潜藏因子的信息含量:来自中国国债市场的证据

郑振龙, 廖木英, 陈蓉, 黄海峰

系统工程理论与实践 ›› 2016, Vol. 36 ›› Issue (1) : 44-54.

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PDF(967 KB)
系统工程理论与实践 ›› 2016, Vol. 36 ›› Issue (1) : 44-54. DOI: 10.12011/1000-6788(2016)01-0044-11
论文

潜藏因子的信息含量:来自中国国债市场的证据

    郑振龙, 廖木英, 陈蓉, 黄海峰
作者信息 +

Information content of the hidden factor: Evidence from the China's treasury bond market

    ZHENG Zhenlong, LIAO Muying, CHEN Rong, HUANG Haifeng
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文章历史 +

摘要

潜藏因子是指对当前利率曲线没有影响或影响甚微,但对未来利率具有预测作用的信息. 本文采用Duffee 的潜藏因子分析框架, 发现中国市场上中短期利率的五因子模型的方差比仅为0.41, 较好地证实了潜藏因子的存在性. 接着从风险溢酬因子中剔除利率曲线信息后得到潜藏因子, 并且证实了潜藏因子包含着丰富的经济信息含量, 并集中体现为通货膨胀和宏观流动性的信息, 特别是通货膨胀信息, 但与经济增长类指标联系微弱. 最后, 本文发现中国市场上的潜藏因子对未来利率变化具有良好的预测力.

Abstract

The hidden factor is the information that has no or little effect on the current interest rate curve but affects the expected interest rates. Using the hidden factor idea proposed by Duffee, we find that the variance ratio of the five-factor model in China's treasury bond market is only 0.41, which confirms the existence of the hidden factor. Then we exclude the interest rate curve information from the risk premium factor to get the hidden factor, and confirm that the hidden factor in China does contain a wealth of economic information content. It is closely linked with the inflation and the macro-liquidity, especially the inflation information. But the hidden factor has little to do with the economic growth information. At last we find the hidden factor in China has rather great power on predicting future interest rate.

关键词

期限溢酬 / 潜藏因子 / 信息含量

Key words

term premium / hidden factor / information content

引用本文

导出引用
郑振龙 , 廖木英 , 陈蓉 , 黄海峰. 潜藏因子的信息含量:来自中国国债市场的证据. 系统工程理论与实践, 2016, 36(1): 44-54 https://doi.org/10.12011/1000-6788(2016)01-0044-11
ZHENG Zhenlong , LIAO Muying , CHEN Rong , HUANG Haifeng. Information content of the hidden factor: Evidence from the China's treasury bond market. Systems Engineering - Theory & Practice, 2016, 36(1): 44-54 https://doi.org/10.12011/1000-6788(2016)01-0044-11
中图分类号: F830   

参考文献

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基金

国家自然科学基金(71371161, 71471155, 71101121, 71261024)
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