摘要
大类资产价格是由宏观经济因素驱动的,由于宏观经济变量观测频率的限制,对驱动大类资产价格的宏观因素过程并未给出明确清晰的结论。本文利用符号约束法在模型中引入经济增长和通货膨胀两种宏观冲击实现了对驱动中美两国资产价格的宏观因素的高频分解,较好地实现了资产价格周期与宏观经济周期的对应。本文认为经济状态冲击对债券收益率和股价均有正面影响,通货膨胀冲击是债券收益率的正面影响因素是股价的负面影响因素。本文的研究为在较高频率上进行大类资产配置的理论和实践提供了分析基准,为高频宏观大数据在资产配置领域的应用提供了支持。
Major asset price is driven by macroeconomic factors, there is no significant conclusion on the process of how macroeconomy influence the major asset price because of the limitation on frequency of macroeconomic variables. We introduce economic pattern and inflation shocks into the model using sign restriction to decompose the macro-driven factors of US and China market at high frequency and achieve better fitness of financial cycle and economic cycle. We identify positive impact of economic shock on bond yield and stock price and the impact of inflation shock on bond yield is also positive but negative on stock price. This research can provide a baseline and support the application of high-frequency macro data in major asset allocation.
作者
陈文生
屠文雯
Chen Wensheng;Tu Wenwen
出处
《投资研究》
CSSCI
北大核心
2019年第9期45-59,共15页
Review of Investment Studies
关键词
大类资产
宏观驱动
符号约束
历史分解
Major asset
Macro-driven
Sign restriction
Historical decomposition