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Measuring the Sensitivity of Credit Ratings to Macroeconomic Indicators across Business Sectors; A Study on the US Market

Ashour, Hazem LU and Silfverberg, Oliwer LU (2019) NEKN02 20191
Department of Economics
Abstract
This paper examines the sensitivity of credit ratings to macroeconomic indicators, with a focus on monetary policy tools, across eleven business sectors in the United States. We examine the data using ordered probit and random forest models, taking into account firm fundamentals that measure the business and the financial risk, in addition to the macroeconomic indicators. Employing quarterly credit ratings by Standard \& Poor's for 299 American companies from 1985 till 2016, we find that firm-specific risk factors commonly have more explanatory power in determining credit rating classes. In addition, the findings suggest that business sectors respond differently to changes in the macroeconomic indicators, with some variables displaying... (More)
This paper examines the sensitivity of credit ratings to macroeconomic indicators, with a focus on monetary policy tools, across eleven business sectors in the United States. We examine the data using ordered probit and random forest models, taking into account firm fundamentals that measure the business and the financial risk, in addition to the macroeconomic indicators. Employing quarterly credit ratings by Standard \& Poor's for 299 American companies from 1985 till 2016, we find that firm-specific risk factors commonly have more explanatory power in determining credit rating classes. In addition, the findings suggest that business sectors respond differently to changes in the macroeconomic indicators, with some variables displaying high significance while others being indubitably insignificant. (Less)
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author
Ashour, Hazem LU and Silfverberg, Oliwer LU
supervisor
organization
course
NEKN02 20191
year
type
H1 - Master's Degree (One Year)
subject
language
English
id
8998119
date added to LUP
2020-02-27 13:54:34
date last changed
2020-02-27 13:54:34
@misc{8998119,
  abstract     = {{This paper examines the sensitivity of credit ratings to macroeconomic indicators, with a focus on monetary policy tools, across eleven business sectors in the United States. We examine the data using ordered probit and random forest models, taking into account firm fundamentals that measure the business and the financial risk, in addition to the macroeconomic indicators. Employing quarterly credit ratings by Standard \& Poor's for 299 American companies from 1985 till 2016, we find that firm-specific risk factors commonly have more explanatory power in determining credit rating classes. In addition, the findings suggest that business sectors respond differently to changes in the macroeconomic indicators, with some variables displaying high significance while others being indubitably insignificant.}},
  author       = {{Ashour, Hazem and Silfverberg, Oliwer}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Measuring the Sensitivity of Credit Ratings to Macroeconomic Indicators across Business Sectors; A Study on the US Market}},
  year         = {{2019}},
}