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Nonlinear Expectations in Speculative Markets

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  • Reitz, Stefan
  • Rülke, Jan
  • Stadtmann, Georg

Abstract

Heterogenous agents models have proven to be capable of explaining price dynamics on speculative markets. In general, this is achieved by allowing time series properties to be state dependent. This paper investigates whether market participants' expectations already reflect these time varying nonlinearities. The empirical results are based on a new data set from the European Central Bank Survey of Professional Forecasters on oil price expectations. In particular, we find that forecasters form destabilizing expectations in the neighborhood of the fundamental value, whereas expectations tend to be stabilizing in the presence of substantial oil price misalignment.

Suggested Citation

  • Reitz, Stefan & Rülke, Jan & Stadtmann, Georg, 2012. "Nonlinear Expectations in Speculative Markets," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62045, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc12:62045
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Pierdzioch, Christian & Reitz, Stefan & Ruelke, Jan-Christoph, 2014. "Heterogeneous forecasters and nonlinear expectation formation in the US stock market," Kiel Working Papers 1947, Kiel Institute for the World Economy (IfW Kiel).
    2. Goldbaum, David & Zwinkels, Remco C.J., 2014. "An empirical examination of heterogeneity and switching in foreign exchange markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 667-684.
    3. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
    4. Leppin, Julian Sebstian, 2014. "The Relation Between Overreaction in Forecasts and Uncertainty: A Nonlinear Approach," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100284, Verein für Socialpolitik / German Economic Association.
    5. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," EconomiX Working Papers 2015-17, University of Paris Nanterre, EconomiX.
    6. Leppin, Julian Sebastian, 2014. "The relation between overreaction in forecasts and uncertainty: A nonlinear approachvon," HWWI Research Papers 158, Hamburg Institute of International Economics (HWWI).
    7. Czudaj, Robert L., 2019. "Crude oil futures trading and uncertainty," Energy Economics, Elsevier, vol. 80(C), pages 793-811.
    8. Pierdzioch, Christian & Risse, Marian & Rohloff, Sebastian, 2016. "A quantile-boosting approach to forecasting gold returns," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 38-55.
    9. Andreas Fritz & Michael Stein & Christoph Weber, 2015. "The Role of Heterogeneous Agents in Fuel Markets: Testing Tales of Speculators in Oil Markets," EWL Working Papers 1505, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Aug 2015.
    10. Imane El Ouadghiri, 2015. "Heterogeneity in Macroeconomic News Expectations: A disaggregate level analysis," Working Papers hal-04141409, HAL.

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    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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