我国股票市场运行特征及其与宏观经济波动的关联性研究
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摘要
经过二十多年的不断建设，我国股票市场经历了坎坷曲折的摸索，规模迅速发展壮大，已经跃进世界排名前五大股票市场的行列。股票市场的繁荣和稳定在建设社会主义市场经济进程中具有举足轻重的地位，它不仅仅承载着资本市场融资和筹资的重要责任，还肩负着合理调节资源配置和控制金融风险的重任，同时也是广大投资者和社会经济活动的参与者对未来宏观经济预期充满信心的重要保证。随着股票、债券等证券投资工具越来越受到投资者的关注，股票市场的发展和规范在宏观经济体系中也占有越来越重的地位。经济学界和金融学界的众多学者认为，股票市场价格波动与宏观经济波动之间关系密切，对两者之间关系进行深入的理论研究与实证检验，有利于股票市场的发展和规范，有助于资本市场的健全和完善，对推进社会主义改革和经济建设有着至关重要的作用。因此，近年来经济金融学界越来越关注对股票市场价格波动与宏观经济波动之间相互关系以及作用机理的研究。
在宏观经济运行过程中资本市场发挥着极为重要的作用。作为资本市场的重要组成部分，股票市场的收益率波动影响着资本市场发展的稳定繁荣程度，进而影响宏观经济运行。所以宏观经济波动和股票市场收益率的波动之间的关系非常紧密，为了分析宏观经济波动与股票市场收益率之间的相关性，我们不仅介绍了我国股票市场运行的基本特征和发展轨迹，而且介绍了股票市场收益率波动与实际产出波动关联性的理论模型，同时介绍股票市场收益率波动和宏观经济波动之间的传导机制，并分析了股票市场价格波动的“经济效应”。目的在于将股票市场作为经济系统的有机构成，建立股票市场与宏观经济的密切关联，从而实现两者之间的紧密关联，为制定和选择有效的宏观经济调控，保证经济稳定持续运行提供重要的决策支撑。
对我国金融市场的相关性的理论分析，是描述我国股票市场运行特征进而实证检验宏观经济波动和股票市场收益率的波动之间的关联性的重要前提。在本文中，我们引用了Copula-GARCH模型描述我国股票市场运行特征。在对Copula-GARCH模型的参数估计中，曾经最广泛使用的是两步优化(IFM)估计方法。但是模型所研究样本容量一旦较小，IFM方法将会出现较大的估计偏差。本文采用多步优化(MBP)估计方法来估计Copula-MGARCH模型，进而研究我国金融市场的相关性问题。MBP估计方法将复杂的对数似然函数分为两部分，一部分包括似然函数中独立相关条件下的边缘分布函数；另一部分包含多变量似然函数的相关参数。检验表明在Copula-GARCH模型的参数估计中，相比精确极大似然估计方法，多步优化估计方法更简单有效，描述我国股票市场运行特征更加细致准确。
对于我国上海股票市场和深圳股票市场收益率序列的分析是研究我国宏观经济波动与股票市场收益率波动之间关联性的重要基础。本文使用近年来国内外大量文献中提出的检验长期记忆性的方法来对其进行研究，这些方法包括ARFIMA模型的极大似然估计、FIGARCH模型的极大似然估计以及ARFIMA-FIGARCH模型的极大似然估计，通过实证检验，结果表明我国上海股票市场和深圳股票市场收益率序列具有时变波动性和双长期记忆性。这个结果可以作为研究我国宏观经济波动与股票市场收益率波动之间关联性的重要基础。
为了进一步实证检验我国宏观经济波动与股票市场收益率波动之间的相互关系问题，我们采用了单位根检验方法、VAR模型方法、Granger因果关系检验方法、冲击响应函数和方差分解方法等多种计量经济学方法，研究我国宏观经济波动与股票市场收益率波动之间的关联性和相互作用影响，结果发现当经济处于衰退时期的时候，股票市场价格指数也会同步逐渐下跌，而当经济逐渐复苏的时候，股票市场价格指数又会同步逐步上升。于此同时，我们还注意到，股票市场价格指数的波动幅度以及波动持续时间在不同的经济周期增长阶段都对宏观经济增长表现出不同的影响作用。
我国宏观经济变量的波动性与股票市场收益率波动之间的关联性研究，是研究宏观经济波动对股票市场价格波动影响作用的重要工具。本文采用银行间同业拆借加权平均利率的月度数据代表名义利率(IR)，采用人民币对美元加权平均汇率的月度数据代表名义汇率(ER)，采用货币供应量M1月末数同比增速代表货币供给量的月度同比增长率(M)，同时采用上证综合指数月收益率(SH)数据以及深证综合指数月收益率(SZ)数据，运用单位根检验方法、VAR模型方法、Granger因果关系检验方法、冲击响应函数和方差分解方法等多种计量经济学方法详细描述宏观经济变量波动对股票市场价格波动的影响作用，发现宏观经济变量波动对股票市场价格波动的之间的影响效应和作用机理，进一步求证了宏观经济波动与股票市场收益率波动之间的关联性。
After20years of construction, China's stock market has gone through ups and downs andtwists and turns of groping, all the way to thrive trials and hardships, the scale has expanded rapidlyleap forward in the ranks of the world's top five largest stock market. The prosperity and stability ofthe stock market plays a decisive role in the process of building a socialist economy, it is not onlyimportant responsibility of carrying the financing of capital market financing, but also shoulder theburden of reasonable adjustment of resource allocation and control of financial risks, but also themajority of investors and socio-economic activities of participants is expected to be confident aboutthe future macroeconomic important guarantee. More and more attention from investors as stocks,bonds and other securities investment tools, the development and standardization of the stockmarket in the macroeconomic system also plays a more and more weight status. Economic circlesand financial circles, many scholars believe that the close relationship between the stock marketprice volatility and macroeconomic volatility, depth theoretical research and empirical test of therelationship between the two, which is conducive to the development and standardization of thestock market, help improve and perfect capital markets, has a crucial role in promoting the socialistreform and economic construction. Therefore, the economic and financial circles in recent years,more and more concerned about the relationship between price volatility and macroeconomicvolatility of the stock market, as well as the study of the mechanism of action.
The capital market plays an extremely important role in the macroeconomic process. As animportant part of the capital market, the yield of the stock market fluctuations affect the degree ofstability and prosperity in the development of capital markets, thereby affecting macroeconomicperformance. Therefore, the relationship between macroeconomic volatility and the volatility of thestock market yields very closely in order to analyze the correlation between macroeconomicvolatility and stock market yields, in this article not only describes the characteristics of China'sstock market run, and introduced The yield of the stock market volatility and correlation of realoutput fluctuations theoretical model, also introduced the transmission mechanism between theyield of the stock market volatility and macroeconomic volatility, and analysis of the economic effects of price fluctuations in the stock market.
The analysis of the theory of China's financial markets is an important prerequisite to describethe characteristics of China's stock market run further empirical test the correlation betweenmacroeconomic volatility and the volatility of the stock market yields. In this article, we refer to theCopula-GARCH model to describe the characteristics of China's stock market run.Copula-GARCH model parameter estimation, once the most widely used is a two-step optimization(IFM) estimation method. However, the model studied Once the sample size is small, IFM methodwill appear larger estimation bias. In this paper, a multi-step optimization (MBP) estimationmethod to estimate the Copula-MGARCH model, and to study the related issues in China'sfinancial markets. MBP estimation method the complex logarithmic likelihood function is dividedinto two parts, part of the likelihood function independent marginal distribution function under therelevant conditions; another section contains the relevant parameters of the multivariate likelihoodfunction. The test showed that the Copula-GARCH model parameter estimation, compared to theexact maximum likelihood estimation method, multi-step optimization estimation method is simpleand effective, and to describe the characteristics of China's stock market run a more detailed andaccurate.
China's Shanghai stock market and Shenzhen stock market return series analysis is animportant foundation to study the correlation between the yield of China's macroeconomicvolatility and stock market fluctuations. This article uses at home and abroad in recent years a largenumber of long-term memory test proposed in the literature approach to their research, thesemethods include the ARFIMA models maximum likelihood estimation FIGARCH model maximumlikelihood estimation and ARFIMA-FIGARCH model pole maximum likelihood estimate byempirical test results show that the time-varying volatility and long-term memory of the Shanghaistock market and Shenzhen stock market return series. This result has laid an important foundationof the association between the study of macroeconomic fluctuations and fluctuations in the stockmarket yields.
Interaction effects between the association between the fluctuations of the studymacroeconomic volatility and stock market yields and both for the judgment of the turning point ofChina's macro-economic cycle, identify the expansion of China's economic development andsystolic and help China's economic development stage to take a different economic policy trend hasimportant economic significance to promote the prosperity and stability of the stock market and thesustained and healthy development of economic construction.
Relationship between empirical examination of macroeconomic volatility and stock marketgains rate fluctuations, we use the unit root test methods, VAR model approach, Granger causalitytest, impulse response function and variance decomposition method other econometric learningmethods, relevance and interaction effects between the study of macroeconomic volatility andfluctuations in the stock market yields, and found that when the economy is in a recession, the stock market price index will sync gradually fell, while the gradual economic recovery when thestock market price index will sync gradually rise. At the same time, we also noted that the volatilityof the stock market price index fluctuations duration showed different effects on themacro-economic growth in the different stage of the economic cycle of growth.
The study of the correlation between the fluctuations in the volatility of macroeconomicvariables and stock market yields, is an important tool of macroeconomic volatility effect of pricevolatility on the stock market. In this paper, the inter-bank lending weighted average interest rate ofthe monthly data on behalf of the nominal interest rate (IR), using monthly data on behalf of theweighted average exchange rate of the RMB against the U.S. dollar nominal exchange rate (ER),money supply (M1) represent the amount of money supply growth in the number of year-on-year atthe end of monthly year-on-year growth rate (M), at the same time using the data of the monthlyreturns of the Shanghai Composite Index (SH) and the Shenzhen Composite Index monthly returns(SZ) data, the use of the unit root test methods, VAR model method, Granger causality test methodsimpulse response function and variance decomposition methods econometric methods detaileddescription of the macroeconomic variables impact of fluctuations in the price fluctuations of thestock market, found that the fluctuations in macroeconomic variables between the price fluctuationsof the stock market effect and mechanism, further Prove that the correlation betweenmacroeconomic volatility and stock market fluctuations in yield.
在宏观经济运行过程中资本市场发挥着极为重要的作用。作为资本市场的重要组成部分，股票市场的收益率波动影响着资本市场发展的稳定繁荣程度，进而影响宏观经济运行。所以宏观经济波动和股票市场收益率的波动之间的关系非常紧密，为了分析宏观经济波动与股票市场收益率之间的相关性，我们不仅介绍了我国股票市场运行的基本特征和发展轨迹，而且介绍了股票市场收益率波动与实际产出波动关联性的理论模型，同时介绍股票市场收益率波动和宏观经济波动之间的传导机制，并分析了股票市场价格波动的“经济效应”。目的在于将股票市场作为经济系统的有机构成，建立股票市场与宏观经济的密切关联，从而实现两者之间的紧密关联，为制定和选择有效的宏观经济调控，保证经济稳定持续运行提供重要的决策支撑。
对我国金融市场的相关性的理论分析，是描述我国股票市场运行特征进而实证检验宏观经济波动和股票市场收益率的波动之间的关联性的重要前提。在本文中，我们引用了Copula-GARCH模型描述我国股票市场运行特征。在对Copula-GARCH模型的参数估计中，曾经最广泛使用的是两步优化(IFM)估计方法。但是模型所研究样本容量一旦较小，IFM方法将会出现较大的估计偏差。本文采用多步优化(MBP)估计方法来估计Copula-MGARCH模型，进而研究我国金融市场的相关性问题。MBP估计方法将复杂的对数似然函数分为两部分，一部分包括似然函数中独立相关条件下的边缘分布函数；另一部分包含多变量似然函数的相关参数。检验表明在Copula-GARCH模型的参数估计中，相比精确极大似然估计方法，多步优化估计方法更简单有效，描述我国股票市场运行特征更加细致准确。
对于我国上海股票市场和深圳股票市场收益率序列的分析是研究我国宏观经济波动与股票市场收益率波动之间关联性的重要基础。本文使用近年来国内外大量文献中提出的检验长期记忆性的方法来对其进行研究，这些方法包括ARFIMA模型的极大似然估计、FIGARCH模型的极大似然估计以及ARFIMA-FIGARCH模型的极大似然估计，通过实证检验，结果表明我国上海股票市场和深圳股票市场收益率序列具有时变波动性和双长期记忆性。这个结果可以作为研究我国宏观经济波动与股票市场收益率波动之间关联性的重要基础。
为了进一步实证检验我国宏观经济波动与股票市场收益率波动之间的相互关系问题，我们采用了单位根检验方法、VAR模型方法、Granger因果关系检验方法、冲击响应函数和方差分解方法等多种计量经济学方法，研究我国宏观经济波动与股票市场收益率波动之间的关联性和相互作用影响，结果发现当经济处于衰退时期的时候，股票市场价格指数也会同步逐渐下跌，而当经济逐渐复苏的时候，股票市场价格指数又会同步逐步上升。于此同时，我们还注意到，股票市场价格指数的波动幅度以及波动持续时间在不同的经济周期增长阶段都对宏观经济增长表现出不同的影响作用。
我国宏观经济变量的波动性与股票市场收益率波动之间的关联性研究，是研究宏观经济波动对股票市场价格波动影响作用的重要工具。本文采用银行间同业拆借加权平均利率的月度数据代表名义利率(IR)，采用人民币对美元加权平均汇率的月度数据代表名义汇率(ER)，采用货币供应量M1月末数同比增速代表货币供给量的月度同比增长率(M)，同时采用上证综合指数月收益率(SH)数据以及深证综合指数月收益率(SZ)数据，运用单位根检验方法、VAR模型方法、Granger因果关系检验方法、冲击响应函数和方差分解方法等多种计量经济学方法详细描述宏观经济变量波动对股票市场价格波动的影响作用，发现宏观经济变量波动对股票市场价格波动的之间的影响效应和作用机理，进一步求证了宏观经济波动与股票市场收益率波动之间的关联性。
After20years of construction, China's stock market has gone through ups and downs andtwists and turns of groping, all the way to thrive trials and hardships, the scale has expanded rapidlyleap forward in the ranks of the world's top five largest stock market. The prosperity and stability ofthe stock market plays a decisive role in the process of building a socialist economy, it is not onlyimportant responsibility of carrying the financing of capital market financing, but also shoulder theburden of reasonable adjustment of resource allocation and control of financial risks, but also themajority of investors and socio-economic activities of participants is expected to be confident aboutthe future macroeconomic important guarantee. More and more attention from investors as stocks,bonds and other securities investment tools, the development and standardization of the stockmarket in the macroeconomic system also plays a more and more weight status. Economic circlesand financial circles, many scholars believe that the close relationship between the stock marketprice volatility and macroeconomic volatility, depth theoretical research and empirical test of therelationship between the two, which is conducive to the development and standardization of thestock market, help improve and perfect capital markets, has a crucial role in promoting the socialistreform and economic construction. Therefore, the economic and financial circles in recent years,more and more concerned about the relationship between price volatility and macroeconomicvolatility of the stock market, as well as the study of the mechanism of action.
The capital market plays an extremely important role in the macroeconomic process. As animportant part of the capital market, the yield of the stock market fluctuations affect the degree ofstability and prosperity in the development of capital markets, thereby affecting macroeconomicperformance. Therefore, the relationship between macroeconomic volatility and the volatility of thestock market yields very closely in order to analyze the correlation between macroeconomicvolatility and stock market yields, in this article not only describes the characteristics of China'sstock market run, and introduced The yield of the stock market volatility and correlation of realoutput fluctuations theoretical model, also introduced the transmission mechanism between theyield of the stock market volatility and macroeconomic volatility, and analysis of the economic effects of price fluctuations in the stock market.
The analysis of the theory of China's financial markets is an important prerequisite to describethe characteristics of China's stock market run further empirical test the correlation betweenmacroeconomic volatility and the volatility of the stock market yields. In this article, we refer to theCopula-GARCH model to describe the characteristics of China's stock market run.Copula-GARCH model parameter estimation, once the most widely used is a two-step optimization(IFM) estimation method. However, the model studied Once the sample size is small, IFM methodwill appear larger estimation bias. In this paper, a multi-step optimization (MBP) estimationmethod to estimate the Copula-MGARCH model, and to study the related issues in China'sfinancial markets. MBP estimation method the complex logarithmic likelihood function is dividedinto two parts, part of the likelihood function independent marginal distribution function under therelevant conditions; another section contains the relevant parameters of the multivariate likelihoodfunction. The test showed that the Copula-GARCH model parameter estimation, compared to theexact maximum likelihood estimation method, multi-step optimization estimation method is simpleand effective, and to describe the characteristics of China's stock market run a more detailed andaccurate.
China's Shanghai stock market and Shenzhen stock market return series analysis is animportant foundation to study the correlation between the yield of China's macroeconomicvolatility and stock market fluctuations. This article uses at home and abroad in recent years a largenumber of long-term memory test proposed in the literature approach to their research, thesemethods include the ARFIMA models maximum likelihood estimation FIGARCH model maximumlikelihood estimation and ARFIMA-FIGARCH model pole maximum likelihood estimate byempirical test results show that the time-varying volatility and long-term memory of the Shanghaistock market and Shenzhen stock market return series. This result has laid an important foundationof the association between the study of macroeconomic fluctuations and fluctuations in the stockmarket yields.
Interaction effects between the association between the fluctuations of the studymacroeconomic volatility and stock market yields and both for the judgment of the turning point ofChina's macro-economic cycle, identify the expansion of China's economic development andsystolic and help China's economic development stage to take a different economic policy trend hasimportant economic significance to promote the prosperity and stability of the stock market and thesustained and healthy development of economic construction.
Relationship between empirical examination of macroeconomic volatility and stock marketgains rate fluctuations, we use the unit root test methods, VAR model approach, Granger causalitytest, impulse response function and variance decomposition method other econometric learningmethods, relevance and interaction effects between the study of macroeconomic volatility andfluctuations in the stock market yields, and found that when the economy is in a recession, the stock market price index will sync gradually fell, while the gradual economic recovery when thestock market price index will sync gradually rise. At the same time, we also noted that the volatilityof the stock market price index fluctuations duration showed different effects on themacro-economic growth in the different stage of the economic cycle of growth.
The study of the correlation between the fluctuations in the volatility of macroeconomicvariables and stock market yields, is an important tool of macroeconomic volatility effect of pricevolatility on the stock market. In this paper, the inter-bank lending weighted average interest rate ofthe monthly data on behalf of the nominal interest rate (IR), using monthly data on behalf of theweighted average exchange rate of the RMB against the U.S. dollar nominal exchange rate (ER),money supply (M1) represent the amount of money supply growth in the number of year-on-year atthe end of monthly year-on-year growth rate (M), at the same time using the data of the monthlyreturns of the Shanghai Composite Index (SH) and the Shenzhen Composite Index monthly returns(SZ) data, the use of the unit root test methods, VAR model method, Granger causality test methodsimpulse response function and variance decomposition methods econometric methods detaileddescription of the macroeconomic variables impact of fluctuations in the price fluctuations of thestock market, found that the fluctuations in macroeconomic variables between the price fluctuationsof the stock market effect and mechanism, further Prove that the correlation betweenmacroeconomic volatility and stock market fluctuations in yield.
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