PRMIA 8007 real exam prep : Exam II: Mathematical Foundations of Risk Measurement - 2015 Edition

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PRMIA 8007 Exam Syllabus Topics:

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

Question 1

If the annual volatility of returns is 25% what is the variance of the quarterly returns?

A. 0.1250
B. 0.0156
C. 0.0625
D. None of the above

Question 2

Suppose we perform a principle component analysis of the correlation matrix of the returns of 13 yields along the yield curve. The largest eigenvalue of the correlation matrix is 9.8. What percentage of return volatility is explained by the first component? (You may use the fact that the sum of the diagonal elements of a square matrix is always equal to the sum of its eigenvalues.)

A. Cannot be determined without estimates of the volatilities of the individual returns
B. 75%
C. 64%
D. 98%

Question 3

You are investigating the relationship between weather and stock market performance. To do this, you pick
100 stock market locations all over the world. For each location, you collect yesterday's mean temperature and humidity and yesterday's local index return. Performing a regression analysis on this data is an example of...

A. Simple time-series regression
B. Simple cross-section regression
C. Multiple time-series regression
D. Multiple cross-section regression

Question 4

The bisection method can be used for solving f(x)=0 for a unique solution of x, when

A. The function f(x) is continuous
B. The function f(x) is differentiable and we have an explicit expression for the derivative
C. The function f(x) is continuous and monotonic
D. The function f(x) is differentiable

Question 5

What can be said about observations of random variables that are i.i.d. a normally distributed?

A. The estimated mean divided by the estimated variance has a Chi2-distribution
B. The estimated mean divided by the estimated standard deviation has a Chi2-distribution
C. The estimated mean divided by the estimated variance has a t-distribution
D. The estimated mean divided by the estimated standard deviation has a t-distribution

Solutions: