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PRMIA Exam II: Mathematical Foundations of Risk Measurement - 2015 Edition Sample Questions:

1. Every covariance matrix must be positive semi-definite. If it were not then:

A) Some portfolios could have a negative variance
B) It could not be used to simulate correlated asset paths
C) All the above statements are true
D) The associated correlation matrix would not be positive semi-definite

2. An indefinite integral of a polynomial function is

A) always positive
B) always increasing
C) always less than the function itself
D) none of the above

3. Exploring a regression model for values of the independent variable that have not been observed is most accurately described as...

A) Regression
B) Hypothesis testing
C) Estimation
D) Prediction

4. In a quadratic Taylor approximation, a function is approximated by:

A) a parabola
B) a constant
C) a cubic polynomial
D) a straight line

5. Every covariance matrix must be positive semi-definite. If it were not then:

A) Some portfolios could have a negative variance
B) One or more of its eigenvalues would be negative
C) All the above statements are true
D) There would be no Cholesky decomposition matrix

Solutions: