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

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.