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PRMIA 8007 Exam Syllabus Topics:

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

Question 1

Which of the provided answers solves this system of equations?
2y - 3x = 3y +x
y2 + x2 = 68

A. x = 2; y = -8
B. x = 2; y = 8
C. x = 1; y = square root of 67
D. x = -2; y = -8

Question 2

A linear regression gives the following output:
Figures in square brackets are estimated standard errors of the coefficient estimates. What is the value of the test statistic for the hypothesis that the coefficient of is zero against the alternative that is less than zero?

A. 0.125
B. -2.5
C. 2.5
D. -1.25

Question 3

Identify the type and common element (that is, common ratio or common difference) of the following sequence: 6, 12, 24

A. arithmetic sequence, common ratio 2
B. geometric sequence, common ratio 3
C. geometric sequence, common ratio 2
D. arithmetic sequence, common difference 2

Question 4

You are given the following regressions of the first difference of the log of a commodity price on the lagged price and of the first difference of the log return on the lagged log return. Each regression is based on 100 data points and figures in square brackets denote the estimated standard errors of the coefficient estimates:
Which of the following hypotheses can be accepted based on these regressions at the 5% confidence level (corresponding to a critical value of the Dickey Fuller test statistic of - 2.89)?

A. The commodity returns are integrated of order 1
B. The commodity prices are stationary
C. The commodity returns are stationary
D. None of the above

Question 5

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

Solutions: