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Forecasting the Correlation Structure of German Stock Returns: A Test of Firm‐Specific Factor Models

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  • Manfred Steiner
  • Martin Wallmeier

Abstract

This paper evaluates the performance of various factor models with firm‐specific variables in forecasting correlation matrices at the German stock market. We investigate forecasts of correlations for a comprehensive sample and a sample of blue chips and analyse the impact of stock market crashes on the forecasting accuracy. Our empirical results show that the multi‐factor models do not generally produce better forecasts than ‘naive’ models. Specifically, the traditional industry mean model significantly outperforms all other techniques in most of the time periods.

Suggested Citation

  • Manfred Steiner & Martin Wallmeier, 1999. "Forecasting the Correlation Structure of German Stock Returns: A Test of Firm‐Specific Factor Models," European Financial Management, European Financial Management Association, vol. 5(1), pages 85-102, March.
  • Handle: RePEc:bla:eufman:v:5:y:1999:i:1:p:85-102
    DOI: 10.1111/1468-036X.00081
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    Cited by:

    1. Bonga-Bonga, Lumengo & Mwamba, Muteba, 2015. "A multivariate model for the prediction of stock returns in an emerging market: A comparison of parametric and non-parametric models," MPRA Paper 62028, University Library of Munich, Germany.

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