宏观经济政策与股市系统性风险--宏微观混合β估测方法的提出与检验  

Macroeconomic Policies and Systemic Risk in China's Stock Market: An Approach Based on Integrated Hybrid Betas

作　　者：邓可斌 关子桓[1,2] 陈彬 DENG Kebin;GUAN Zihuan;CHEN Bin(School of Economics and Commerce,South China University of Technology;Department of Economics,University of Rochester)

机构地区：[1]华南理工大学经济与贸易学院,金融工程研究中心 [2]华南理工大学经济与贸易学院广东省供应链金融工程技术研究中心,510006 [3]罗切斯特大学(美国)经济系

出　　处：《经济研究》2018年第8期68-83,共16页Economic Research Journal

基　　金：本研究得到国家自然科学基金(716283021)、国家社科重大项目(15ZDA013)、中央高校基本科研业务费项目(2017ZX012)的资助。

摘　　要：本文首先提出了一种同时包括货币政策、财政政策等宏观经济政策的动态股市系统性风险估测方法(命名为宏微观混合β估测方法),并与现有模型比较,证明忽略宏观经济政策因素的已有方法会显著低估系统性风险,同时显著降低样本外预测精度。其次,证明了货币政策、财政政策因素在系统性风险的形成方面均有决定作用:宽松货币/财政政策均能有效地降低我国股市的系统性风险。最后提供了股市系统性风险价格的结构转换的检验方法,发现2009—2015年中我国股市的系统性风险价格存在着2012年2月与2014年9月两个主要结构转换点,相应的两个主要系统性风险结构转换点则为2012年8月与2014年12月。Summary:This paper proposes a novel hybridβ,integrating macroeconomic policy factors and firm characteristic factors to detect systemic risk at the firm level in emerging economies such as China.A characteristic of China's economy is the striking contrast between the outstanding macroeconomic growth and the flat performance of listed firms.This hints at the distinction between the impacts of macroeconomic policy and of stock market factors on systemic risk.Using a unique monthly dataset of China's A-share listed firms from January 2000 to December 2015,we provide a new methodology by developing the Bayes estimating approach of Cosemans et al.(2016).We include two indicators,the M2 growth rate to capture monetary policy and the growth rate of state-owned fixed assets to capture fiscal policy,in a dynamic model for estimating the hybridβ(the systemic risk factor).The results demonstrate that both easy monetary policy and easy fiscal policy can significantly decrease systemic risk.In our model,the intercept termαis near zero and the coefficient of the hybridβis significantly positive,consistent with the classical asset pricing theory.Not including macroeconomic policy factors in a pricing model would lead to both a significantly positiveαand a lower coefficient of the hybridβ.We document that systemic risk is well explained by excessive returns after eliminating the measurement error ofβin China.We further illustrate how to detect structural turning points in the time-varying risk price and time-varyingβby expanding the method of Chen&Hong(2012)and Chen&Huang(2018).Knowing when turning-points occur can help in timing government interventions to address systemic risk.When either the risk price rises abruptly and systemic risk drops swiftly or the reverse happens,the government should intervene in the stock market.When the risk price rises abruptly together with systemic risk,the government should not intervene because the rise in systemic risk implies that the economic climate is improving.We make three contr

关 键 词：宏微观混合β 资本资产定价模型 宏观经济政策 结构转换特征 

分 类 号：F123.16[经济管理—世界经济]