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Real‐Time Forecasting and Political Stock Market Anomalies: Evidence for the United States

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  • Martin T. Bohl
  • Jörg Döpke
  • Christian Pierdzioch

Abstract

Using monthly data from 1953 to 2003, we apply a real‐time modeling approach to investigate the implications of U.S. political stock market anomalies for forecasting excess stock returns in real‐time. Our empirical findings show that political variables, chosen on the basis of widely used model‐selection criteria, are often included in real‐time forecasting models. However, political variables do not contribute systematically to improving the performance of simple trading rules. For this reason, political stock market anomalies are not necessarily an indication of market inefficiency.

Suggested Citation

  • Martin T. Bohl & Jörg Döpke & Christian Pierdzioch, 2008. "Real‐Time Forecasting and Political Stock Market Anomalies: Evidence for the United States," The Financial Review, Eastern Finance Association, vol. 43(3), pages 323-335, August.
    • Handle: RePEc:bla:finrev:v:43:y:2008:i:3:p:323-335
    DOI: 10.1111/j.1540-6288.2008.00196.x
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    Cited by:

    1. Gupta, Rangan & Pierdzioch, Christian & Selmi, Refk & Wohar, Mark E., 2018. "Does partisan conflict predict a reduction in US stock market (realized) volatility? Evidence from a quantile-on-quantile regression model☆," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 87-96.
    2. Andrew C. Worthington, 2009. "Political Cycles in the Australian Stock Market since Federation," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 42(4), pages 397-409, December.
    3. Ray R. Sturm, 2016. "Is There a Presidential Election Cycle in Firm Financials?," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 1-18, June.
    4. Rangan Gupta & Christian Pierdzioch & Refk Selmi & Mark E. Wohar, 2017. "Does Partisan Conflict Predict a Reduction in US Stock Market (Realized) Volatility? Evidence from a Quantile-on-Quantile Regression Model," Working Papers 201744, University of Pretoria, Department of Economics.
    5. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2014. "The international business cycle and gold-price fluctuations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 292-305.

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