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Predicting stock price movements: regressions versus economists

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  • Paul Soderlind

Abstract

The forecasting performance of the Livingston survey and traditional prediction models of stock prices is analysed. The survey forecasts look similar to those from a 'too large' prediction model: poor out-of-sample performance and too sensitive to recent and irrelevant information.

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  • Paul Soderlind, 2010. "Predicting stock price movements: regressions versus economists," Applied Economics Letters, Taylor & Francis Journals, vol. 17(9), pages 869-874.
    • Handle: RePEc:taf:apeclt:v:17:y:2010:i:9:p:869-874
    DOI: 10.1080/17446540802584871
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    Cited by:

    1. Silvija Vlah Jerić & Mihovil Anđelinović, 2019. "Evaluating Croatian stock index forecasts," Empirical Economics, Springer, vol. 56(4), pages 1325-1339, April.
    2. A. Belenky & L. Egorova, 2016. "Two approaches to modeling the interaction of small and medium price-taking traders with a stock exchange by mathematical programming techniques," Papers 1610.05703, arXiv.org.
    3. Rangvid, Jesper & Schmeling, Maik & Schrimpf, Andreas, 2013. "What do professional forecasters' stock market expectations tell us about herding, information extraction and beauty contests?," Journal of Empirical Finance, Elsevier, vol. 20(C), pages 109-129.
    4. Pierdzioch, Christian & Rülke, Jan-Christoph, 2012. "Forecasting stock prices: Do forecasters herd?," Economics Letters, Elsevier, vol. 116(3), pages 326-329.
    5. Björn Fastrich & Peter Winker, 2014. "Combining Forecasts with Missing Data: Making Use of Portfolio Theory," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 127-152, August.

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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