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PRMIA 8007 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Stochastic Processes and Time Series | - Time series analysis
|
| Topic 2: Simulation and Numerical Methods | - Monte Carlo simulation
|
| Topic 3: Probability and Statistics Foundations | - Random variables and probability distributions
|
| Topic 4: Risk Measurement Techniques | - Volatility and correlation
|
PRMIA Exam II: Mathematical Foundations of Risk Measurement - 2015 Edition Sample Questions:
Find the first-order Taylor approximation p(x) for the function: at the point .
- A. x-1
- B. -x+1
- C. x+1
- D. -x
A simple linear regression is based on 100 data points. The total sum of squares is 1.5 and the correlation between the dependent and explanatory variables is 0.5. What is the explained sum of squares?
- A. 0.3333
- B. 0.375
- C. 1.125
- D. 0.75
In statistical hypothesis tests, 'Type I error' refers to the situation in which...
- A. The null hypothesis is accepted when in fact it should have been rejected
- B. Both null hypothesis and alternative hypothesis are rejected
- C. The null hypothesis is rejected when in fact it should have been accepted
- D. Both null hypothesis and alternative hypothesis are accepted
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 stationary
- B. The commodity prices are stationary
- C. The commodity returns are integrated of order 1
- D. None of the above
In a multiple linear regression, the significance of R2 can be tested using which distribution?
- A. Student's t distribution
- B. F-distribution
- C. Binomial distribution
- D. Normal distribution
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