Credit Risk Management Practice Exam

What is utilized to compute the default probability in a logistic regression model?

1. Dependent and independent variables

2. Historical market trends

3. Financial ratios of the firm

4. Variance calculations

The correct answer is: Dependent and independent variables

In a logistic regression model, the computation of default probability relies on the relationship between dependent and independent variables. The dependent variable in this context represents the binary outcome (such as default/no default), while the independent variables can include a wide array of factors such as financial ratios, credit scores, and other relevant predictors that influence the likelihood of default. By leveraging these variables, logistic regression quantifies the relationship through statistical methods, allowing for the estimation of the probability that a particular observation (such as a loan applicant) will default. The other options, while related to credit risk assessment, do not directly pertain to the mechanics of logistic regression. Historical market trends may inform the selection of independent variables but are not utilized in the computation itself. Financial ratios provide meaningful data points that can be developed into independent variables, but alone they are not sufficient for calculating default probability. Variance calculations do play a role in understanding variability and risk, but they do not directly contribute to the computation of default probability in the context of a logistic regression model.