Bond Return Predictability and its Economic Value: The Case of China

Abstract

This paper investigates bond return predictability and its economic value. Using regression models, we first examine both the statistical and economic significance of bond return predictability in the Chinese market, and analyze the non-Markov and stochastic volatility properties of bond yields. On the basis of the above analysis, we propose a systematic method for constructing non-Markov dynamic term structure models (DTSMs) under a generalized Heath-Jarrow-Morton (HJM) framework with stochastic volatility. Then, we investigate the roles of the non-Markov property and stochastic volatility in bond return predictability and its economic gains realizing. Finally, we analyze the economic drivers of bond return predictability. Empirical results show that bond return predictability in the Chinese market is statistically significant, which also can be converted into significant economic gains. The non-Markov property and stochastic volatility are of critical importance for this conversion process. Moreover, time-varying risk premia driven by the economic environment are the main source of the bond return predictability in the Chinese market, while unspanned stochastic volatility factors also contain much information for future bond returns.