Forecasting the Correlation Structure of German Stock Returns: A Test of Firm‐Specific Factor Models
评估了多种公司特定变量因子模型在预测德国股票市场相关矩阵方面的表现，发现多因子模型并不总是优于简单模型，传统行业均值模型在多数时期表现最佳。
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.