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作 者:寇明婷[1] 杨海珍 汪寿阳 Kou Mingting;Yang Haizhen;Wang Shouyang(Donlinks School of Economics and Management,University of Sciences and Technology Beijing,Beijing 100083;School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190;Academy of Mathematics and Systems Science.Chinese Academy of Sciences,Beijing 100190)
机构地区:[1]北京科技大学东凌经济管理学院,北京100083 [2]中国科学院大学经济与管理学院,北京100190 [3]中国科学院数学与系统科学研究院,北京100190
出 处:《管理评论》2018年第9期3-11,共9页Management Review
基 金:国家自然科学基金重点项目(71532013);国家自然科学基金面上项目(71273257);国家自然科学基金青年项目(71804008);中央高校基本科研业务费专项资金资助项目(FRF-TP-16-051A1)
摘 要:经济预测机构对经济数据的预测与发布使得宏观经济信息宣布对金融市场和投资者而言已非全新信息,与之相对应的传统资产价格与宏观经济政策之间传递溢出效应的估计也因此而有失偏颇。本文以政策预期为视角,通过构建改进的C-GARCH模型,在特别设计区分宏观经济信息的预见与未预见部分的基础上,分别从政策异质性与行业差异性层面细致分析了我国股票价格波动与宏观经济变量的关联互动,并借助扩展的T-GARCH模型进行了稳健性检验。实证结果表明,未预期到的宏观经济信息变动较预期部分对股票市场的影响更大;受宏观经济政策异质性的影响,股票市场在长期和短期层面的波动差异显著;同时还发现行业的差异导致股票市场与宏观经济运行联动关系迥异,与宏观经济变量关联较大的行业主要分布在能源、材料、消费、医药行业。The release of forecasted economic data by some forecasters often result in the fact that macroeconomic information, when officially announced, has no longer been completely unknown to financial markets and investors. Accordingly, the resultant estimation of spillover effects between asset prices and macroeconomic policies is biased. On the basis of the specialized discrimination between the expected and unexpected parts of macroeconomic information, we construct a generalized C-GARCH model, and estimate the dynamic correlative relations between stock market and macroeconomic operation from the perspective of policy predictability, which are implemented respectively by accounting for policy heterogeneity and industry differences. Then we employ the generalized T-GARCH model to do the robust test. The empirical results show that the effect of unexpected part of macroeconomic operation on the stock market is greater than the expected part. Due to the difference of the macroeconomic information, the fluctuation difference of stock market between the long-term and short-term levels is significant. Furthermore, the extent of stock price synchronicity varies among industries, and those that are more correlative to macro-economy include energy, material, consumer and pharmaceutical industrials.
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