Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey

In this paper, we investigate the relationship between industrial production and sectoral credit defaults (non-performing loans ratio) cycle by wavelet network analysis in Turkey over the period January 2001-November 2007. We use feedforward neural network based wavelet decomposition to analyze the contemporaneous connection between industrial production cycles and sectoral credit default cycles at different time scales between 2 and 64Â months. The main findings for Turkey indicates that industrial production cycles effect the sectoral credit default cycles at different time scales and thus indicate that the creditors should consider the multiscale sectoral cycles in order to minimize credit default rates.

[1]  Paul P Wang Information Sciences 2007 , 2007 .

[2]  Michael P. Clements,et al.  Business Cycle Asymmetries , 2003 .

[3]  S. Kim,et al.  Wavelet Methods for the Detection of Anomalies and their Application to Network Traffic Analysis , 2006, Qual. Reliab. Eng. Int..

[4]  Dimitrios Kavvathas,et al.  Estimating Credit Rating Transition Probabilities for Corporate Bonds , 2000 .

[5]  Yi Wen,et al.  Wavelet: a new tool for business cycle analysis , 2005 .

[6]  J. Kitchin Cycles and Trends in Economic Factors , 1923 .

[7]  Timotej Jagrič,et al.  METHOD OF ANALYZING BUSINESS CYCLES IN A TRANSITION ECONOMY: THE CASE OF SLOVENIA , 2004 .

[8]  Anil K. Bera,et al.  Efficient tests for normality, homoscedasticity and serial independence of regression residuals: Monte Carlo Evidence , 1981 .

[9]  Marianne Baxter,et al.  Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series , 1995, Review of Economics and Statistics.

[10]  R. Gencay,et al.  An Introduction to Wavelets and Other Filtering Methods in Finance and Economics , 2001 .

[11]  Til Schuermann,et al.  Macroeconomic Dynamics and Credit Risk: A Global Perspective , 2003, SSRN Electronic Journal.

[12]  Stephen Chen,et al.  Towards the automated design of phased array ultrasonic transducers: Using particle swarms to find "smart" start points , 2007 .

[13]  J. B. Ramsey,et al.  The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income , 1998 .

[14]  Halbert White,et al.  Artificial neural networks: an econometric perspective ∗ , 1994 .

[15]  Alper Ozun,et al.  A Signal Processing Model for Time Series Analysis: The Effects of International F/X Markets on Domestic Currencies Using Wavelet Networks (SCI-Expanded) , 2008 .

[16]  Ali M. Kutan,et al.  Do Regional Integration Agreements Increase Business-Cycle Convergence? Evidence from APEC and NAFTA , 2005 .

[17]  P. Phillips Testing for a Unit Root in Time Series Regression , 1988 .

[18]  Vladik Kreinovich,et al.  Maximum Entropy Approach to Fuzzy Control , 1994, Inf. Sci..

[19]  W. Perraudin,et al.  Stability of ratings transitions , 2001 .

[20]  Motohiro Yogo,et al.  Measuring Business Cycles: A Wavelet Analysis of Economic Time Series , 2008 .

[21]  Ramazan Gençay,et al.  Nonlinear modelling and prediction with feedforward and recurrent networks , 1997 .

[22]  R. Bowden,et al.  The agribusiness cycle and its wavelets , 2008 .

[23]  J. Keynes,et al.  The General Theory of Employment, Interest and Money. , 1936 .

[24]  Yuzo Honda,et al.  Do stock prices contain predictive information on business turning points? A wavelet analysis , 2005 .

[25]  W. Mitchell Business Cycles: The Problem and Its Setting. , 1928 .

[26]  Timotej Jagri,et al.  Measuring Business Cycles: The Case of Slovenia , 2002 .

[27]  Francis X. Diebold,et al.  Ratings Migration and the Business Cycle, With Application to Credit Portfolio Stress Testing , 2002 .

[28]  Ruey S. Tsay,et al.  Analysis of Financial Time Series , 2005 .

[29]  John G. Daugman,et al.  Complete discrete 2-D Gabor transforms by neural networks for image analysis and compression , 1988, IEEE Trans. Acoust. Speech Signal Process..

[30]  Siem Jan Koopman,et al.  Business and Default Cycles for Credit Risk , 2003 .

[31]  T. C. Wilson,et al.  Portfolio Credit Risk , 1998 .

[32]  W. Fuller,et al.  LIKELIHOOD RATIO STATISTICS FOR AUTOREGRESSIVE TIME SERIES WITH A UNIT ROOT , 1981 .

[33]  S. Koopman,et al.  Empirical credit cycles and capital buffer formation , 2005 .

[34]  Costas Milas,et al.  Nonlinear Time Series Analysis of Business Cycles , 2006 .

[35]  Anil K. Bera,et al.  Efficient tests for normality, homoscedasticity and serial independence of regression residuals , 1980 .

[36]  Greg Tkacz,et al.  Estimating the Fractional Order of Integration of Interest Rates Using a Wavelet OLS Estimator , 2001 .

[37]  Sharmishtha Mitra,et al.  Modeling exchange rates using wavelet decomposed genetic neural networks , 2006 .

[38]  L. Hurwicz,et al.  Measuring Business Cycles. , 1946 .

[39]  J. B. Ramsey,et al.  DECOMPOSITION OF ECONOMIC RELATIONSHIPS BY TIMESCALE USING WAVELETS , 1998, Macroeconomic Dynamics.

[40]  W. Perraudin,et al.  Stability of ratings transitions , 2001 .

[41]  James D. Hamilton A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .

[42]  Timotej Jagrič Business Cycles in Central and East European Countries , 2003 .

[43]  Anthony Saunders,et al.  A Survey of Cyclical Effects in Credit Risk Measurement Models , 2002 .