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Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey
Authors:Atilla Cifter   Sait Yilmazer  Elif Cifter  
Affiliation:aDepartment of Econometrics, Marmara University, Istanbul and Sekerbank, Turkey;bRisk Management, Tekstilbank, Istanbul, Turkey
Abstract: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 64 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.
Keywords:Sectoral credit default cycles   Business cycles   Wavelets   Wavelet networks
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