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

Exam Code: 8007

Exam Name: Exam II: Mathematical Foundations of Risk Measurement - 2015 Edition

Updated: Sep 09, 2026

Q & A: 133 Questions and Answers

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PRMIA 8007 Exam Syllabus Topics:

SectionObjectives
Topic 1: Stochastic Processes and Time Series- Stochastic processes basics
  • 1. Brownian motion (introductory level)
    • 2. Markov processes
      - Time series analysis
      • 1. Autocorrelation and stationarity
        • 2. AR, MA, and ARMA models
          Topic 2: Simulation and Numerical Methods- Monte Carlo simulation
          • 1. Risk distribution simulation
            • 2. Random number generation
              Topic 3: Probability and Statistics Foundations- Statistical inference
              • 1. Estimation theory
                • 2. Confidence intervals and hypothesis testing
                  - Random variables and probability distributions
                  • 1. Discrete and continuous distributions
                    • 2. Expectation, variance, and moments
                      Topic 4: Risk Measurement Techniques- Value at Risk (VaR)
                      • 1. Parametric and non-parametric VaR
                        • 2. Historical simulation approach
                          - Volatility and correlation
                          • 1. Correlation estimation techniques
                            • 2. Variance-covariance methods

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

                              Question #1

                              Consider the following distribution data for a random variable X: What is the mean and variance of X?

                              • A. 3.5 and 3.45
                              • B. 3.4 and 3.84
                              • C. 3.6 and 7.15
                              • D. None of these
                              Reveal Solution  Discussion  0

                              Correct Answer: D  🗳️

                              Question #2

                              Which of the following is consistent with the definition of a Type I error?

                              • A. A Type I occurs whenever data series are serially correlated
                              • B. A Type I error would have occurred if the performance of a stock was positively correlated with the performance of a hedge fund, but in a linear regression, the hypothesis of positive correlation was rejected
                              • C. The probability of a Type I error is 100% minus the significance level
                              • D. A Type I error would have occurred if the performance of a stock was positively correlated with the performance of a hedge fund, but in a linear regression, the hypothesis of no correlation was rejected
                              Reveal Solution  Discussion  0

                              Correct Answer: B  🗳️

                              Question #3

                              You are given the following values of a quadratic function f(x): f(0)=0, f(1)=-2, f(2)=-5. On the basis of these data, the derivative f'(0) is ...

                              • A. in the interval ]-2,+[
                              • B. equal to -2
                              • C. in the interval ]-,-2.5]
                              • D. in the interval ]-2.5,-2[
                              Reveal Solution  Discussion  0

                              Correct Answer: A  🗳️

                              Question #4

                              Evaluate the derivative of ln(1+ x2) at the point x = 1

                              • A. 1
                              • B. 0.5
                              • C. 2
                              • D. 0
                              Reveal Solution  Discussion  0

                              Correct Answer: A  🗳️

                              Question #5

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

                              • A. Prediction
                              • B. Regression
                              • C. Estimation
                              • D. Hypothesis testing
                              Reveal Solution  Discussion  0

                              Correct Answer: A  🗳️

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