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

1. When the errors in a linear regression show signs of positive autocorrelation, which of the statements below is true?

A) The regression coefficient will be too low and the standard error of the regression coefficient will be overstated
B) The regression coefficient will be unbiased, but the standard error of the regression coefficient will be understated
C) The regression coefficient will be unbiased, but the standard error of the regression coefficient will be overstated
D) The regression coefficient will be too high and the standard error of the regression coefficient will be understated

2. What is the simplest form of this expression: log2(165/2)

A) log2 (5/2) + log2(16)
B) 5/2 + log2(16)
C) 32
D) 10

3. Calculate the determinant of the following matrix:

A) 2
B) 4
C) 4.25
D) -4.25

4. Variance reduction is:

A) A numerical method for finding portfolio weights to minimize the variance of a portfolio that has a given expected return
B) A numerical method for finding the variance of the underlying that is implicit in a market price of an option
C) A method for reducing the number of simulations required in a Monte Carlo simulation
D) A technique that is applied in regression models to improve the accuracy of the coefficient estimates

5. For the function f(x) =3x-x3 which of the following is true?

A) x = 0 is a minimum
B) None of these
C) x = 2 is a maximum
D) x = -3 is a maximum

Solutions: