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Quantifying survey expectations: What's wrong with the probability approach?

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Listed author(s):
  • Breitung, Jörg
  • Schmeling, Maik

Abstract

We study a matched sample of individual stock market forecasts consisting of both qualitative and quantitative forecasts. This allows us to test for the quality of forecast quantification methods by comparing quantified qualitative forecasts with actual quantitative forecasts. Focusing mainly on the widely used quantification framework advocated by Carlson and Parkin (1975), the so-called "probability approach", we find that quantified expectations derived from the probability approach display a surprisingly weak correlation with reported quantitative stock return forecasts. We trace the reason for this low correlation to the importance of asymmetric and time-varying thresholds, whereas individual heterogeneity across forecasters seems to play a minor role. Hence, our results suggest that qualitative survey data may not be a very useful device to obtain quantitative forecasts and we suggest ways to remedy this problem when designing qualitative surveys.

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Paper provided by Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät in its series Hannover Economic Papers (HEP) with number dp-485.

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Length: 38 pages
Date of creation: Dec 2011
Handle: RePEc:han:dpaper:dp-485
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Keywords: Quantification; Stock Market Expectations; Probability Approach; Heterogeneity;

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Find related papers by JEL classification:
  • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
  • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
  • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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Cited by:

  1. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents' expectations. Different patterns of anticipation of the 2008 financial crisis”," IREA Working Papers 201511, University of Barcelona, Research Institute of Applied Economics, revised Mar 2015.
  2. Hutson, Mark & Joutz, Fred & Stekler, Herman, 2014. "Interpreting and evaluating CESIfo's World Economic Survey directional forecasts," Economic Modelling, Elsevier, vol. 38(C), pages 6-11.
  3. Lahiri, Kajal & Zhao, Yongchen, 2015. "Quantifying survey expectations: A critical review and generalization of the Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 31(1), pages 51-62.
  4. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming," IREA Working Papers 201711, University of Barcelona, Research Institute of Applied Economics, revised May 2017.
  5. Christian Seiler, 2015. "On the robustness of balance statistics with respect to nonresponse," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2014(2), pages 45-62.
  6. Kajal Lahiri & Yongchen Zhao, 2013. "Quantifying Heterogeneous Survey Expectations: The Carlson-Parkin Method Revisited," Discussion Papers 13-08, University at Albany, SUNY, Department of Economics.

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