns out-of-sample on the base of medium-run sentiment at least if an apparently spurious influence from short-run sentiment is discarded

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Bibliographic Info

Paper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number 1514.

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Length: 42 pages
Date of creation: Apr 2009
Date of revision:
Handle: RePEc:kie:kieliw:1514

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Keywords: Opinion formation; social interaction; investor sentiment;

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References

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  1. Brown, Gregory W. & Cliff, Michael T., 2004. "Corrigendum to "Investor sentiment and the near-term stock market" [J. Empirical Finance 11 (2004) 1-27]," Journal of Empirical Finance, Elsevier, Elsevier, vol. 11(4), pages 627-628, September.
  2. Friedrich Wagner & Thomas Lux & Simone Alfarano, 2005. "Time-Variation of Higher Moments in a Financial Market with Heterogeneous Agents: An Analytical Approach," Working Papers, Warwick Business School, Finance Group wp05-02, Warwick Business School, Finance Group.
  3. Thomas Lux, 2008. "Sentiment Dynamics and Stock Returns: The Case of the German Stock Market," Kiel Working Papers 1470, Kiel Institute for the World Economy.
  4. Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0326, National Bureau of Economic Research, Inc.
  5. Kling, Gerhard & Gao, Lei, 2008. "Chinese institutional investors' sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, Elsevier, vol. 18(4), pages 374-387, October.
  6. 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, Elsevier, vol. 33(2), pages 143-165, January.
  7. Wang, Yaw-Huei & Keswani, Aneel & Taylor, Stephen J., 2006. "The relationships between sentiment, returns and volatility," International Journal of Forecasting, Elsevier, Elsevier, vol. 22(1), pages 109-123.
  8. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, University of Chicago Press, vol. 78(2), pages 405-440, March.
  9. Creedy, John & Lye, Jenny & Martin, Vance L, 1996. "A Non-linear Model of the Real US-UK Exchange Rate," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(6), pages 669-86, Nov.-Dec..
  10. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 105(431), pages 881-96, July.
  11. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, Elsevier, vol. 11(1), pages 1-27, January.
  12. Bernd Pape, 2007. "Asset allocation and multivariate position based trading," Journal of Economic Interaction and Coordination, Springer, Springer, vol. 2(2), pages 163-193, December.
  13. Lux, T. & M. Marchesi, . "Volatility Clustering in Financial Markets: A Micro-Simulation of Interacting Agents," Discussion Paper Serie B, University of Bonn, Germany 437, University of Bonn, Germany, revised Jul 1998.
  14. Kirman, Alan, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, MIT Press, MIT Press, vol. 108(1), pages 137-56, February.
  15. Lux, T. & M. Marchesi, . "Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market," Discussion Paper Serie B, University of Bonn, Germany 438, University of Bonn, Germany, revised Jul 1998.
  16. Yacine Ait-Sahalia, 1995. "Testing Continuous-Time Models of the Spot Interest Rate," NBER Working Papers 5346, National Bureau of Economic Research, Inc.
  17. Horst, Ulrich & Rothe, Christian, 2008. "Queuing, Social Interactions, And The Microstructure Of Financial Markets," Macroeconomic Dynamics, Cambridge University Press, Cambridge University Press, vol. 12(02), pages 211-233, April.
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Cited by:
  1. Lux, Thomas, 2008. "Rational forecasts or social opinion dynamics? Identification of interaction effects in a business climate survey," Economics Working Papers 2008,07, Christian-Albrechts-University of Kiel, Department of Economics.

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