Nonlinearity in Investment-Grade Credit Default Swap (CDS) Indices of US and Europe : Evidence from BDS and Close-Returns Tests

This paper is aimed at testing for nonlinearity and chaos in Investment Grade CDS Indices of US and Europe. For this exercise, the author has chosen the two most liquid indices, namely CDX.NA.IG (US) and iTraxx.Europe (Europe). BDS test (Brock, Dechert, & Scheinkman, 1987) is employed to test for prevalence of nonlinearity in the US and European datasets. The author then subjects both the US and European datasets to the close-returns test (Gilmore, 1996; Gilmore, 1993; Gilmore, 2001) to examine whether the close-returns plots pertaining to these datasets exhibit any chaotic patterns. The CDS datasets were prepared differently for BDS and close-returns test. Since the BDS test cannot differentiate between linear and non-linear dependency, a best-fitting AR model was fitted to the transformed CDS datasets to remove linear-dependency in the data. The BDS test was then applied to the stationary, linearly-independent AR residuals pertaining to transformed US and European datasets. BDS test outcomes revealed rejection of null hypothesis (i.i.d.) with regard to US and European Investment-Grade CDS Indices. The close-returns test outcomes revealed prevalence of an underlying structure that is neither random nor chaotic in nature. In short, the study's findings reveal prevalence of non-chaotic nonlinearity in the US and European CDS indices. These findings not only augment existing literature on nonlinearity of different asset classes, but also reflect the need for researchers and practitioners to accommodate and appropriately account for nonlinearity while modeling CDS indices spread movements