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金融研究  2018, Vol. 461 Issue (11): 30-46    
  中国数字金融专题 本期目录 | 过刊浏览 | 高级检索 |
测量中国的金融不确定性——基于大数据的方法
黄卓, 邱晗, 沈艳, 童晨
北京大学国家发展研究院/北京大学数字金融研究中心,北京 100871
Measuring China's Financial Uncertainty: A Method Based on a Large Dataset
HUANG Zhuo, QIU Han, SHEN Yan, TONG Chen
National School of Development and Institute of Digital Finance, Peking University
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摘要 本文基于 Jurado et al.(2015)提出的大数据分析方法,采用280个月度经济金融变量构造了2002-2017的中国金融不确定性指数,并从股票市场波动和金融机构系统性风险两个方面对中国的金融不确定性指数进行了实证分析。本文发现,在控制了滞后波动率后,金融不确定性指数仍然对股票市场的波动率有显著的预测作用;同时,金融不确定性的增加会显著提升金融机构的系统性风险,尤其是规模较大的金融机构。实证结果表明,金融不确定性是金融市场波动的一个重要来源。
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黄卓
邱晗
沈艳
童晨
关键词:  金融不确定性  已实现波动率  系统性风险    
Abstract:  Based on the method of big data analysis proposed by Jurado et al. (2015), this paper uses the 280 monthly economic and financial variables to construct the 2002-2017 monthly China's financial uncertainty index. We make an empirical analysis of China's financial uncertainty index from two aspects: stock market volatility and systemic risk of financial institutions. The empirical results show that the financial uncertainty index can well predict the realized volatility in the stock market after controlling the lagged volatility; we also find that an increase in financial uncertainty will significantly increase the systemic risk of financial institutions, especially the larger financial institutions. Out results suggest that the financial uncertainty is an important source of volatility in financial markets.
Key words:  Financial Uncertainty    Stock Market Volatility    Systemic Risk
JEL分类号:  C53   D81   G32  
基金资助: * 本文受国家自然科学基金项目(编号71671004)和国家社会科学基金重大项目(编号18ZDA091)资助;
作者简介:  黄 卓,经济学博士,副教授,北京大学国家发展研究院,北京大学数字金融研究中心,Email: zhuohuang@nsd.pku.edu.cn.
邱 晗(通讯作者),博士研究生,北京大学国家发展研究院,北京大学数字金融研究中心,Email: qiuh@pku.edu.cn.
沈 艳,经济学博士,教授,北京大学国家发展研究院,北京大学数字金融研究中心,Email: yshen@nsd.pku.edu.cn.
童 晨,博士研究生,北京大学国家发展研究院,北京大学数字金融研究中心,Email: tongchen@pku.edu.cn.
引用本文:    
黄卓, 邱晗, 沈艳, 童晨. 测量中国的金融不确定性——基于大数据的方法[J]. 金融研究, 2018, 461(11): 30-46.
HUANG Zhuo, QIU Han, SHEN Yan, TONG Chen. Measuring China's Financial Uncertainty: A Method Based on a Large Dataset. Journal of Financial Research, 2018, 461(11): 30-46.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2018/V461/I11/30
[1] 陈雨露、马勇和阮卓阳,2016,《金融周期和金融波动如何影响经济增长与金融稳定?》,《金融研究》第2期,第1~22页.
[2] 丁志国、苏治和赵晶,2012,《资产系统性风险跨期时变的内生性: 由理论证明到实证检验》,《中国社会科学》第4期,第83~102页.
[3] 董直庆和王林辉,2008,《我国证券市场与宏观经济波动关联性:基于小波变换和互谱分析的对比检验》,《金融研究》第8期,第39~52页.
[4] 李振、陈忠阳和朱建林,2018,《金融结构、金融波动与经济增长》,《金融论坛》第5期,第54~65页.
[5] 李志辉、李源和李政,2016,《中国银行业系统性风险监测研究——基于SCCA技术的实现与优化》,《金融研究》第3期, 第92~106页.
[6] 马君潞、范小云和曹元涛,2007,《中国银行间市场双边传染的风险估测及其系统性特征分析》,《经济研究》第1期,第68~78页.
[7] 邱兆祥和刘远亮,2010,《宏观经济不确定性与银行资产组合行为: 1995~ 2009》,《金融研究》第11期,第34~44页.
[8] 尚玉皇和郑挺国,2018,《中国金融形势指数混频测度及其预警行为研究》,《金融研究》第3期,第21~35页.
[9] 王国静和田国强,2014,《金融冲击和中国经济波动》,《经济研究》第3期,第20~34页.
[10] 肖强和司颖华,2015,《我国FCI的构建及对宏观经济变量影响的非对称性》,《金融研究》第8期,第95~108页.
[11] 王义中和宋敏,2014,《宏观经济不确定性、资金需求与公司投资》,《经济研究》第2期,第4~17页.
[12] 郑振龙、王为宁和刘杨树,2014,《平均相关系数与系统性风险:来自中国市场的证据》,《经济学(季刊)》,第3期,第1047~1064页.
[13] Adrian, T. and M. K. Brunnermeier, 2016, “CoVaR”,American Economic Review, 106(7), pp. 1705~1741.
[14] Andersen T. G.,T. Bollerslev,F. X. Diebold and P. Labys, 2003, “Modeling and Forecasting Realized Volatility”,Econometrica, 71(2), pp.579~625.
[15] Anderson E. W.,E. Ghysels, and J. L. Juergens, 2009, “The Impact of Risk and Uncertainty on Expected Returns”,Journal of Financial Economics, 94(2), pp.233~263.
[16] Aramonte S.2014, “Macroeconomic Uncertainty and the Cross-section of Option Returns”.Journal of Financial Markets, 21, pp.25~49.
[17] Bachmann R.,S. Elstner and E. R. Sims, 2013, “Uncertainty and Economic Activity: Evidence from Business Survey Data”.American Economic Journal: Macroeconomics, 5(2), pp.217~249.
[18] Bai, J. and S. Ng, 2002, “Determining the Number of Factors in Approximate Factor Models”.Econometrica, 70(1), pp.191~221.
[19] Baker S. R.,N. Bloom, and S. J. Davis, 2016, “Measuring Economic Policy Uncertainty”.The Quarterly Journal of Economics, 131(4), pp.1593~1636.
[20] Bali T. G.,S. J. Brown and Y. Tang, 2017, “Is Economic Uncertainty Priced in the Cross-section of Stock Returns?”.Journal of Financial Economics, 126(3), pp.471~489.
[21] Bekaert G.,M. Hoerova and M. L. Duca, 2013, “Risk, Uncertainty and Monetary Policy”.Journal of Monetary Economics, 60(7), pp.771~788.
[22] Bloom, N, 2009, “The Impact of Uncertainty Shocks”.Econometrica, 77(3), pp.623~685.
[23] Bollerslev T.,G. Tauchen and H. Zhou, 2009, “Expected Stock Returns and Variance Risk Premia”.The Review of Financial Studies, 22(11), pp.4463~4492.
[24] Brunnermeier, M. K. and Y. Sannikov, 2014, “A Macroeconomic Model with a Financial Sector”.American Economic Review, 104(2), pp.379~421.
[25] Byun S. J.,2016, “The Usefulness of Cross-sectional Dispersion for Forecasting Aggregate Stock Price Volatility”.Journal of Empirical Finance, 36, pp.162~180.
[26] Caggiano G.,E. Castelnuovo and N. Groshenny, 2014, “Uncertainty Shocks and Unemployment Dynamics in US Recessions”.Journal of Monetary Economics, 67, pp.78~92.
[27] Diebold F.,R. Mariano, 1995, “Comparing predictive accuracy”.Journal of Business and Economic Statistics, 13, pp.253~263.
[28] Caldara D.,C. Fuentes-Albero S. Gilchrist and E. Zakrajšek,2016. “The Macroeconomic Impact of Financial and Uncertainty Shocks”.European Economic Review, 88, pp.185~207.
[29] Fernald J. G.,M. M. Spiegel and E. T. Swanson, 2014, “Monetary Policy Effectiveness in China: Evidence from a FAVAR Model”.Journal of International Money and Finance, 49, pp.83~103.
[30] Gilchrist S.,J. W. Sim and E. Zakrajšek,2014, “Uncertainty, Financial Frictions, and Investment Dynamics”. NBER Working Paper, No. 20038.
[31] Hatzius J.,P. Hooper,F. S. Mishkin,K. L. Schoenholtz and M. W. Watson, 2010, “Financial Conditions Indexes: A Fresh Look After the Financial Crisis”. NBER Working Paper, No. 16150.
[32] Huang Z.,C. Tong,H. Qiu and Y. Shen, 2018, “The Spillover of Macroeconomic Uncertainty between the US and China”.Economics Letters, 171, pp.123~127.
[33] Jo, S. and R. Sekkel, 2017, “Macroeconomic Uncertainty through the Lens of Professional Forecasters”.Journal of Business & Economic Statistics, pp.1~11.
[34] Jurado K.,S. C. Ludvigson and S.Ng, 2015, “Measuring Uncertainty”.American Economic Review, 105(3), pp.1177~1216.
[35] Knotek II, E. S. and S. Khan, 2011, “How do Households Respond to Uncertainty Shocks?”.Economic Review-Federal Reserve Bank of Kansas City, 63.
[36] López-Espinosa G.,A. Moreno,A. Rubia and L. Valderrama, 2012, “Short-term Wholesale Funding and Systemic Risk: A Global CoVaR Approach”.Journal of Banking & Finance, 36(12), pp.3150~3162.
[37] Ludvigson S. C.,S. Ma and S. Ng, 2015, “Uncertainty and Business Cycles: Exogenous Impulse or Endogenous Response?”. NBER Working Paper, No. 21803.
[38] Mankiw N. G.,R. Reis, and J. Wolfers, 2003, “Disagreement about Inflation Expectations”.NBER macroeconomics annual, 18, pp.209~248.
[39] Morley J.,2016, “Macro‐Finance Linkages”.Journal of Economic Surveys, 30(4), pp.698~711.
[40] Newey W. K.,K. D. West, 1987, “A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix”.Econometrica. 55(3), pp.703~708.
[41] Ng, S. and J. H. Wright, 2013, “Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling”.Journal of Economic Literature, 51(4), pp.1120~1154.
[42] Pástor L,P. Veronesi, 2013,“Political Uncertainty and Risk Premia”.Journal of Financial Economics, 110(3), pp.520~545
[43] Rossi, B. and T. Sekhposyan, 2015, “Macroeconomic Uncertainty Indices Based on Nowcast and Forecast Error Distributions”.American Economic Review, 105(5), pp.650~655.
[44] Scotti C.,2016, “Surprise and Uncertainty Indexes: Real-time Aggregation of Real-activity Macro-surprises”.Journal of Monetary Economics, 82, pp.1~19.
[45] Shin H. S.,2009, “Reflections on Northern Rock: The Bank Run that Heralded the Global Financial Crisis”.Journal of economic perspectives, 23(1), pp.101~119.
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