ABSTRACT

This study applies the sentiment endurance (SE) index developed by He (2012) to forecast excess returns of insurance stocks. With the exception of the 12-month rolling forecasts of the Fama-French three-factor model (FF), forecasts of the SE model persistently outperform that of the CAPM and FF models in terms of lower absolute percent forecasting error (APFE) and significantly lower standard deviation of APFE. The accuracy of 6-month rolling forecasts of SE model is significantly higher than that of the FF model.

Further, this study finds that the inclusion of SMB and HML in the SE model significantly deteriorates the accuracy and stability of forecasts. To a lesser degree, the addition of the market risk factor to the SE model hurts more than it improves the quality of forecasts. The results clearly suggest that compared to global variables, the SE index, as a local variable, more accurately reflects insurance investor sentiment and response to news and therefore can better forecast excess returns of insurance stocks.

摘要

本研究应用何 (2012) 开发的情绪耐力 (SE) 指数来预测保险股的超额收益。除了 Fama-French 三因子模型 (FF) 的 12 个月滚动预测外，SE 模型的预测在绝对百分比预测误差 (APFE) 和显着降低方面持续优于 CAPM 和 FF 模型。 APFE 的较低标准偏差。SE模型6个月滚动预测的准确率明显高于FF模型。

此外，本研究发现 SE 模型中包含 SMB 和 HML 会显着降低预测的准确性和稳定性。在较小程度上，将市场风险因素添加到 SE 模型的伤害大于它提高预测质量的效果。结果清楚地表明，与全局变量相比，SE指数作为局部变量更准确地反映了保险投资者的情绪和对新闻的反应，因此可以更好地预测保险股的超额收益。