【摘要】 债券收益的可预测性及其经济价值一直是颇具争议的热点问题.本文首先利用回归模型检验了我国债券收益的可预测性,并分析了债券收益的非马尔科夫性和随机波动特征.在此基础上,在广义随机波动HJM框架下提出了非马尔科夫DTSM模型的构建方法,并分析了非马尔科夫性和随机波动性对于债券超额收益的可预测性及其经济价值实现的作用.最后,考察了我国市场上债券收益可预测性的来源.结果表明,我国债券收益可预测性具有很强的统计显著性,且可以转化为显著的经济收益.在此过程中,非马尔科夫性、随机波动性具有十分关键的作用.经济环境驱动的时变性风险溢价是我国债券收益可预测性的主要来源,而非涵盖随机波动因子也显著含有债券收益的预测信息.更多还原

【Abstract】 Bond return predictability and its economic value have always been a hot but controversial topic. Using regression models,this paper examines both the statistical and economic significance of bond return predictability in Chinese markets,and analyzes the non-Markov and stochastic volatility properties of bond yields.On the basis of the above analysis,a systematic method is proposed for constructing non-Markov dynamic term structure models( DTSMs) under a generalized Heath-Jarrow-Morton( HJM) framework with stochastic volatility,which is then used to investigate the roles of the non-Markov property and stochastic volatility in bond return predictability and its economic gains realizing. Finally,this paper analyzes the economic drivers of bond return predictability. Empirical results show that bond return predictability in Chinese markets is statistically significant,which can also be converted into significant economic gains. The non-Markov property and stochastic volatility are of critical importance in the converting. Moreover,time-varying risk premia driven by the economic environment are the main sources of the bond return predictability in Chinese markets,while unspanned stochastic volatility factors also contain much information for future bond returns.更多还原