The study extends the theoretical framework proposed to decompose rating migration matrices from bond market price data. Method to decompose default probability term structures for and from interest rate term structures for different rating categories, is delineated and empirically evaluated. Emphasis is squarely on using ahistorical (non-historical) market data, and utilizing actual market perceptions regarding default probabilities. The method naturally allows a mapping and transitioning between interest rate term structures and default probability term structures. Mapping to and fro interest rate term structures and default probability term structures introduces an additional level of triangulation and evaluation. The study examines the corresponding interest rate term structures of the default probability term structures of a typical rating migration matrix, and the corresponding default probability term structures of a typical market interest rate term structure set. It is found...
Category - Brian BARNARD
Wits Business School, University of the Witwatersrand (WITS), South Africa
The study builds on previous research that decomposes rating category default probability term structures from rating category interest rate term structures, and proposes a method to decompose rating migration matrices from market data, via decomposed default probability term structures. To investigate the power and accuracy of the proposed method, it was examined to what extent an existing, known rating migration matrix could again be surfaced by the method. Overall, the results are more than satisfactory, and the method promises to be accurate. Although not considered here, the main objective is the application of the method to market data. The outcome should be insightful in itself, and can be used to evaluate historical rating migration matrices commonly devised by rating agencies, and to form a better understanding of the default probability term structures embedded in market data.