Measuring the Sensitivity of Credit Ratings to Macroeconomic Indicators across Business Sectors; A Study on the US Market
(2019) NEKN02 20191Department 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)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8998119
- author
- Ashour, Hazem LU and Silfverberg, Oliwer LU
- supervisor
- organization
- course
- NEKN02 20191
- year
- 2019
- 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}}, }