题目： Real-Time Bayesian Learning and Bond Return Predictability 

时间：11月13日中午

地点：诚明楼315会议室

主讲人：万润青

内容概述：The paper examines statistical and economic evidence of out-of-sample bond return predictability for a real-time Bayesian investor who learns about parameters, hidden states, and predictive models over time. We find some statistical evidence using information contained in forward rates. However, such statistical predictability can hardly generate any economic value for investors. Furthermore, we find that strong statistical and economic evidence of bond return predictability from fully-revised macroeconomic data vanishes when real-time macroeconomic information is used. We also show that highly levered investments in bonds can improve short-run bond return predictability.

题目：实时贝叶斯学习与债券收益预测性

内容概述：本文研究了实时贝叶斯投资者样本外债券回报可预测性的统计和经济证据，该投资者随着时间的推移了解参数、隐藏状态和预测模型。我们使用远期汇率中包含的信息找到了一些统计证据。然而，这种统计上的可预测性很难为投资者带来任何经济回报。此外，我们发现，当使用实时宏观经济信息时，来自全面修订的宏观经济数据的债券回报可预测性的强有力的统计和经济证据消失了。我们还表明，对债券的高杠杆投资可以提高短期债券回报的可预测性。