Changes in Cross-Correlations as an Indicator for Systemic Risk

The 2008–2012 global financial crisis began with the global recession in December 2007 and exacerbated in September 2008, during which the U.S. stock markets lost 20% of value from its October 11 2007 peak. Various studies reported that financial crisis are associated with increase in both cross-correlations among stocks and stock indices and the level of systemic risk. In this paper, we study 10 different Dow Jones economic sector indexes, and applying principle component analysis (PCA) we demonstrate that the rate of increase in principle components with short 12-month time windows can be effectively used as an indicator of systemic risk—the larger the change of PC1, the higher the increase of systemic risk. Clearly, the higher the level of systemic risk, the more likely a financial crisis would occur in the near future.

[1]  Rama CONT.  Measuring systemic risk , 2008 .

[2]  V. Plerou,et al.  Universal and Nonuniversal Properties of Cross Correlations in Financial Time Series , 1999, cond-mat/9902283.

[3]  D. Helbing,et al.  Quantifying the Behavior of Stock Correlations Under Market Stress , 2012, Scientific Reports.

[4]  Carmen M. Reinhart,et al.  The Twin Crises: The Causes of Banking and Balance-of-Payments Problems , 1996 .

[5]  Japanese banks liability management before and during the banking crises and macroeconomic fundamentals , 2004 .

[6]  Leonidas Sandoval Junior,et al.  Correlation of financial markets in times of crisis , 2011, 1102.1339.

[7]  Yann Le Fur,et al.  International Market Correlation and Volatility , 1996 .

[8]  H. Stanley,et al.  Cross-correlations between volume change and price change , 2009, Proceedings of the National Academy of Sciences.

[9]  Christophe Pérignon,et al.  Do Banks Overstate Their Value-at-Risk? , 2007 .

[10]  Gary B. Gorton.  Banking panics and business cycles , 1988 .

[11]  Sophie Brana,et al.  Capital requirement and financial crisis: The case of Japan and the 1997 Asian crisis , 2009 .

[12]  C. Granger.  Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[13]  René M. Stulz,et al.  Hedge Fund Contagion and Liquidity Shocks , 2010 .

[14]  E. Ben-Jacob,et al.  The Index cohesive effect on stock market correlations , 2009 .

[15]  Jean-Philippe Bouchaud,et al.  Financial Applications of Random Matrix Theory: Old Laces and New Pieces , 2005 .

[16]  P. Hartmann,et al.  Systemic Risk: A Survey , 2000, SSRN Electronic Journal.

[17]  Sébastien Page,et al.  Principal Components as a Measure of Systemic Risk , 2010, The Journal of Portfolio Management.

[18]  Ladislav Kristoufek.  How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study , 2012 .

[19]  Ivo Grosse,et al.  Time-lag cross-correlations in collective phenomena , 2010 .

[20]  Takatoshi Ito,et al.  Meteor Showers or Heat Waves? Heteroskedastic Intra-Daily Volatility in the Foreign Exchange Market , 1988 .

[21]  Dan Braha,et al.  Predicting Economic Market Crises Using Measures of Collective Panic , 2011, ArXiv.

[22]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[23]  A. Lo,et al.  Econometric Measures of Systemic Risk in the Finance and Insurance Sectors , 2010 .

[24]  Gail ter Haar,et al.  A personal viewpoint , 1985 .

[25]  Alfred Lehar.  Measuring Systemic Risk: A Risk Management Approach , 2005 .

[26]  A. Lo,et al.  A Survey of Systemic Risk Analytics , 2012 .

[27]  Enrique Sentana,et al.  Volatiltiy and Links between National Stock Markets , 1990 .

[28]  H. Stanley,et al.  Quantifying and Modeling Long-Range Cross-Correlations in Multiple Time Series with Applications to World Stock Indices , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  Eshel Ben-Jacob,et al.  Quantifying meta-correlations in financial markets , 2012 .

[30]  Robert F. Engle,et al.  Meteor Showers or Heat Waves? Heteroskedastic Intra-Daily Volatility in the Foreign Exchange Market , 1988 .

[31]  T. Adrian.  Measuring Risk in the Hedge Fund Sector , 2007 .

[32]  E. Ben-Jacob,et al.  Hidden temporal order unveiled in stock market volatility variance , 2011 .

[33]  Igor Makarov,et al.  An econometric model of serial correlation and illiquidity in hedge fund returns , 2004 .

[34]  G. Kaufman.  Banking and Currency Crises and Systemic Risk: A Taxonomy and Review , 2000 .

[35]  Clare Marc Wallace.  Personal Viewpoint , 1965, Mental health.

[36]  R. H. Parker,et al.  This time is different: eight centuries of financial folly , 2010 .

[37]  Moira F. Jenkins,et al.  A risk management approach , 2013 .

[38]  Francis A. Longstaff,et al.  Systemic Credit Risk: What Is the Market Telling Us? , 2008 .

[39]  Thomas Lux,et al.  Evolvement of Uniformity and Volatility in the Stressed Global Financial Village , 2012, PloS one.

[40]  Wei-Xing Zhou,et al.  Evolution of Worldwide Stock Markets, Correlation Structure and Correlation Based Graphs , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[41]  Eshel Ben-Jacob,et al.  Dynamics of Stock Market Correlations , 2010 .

[42]  Measuring and Managing Federal Financial Risk , 2010 .

[43]  C. Granger.  Investigating Causal Relations by Econometric Models and Cross-Spectral Methods , 1969 .

[44]  N. Marwan,et al.  On interrelations of recurrences and connectivity trends between stock indices , 2011, 1103.5189.

[45]  C. Granger.  Testing for causality: a personal viewpoint , 1980 .

[46]  J. Bouchaud,et al.  Noise Dressing of Financial Correlation Matrices , 1998, cond-mat/9810255.

[47]  H. Stanley,et al.  Linking agent-based models and stochastic models of financial markets , 2012, Proceedings of the National Academy of Sciences.