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Information and efficiency in political stock markets: using computerized markets to predict election results

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  • Gregor Bruggelambert

Abstract

This study concentrates on four computerized political markets in Germany between 1990 and 1998. While this new method for the prediction of election events worked quite well in the USA it did not perform as well in Germany. Searching for the causes of this distinction it is shown that, in contrast to the findings of Forsythe et al. (1992), (i) extraordinary profits were achieved less by people who took advantage of other people's anomalies than by those people who acquired an advantage from the existence of asymmetric information, (ii) the marginal trader hypothesis does not hold when applied to German markets, and that (iii) traders relied on public opinion polls. It is argued that these distinctions are caused by the differences in the German and the US voting systems. Additionally, it is shown that to a certain extent (iv) election markets were able to predict the contemporary mood of the electorate without the help of public opinion polls, (v) first of all the informed traders used public opinion polls as a source of information, and (vi) prices themselves became a source of information on which expectations were based.

Suggested Citation

  • Gregor Bruggelambert, 2004. "Information and efficiency in political stock markets: using computerized markets to predict election results," Applied Economics, Taylor & Francis Journals, vol. 36(7), pages 753-768.
  • Handle: RePEc:taf:applec:v:36:y:2004:i:7:p:753-768
    DOI: 10.1080/0003684042000217364
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    References listed on IDEAS

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    1. Jacobsen, Ben & Potters, Jan & Schram, Arthur & van Winden, Frans & Wit, Jorgen, 2000. "(In)accuracy of a European political stock market: The influence of common value structures," European Economic Review, Elsevier, vol. 44(2), pages 205-230, February.
    2. Beckmann, Klaus & Werding, Martin, 1996. "'Passauer Wahlborse': Information Processing in a Political Market Experiment," Kyklos, Wiley Blackwell, vol. 49(2), pages 171-204.
    3. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    4. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    5. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    6. Forsythe, Robert & Rietz, Thomas A. & Ross, Thomas W., 1999. "Wishes, expectations and actions: a survey on price formation in election stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 39(1), pages 83-110, May.
    7. S. Baranzoni & P. Bianchi & L. Lambertini, 2000. "Multiproduct Firms, Product Differentiation, and Market Structure," Working Papers 368, Dipartimento Scienze Economiche, Universita' di Bologna.
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    Cited by:

    1. Chin-Tsai Lin & Yi-Hsien Wang, 2005. "An Analysis of Political Changes on Nikkei 225 Stock Returns and Volatilities," Annals of Economics and Finance, Society for AEF, vol. 6(1), pages 169-183, May.
    2. Yi-Hsien Wang & Chung-Chu Chuang, 2009. "Selecting the portfolio investment strategy under political structure change in United States," Quality & Quantity: International Journal of Methodology, Springer, vol. 43(5), pages 845-854, September.
    3. Chung-Chu Chuang & Yi-Hsien Wang, 2009. "Developed stock market reaction to political change: a panel data analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 43(6), pages 941-949, November.

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