全球流动性冲击对我国股市波动的影响研究——基于MS-VAR模型的分析
|
摘要
本文基于1999—2016年相关变量的月度数据,借助非线性的马尔科夫区制转换向量自回归模型(MS-VAR),描绘了具备非线性、时变性特征的全球流动性在不同区制状态下(全球流动性水平低速增长、混合波动增长、高速增长)对我国股市波动的影响,考察了在不同区制下全球流动性冲击对我国股市的传导渠道,并提出了应对冲击实现高效率流动性管理的相关建议。实证检验结果表明:全球流动性冲击通过三条渠道共同发挥作用传递到我国的股票市场,其中资本渠道与贸易渠道占有相对主导地位。在我国短期内仍实行资本管制的情况下,利率渠道并未成为传递或放大全球流动性冲击对我国股市产生影响的主要渠道。短期来看,资本管制是应对冲击的有效手段。但从长期来看,应从积极、持续推进汇率制度改革与人民币国际化进程,保证财政政策与货币政策的独立性与灵活性等方面入手,同时也应注意协调好人民币国际地位的提高、资本管制的放开、灵活的汇率制度之间的关系。
Based on the monthly data from 1999 to 2016,this paper constructs a Markov-Switching Vector Auto Regression model(MS-VAR) which can describe the impact of global liquidity with nonlinear and time-varying characteristics on China's stock market volatility in different regimes including increasing at low speed, moderate speed and high speed. This paper also captures the transmission channel of global liquidity in order to provide policy suggestions for managing liquidity more effectively. The results show that there are three main channels for global liquidity shock to pass into China's stock market including capital channel,trade channel and interest rate channel. And capital channel and trade channel play the leading role while interest rate channel is in the non-dominant position to transmit or amplify the impact of global liquidity shock because of capital control in the short term. Therefore,it's still an essential way to handle liquidity shock by capital control in the short term. But in the long run,the government should focus on promoting reform of the exchange rate regime and the process of RMB internationalization actively and continually and ensuring the independence and flexibility of fiscal policy and monetary policy. At the same time,it's also essential to coordinate the relationship among improving the international status of RMB,the liberalization of capital controls and flexible exchange rate regime.
Based on the monthly data from 1999 to 2016,this paper constructs a Markov-Switching Vector Auto Regression model(MS-VAR) which can describe the impact of global liquidity with nonlinear and time-varying characteristics on China's stock market volatility in different regimes including increasing at low speed, moderate speed and high speed. This paper also captures the transmission channel of global liquidity in order to provide policy suggestions for managing liquidity more effectively. The results show that there are three main channels for global liquidity shock to pass into China's stock market including capital channel,trade channel and interest rate channel. And capital channel and trade channel play the leading role while interest rate channel is in the non-dominant position to transmit or amplify the impact of global liquidity shock because of capital control in the short term. Therefore,it's still an essential way to handle liquidity shock by capital control in the short term. But in the long run,the government should focus on promoting reform of the exchange rate regime and the process of RMB internationalization actively and continually and ensuring the independence and flexibility of fiscal policy and monetary policy. At the same time,it's also essential to coordinate the relationship among improving the international status of RMB,the liberalization of capital controls and flexible exchange rate regime.
引文
[1]Darius R,Radde S.2010.Can global liquidity forecast asset prices?[R].IMF Working Paper.
[2]Brana S,Djibenou M,Prat S.2012.Global excess liquidity and asset prices in emerging countries:A PVAR approach[R].LAREFI Working Paper.
[3]Sun T.2015.The Impact of Global Liquidity on Financial Landscapes and Risks in the ASEAN-5 Countries[R].IMF Working Paper.
[4]Feyen E,Ghosh S,Kibuuka K,et al.2015.Global liquidity and external bond issuance in emerging markets and developing economies[R].World Bank Working Paper.
[5]Beckmann J,Belke A,Czudaj R.2014.Does global liquidity drive commodity prices?[J].Journal of Banking&Finance,(48).
[6]Hamilton,J.D.1989.A new approach to the economic analysis of nonstationary time series and the business cycle.Econometrica(57).
[7]Krolzig H M.1997.Markov switching vector autoregression:Modelling,statistical inference and application to business cycle analysis.[M].Springer.
[8]Belke A,Bordon I G,Hendricks T W.2010.Global liquidity and commodity prices-A Cointegrated VAR Approachfor OECD Countries[J].Applied Financial Economics,20(3).
[9]何知仁,潘英丽.全球流动性的概念、驱动与溢出效应:一个文献评述[J].上海金融,2016,(2).
[10]高海红.全球流动性风险和对策[J].国际经济评论,2012,(2).
[11]陆磊,杨骏.流动性、一般均衡与金融稳定的“不可能三角”[J].金融研究,2016,(1).
[12]张会清,王剑.全球流动性冲击对中国经济影响的实证研究[J].金融研究,2011,(3).
[13]范小云,陈雷.国际流动性安排与人民币国际化[J].南开学报(哲学社会科学版),2015,(5).
[14]姚余栋.人民币已经具备补充全球流动性的潜力[N].人民日报,2016-04-24.
[15]姚余栋.全球流动性新变化下的人民币国际化机遇[N].第一财经日报,2015-06-26.
[16]张明.全球货币互换:现状、功能及国际货币体系改革的潜在方向[J].国际经济评论,2012,(6).
[17]赵爱清,杨五洲.关于全球流动性过剩问题的文献综述[J].经济纵横,2009,(11).
[18]余振,张萍,吴莹.美国退出QE对中美两国金融市场的影响及中国的对策——基于FAVAR模型的分析[J].世界经济研究,2015,(4).
[19]邢天才,田蕊.流动性冲击与金融稳定研究[M].北京:科学出版社,2011.
[20]欧阳志刚,潜力.国际因素对中国通货膨胀的非线性传导效应[J].经济研究,2015,(6).
[21]孙涛.全球流动性对东盟五国金融格局及风险的影响[J].国际金融研究,2016,(7).
[22]叶青,韩立岩.金融危机传染渠道与机制研究——以次贷危机为例[J].系统工程理论与实践,2014,(10).
[23]王晓枫,王秉阳.基于流动性动态特征的货币政策效果与工具选择[J].经济学动态,2013,(9).
(1)由于选取的变量种类多样,国内网站数据和国外网站数据的更新时间并不是同步的。此外指标计算过程中同时涉及不同的变量,比如国外的GDP与汇率,但二者有的更新到了2017年,有的只到2016年,因此本文选择1999—2016年是综合考虑了所有变量可获性的结果。
[2]Brana S,Djibenou M,Prat S.2012.Global excess liquidity and asset prices in emerging countries:A PVAR approach[R].LAREFI Working Paper.
[3]Sun T.2015.The Impact of Global Liquidity on Financial Landscapes and Risks in the ASEAN-5 Countries[R].IMF Working Paper.
[4]Feyen E,Ghosh S,Kibuuka K,et al.2015.Global liquidity and external bond issuance in emerging markets and developing economies[R].World Bank Working Paper.
[5]Beckmann J,Belke A,Czudaj R.2014.Does global liquidity drive commodity prices?[J].Journal of Banking&Finance,(48).
[6]Hamilton,J.D.1989.A new approach to the economic analysis of nonstationary time series and the business cycle.Econometrica(57).
[7]Krolzig H M.1997.Markov switching vector autoregression:Modelling,statistical inference and application to business cycle analysis.[M].Springer.
[8]Belke A,Bordon I G,Hendricks T W.2010.Global liquidity and commodity prices-A Cointegrated VAR Approachfor OECD Countries[J].Applied Financial Economics,20(3).
[9]何知仁,潘英丽.全球流动性的概念、驱动与溢出效应:一个文献评述[J].上海金融,2016,(2).
[10]高海红.全球流动性风险和对策[J].国际经济评论,2012,(2).
[11]陆磊,杨骏.流动性、一般均衡与金融稳定的“不可能三角”[J].金融研究,2016,(1).
[12]张会清,王剑.全球流动性冲击对中国经济影响的实证研究[J].金融研究,2011,(3).
[13]范小云,陈雷.国际流动性安排与人民币国际化[J].南开学报(哲学社会科学版),2015,(5).
[14]姚余栋.人民币已经具备补充全球流动性的潜力[N].人民日报,2016-04-24.
[15]姚余栋.全球流动性新变化下的人民币国际化机遇[N].第一财经日报,2015-06-26.
[16]张明.全球货币互换:现状、功能及国际货币体系改革的潜在方向[J].国际经济评论,2012,(6).
[17]赵爱清,杨五洲.关于全球流动性过剩问题的文献综述[J].经济纵横,2009,(11).
[18]余振,张萍,吴莹.美国退出QE对中美两国金融市场的影响及中国的对策——基于FAVAR模型的分析[J].世界经济研究,2015,(4).
[19]邢天才,田蕊.流动性冲击与金融稳定研究[M].北京:科学出版社,2011.
[20]欧阳志刚,潜力.国际因素对中国通货膨胀的非线性传导效应[J].经济研究,2015,(6).
[21]孙涛.全球流动性对东盟五国金融格局及风险的影响[J].国际金融研究,2016,(7).
[22]叶青,韩立岩.金融危机传染渠道与机制研究——以次贷危机为例[J].系统工程理论与实践,2014,(10).
[23]王晓枫,王秉阳.基于流动性动态特征的货币政策效果与工具选择[J].经济学动态,2013,(9).
(1)由于选取的变量种类多样,国内网站数据和国外网站数据的更新时间并不是同步的。此外指标计算过程中同时涉及不同的变量,比如国外的GDP与汇率,但二者有的更新到了2017年,有的只到2016年,因此本文选择1999—2016年是综合考虑了所有变量可获性的结果。