Sequential Surveillance of Structural Breaks in Firms' Credit Rating Migrations

• Activity Number: 173
• Type: Topic Contributed
• Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Section on Risk Analysis
• Author(s): Ke Wang* and Haipeng Xing
• Companies: SUNY Stony Brook and SUNY Stony Brook
• Keywords: credit rating migration ; structural breaks ; surveillance ; detection rule

Abstract

Recent studies have shown that firms' credit rating migration process is not stationary and may have structural breaks. Assuming the generator of probability transition matrices of firms' credit rating to be piecewise constant and the jump time of generator corresponds to the structural break time in the pattern of firms' rating migrations, we study several types of sequential surveillance rules for early detection. The surveillance rules we investigated include the Shewhart control chart, an generalized likelihood ratio (GLR) detection rule for a single change-point with unknown pre- and post-change transition matrices, a detection rule based on an extension of Shiryaev's Bayes single change-point model, and a detection rule for multiple unknown structural breaks. We provide theoretical discussion and extensive simulations to compare the performance of these rules. We further use these rules to online detect structural breaks in firms' credit rating migrations based on U.S. firms' rating record from 1986 to 2012.