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# Table 4 In-sample predictability of Swiss stock market and bond market excess returns using GVD or its components

From: What Goliaths and Davids among Swiss firms tell us about expected returns on Swiss asset markets

Panel A: Predictability of stock market excess returns | ||||||||
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h=1 | h=3 | h=6 | h=12 | |||||

Predictor | \(\hat {\beta }\) | R^{2}(%) | \(\hat {\beta }\) | R^{2}(%) | \(\hat {\beta }\) | R^{2}(%) | \(\hat {\beta }\) | R^{2}(%) |

GVD | 0.50** | 1.61 | 0.48** | 3.46 | 0.59** | 8.72 | 0.57** | 13.88 |

(p value) | (0.03) | (0.02) | (0.02) | (0.02) | ||||

GVD^{new} | 0.55** | 1.92 | 0.60** | 5.33 | 0.61*** | 9.44 | 0.55** | 12.93 |

(p value) | (0.03) | (0.02) | (0.00) | (0.01) | ||||

GVD^{old} | – 0.34 | 0.72 | – 0.18 | 0.49 | – 0.05 | 0.06 | 0.14 | 0.85 |

(p value) | (0.84) | (0.73) | (0.53) | (0.37) | ||||

Panel B: Predictability of bond market excess returns | ||||||||

Predictor | \(\hat {\beta }\) | R^{2}(%) | \(\hat {\beta }\) | R^{2}(%) | \(\hat {\beta }\) | R^{2}(%) | \(\hat {\beta }\) | R^{2}(%) |

GVD | 0.02 | 0.05 | 0.03 | 0.35 | 0.04 | 0.88 | 0.04 | 1.56 |

(p value) | (0.39) | (0.33) | (0.32) | (0.35) | ||||

GVD^{new} | – 0.02 | 0.07 | – 0.01 | 0.05 | 0.02 | 0.29 | 0.03 | 0.71 |

(p value) | (0.67) | (0.57) | (0.38) | (0.36) | ||||

GVD^{old} | 0.12** | 1.68 | 0.07 | 1.63 | 0.03 | 0.38 | 0.01 | 0.22 |

(p value) | (0.01) | (0.14) | (0.35) | (0.41) |