medium · FRM Part 1 Quantitative Analysis
A financial analyst is using an F-test to compare the model fits of two nested regressions. Regression 1 (the restricted model) has R^2 = 0.45 and Regression 2 (the unrestricted model) has R^2 = 0.50.
What does the F-test fundamentally evaluate in this scenario?
- Whether the intercept in the unrestricted model is zero.
- Whether the two models have equal residual variances.
- Whether the correlation between the error terms is significant.
- Whether the additional variables in the unrestricted model jointly add significant explanatory power.
Sign up free to see the explanation and track your rank →
More FRM Part 1 Quantitative Analysis practice
- A probability distribution that is asymmetric and has a significantly long tail extending
- A single discrete trial that results in exactly one of two possible outcomes (success or f
- How does the mean of a lognormal distribution compare to the mean of its associated normal
- If an analyst says a return series has 'fat tails,' what does this imply for a risk model
- If the correlation between two assets is -1.0, what does this indicate about their co-move
- In Bayesian inference, what does the term 'Updating' refer to?
- In combinatorics, which coefficient represents the number of ways to select r items from a
- In the context of credit risk, if D is the event of default and F is a model flag, how is