Refine
Document Type
- Working Paper (2) (remove)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- Bootstrap (2) (remove)
Institute
This paper compares the accuracy of credit ratings of Moody s and Standard&Poors. Based on 11,428 issuer ratings and 350 defaults in several datasets from 1999 to 2003 a slight advantage for the rating system of Moody s is detected. Compared to former research the robustness of the results is increased by using nonparametric bootstrap approaches. Furthermore, robustness checks are made to control for the impact of Watchlist entries, staleness of ratings and the effect of unsolicited ratings on the results.
A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L. Klassifizierung: C22, C53, C63, G12