This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 298
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract - #307053
Title: Modeling the Dynamics of Corporate Credit Ratings: Creating a Predictive Ratings Model
Author(s): Meghan Rachel Kent*+ and Terri Anna Johnson and Nicole Bader and Jenna Rice
Companies: North Carolina State University and North Carolina State University and North Carolina State University and North Carolina State University
Address: , Raleigh, NC, 27695,
Keywords: bonds ; credit ; corporate ; risk ; ratings ; macroeconomic
Abstract:

Since the early 1900s, agencies like Standard and Poor's have developed corporate rating systems to evaluate the quality of various investments. Historical credit ratings data, from 1981-2002, were used with macroeconomic variables to create a predictive ratings model based on a Markov assumption and cumulative logistic regression estimation. Calibrated to information from S&P's 2002 Ratings Performance report, along with data on unemployment, one and ten-year interest rates, credit spread, and GDP from the Federal Reserve, the model takes into account a bond's current rating and current macroeconomic conditions to predict the probability of upgrades or downgrades as it matures. An awareness of ratings transition probabilities will help investors make more informed decisions regarding an "appropriate" level of risk.


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