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 08, 2026     Q & A: 133 Questions and Answers

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PRMIA 8007 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Statistics and Regression Analysis20%- Linear regression
  • 1. Simple and multiple regression
    • 2. Hypothesis testing and confidence intervals
      - Descriptive statistics
      • 1. Correlation and covariance
        • 2. Measures of location and dispersion
          Topic 2: Numerical Methods & Financial Mathematics15%- Basics of risk modeling
          - Time value of money
          - Root finding and approximation
          Topic 3: Calculus and Functions20%- Multivariable calculus
          • 1. Optimization
            • 2. Partial derivatives
              - Single-variable calculus
              • 1. Derivatives and applications
                • 2. Integrals and applications
                  • 3. Limits and continuity
                    Topic 4: Probability Theory25%- Basic probability concepts
                    • 1. Conditional probability and independence
                      • 2. Axioms and rules
                        - Random variables and distributions
                        • 1. Discrete and continuous distributions
                          • 2. Expected value, variance, covariance
                            Topic 5: Linear Algebra and Matrix Theory20%- Matrix operations
                            • 1. Addition, multiplication, inversion
                              • 2. Determinants and trace
                                - Vectors and eigenvalues
                                • 1. Diagonalization
                                  • 2. Eigenvalues and eigenvectors

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

                                    Question 1

                                    There are two portfolios with no overlapping of stocks or bonds. Portfolio 1 has 6 stocks and 6 bonds.
                                    Portfolio 2 has 4 stocks and 8 bonds. If we randomly select one stock, what is the probability that it came from Portfolio1?

                                    A. 0.3
                                    B. None of these
                                    C. 0.6
                                    D. 0.5


                                    Question 2

                                    In a portfolio there are 7 bonds: 2 AAA Corporate bonds, 2 AAA Agency bonds, 1 AA Corporate and 2 AA Agency bonds. By an unexplained characteristic the probability of any specific AAA bond outperforming the others is twice the probability of any specific AA bond outperforming the others. What is the probability that an AA bond or a Corporate bond outperforms all of the others?

                                    A. 5/7
                                    B. None of these
                                    C. 6/11
                                    D. 8/11


                                    Question 3

                                    Which of the following is not a direct cause of autocorrelation or heteroskedasticity in the residuals of a regression model?

                                    A. The omission of a relevant explanatory variable
                                    B. Using an inappropriate functional form in the model
                                    C. A structural break in the dependent variable
                                    D. A high positive correlation between two explanatory variables


                                    Question 4

                                    Which of the following can induce a 'multicollinearity' problem in a regression model?

                                    A. A high positive correlation between the dependent variable and one of the explanatory variables
                                    B. The omission of a relevant explanatory variable
                                    C. A large negative correlation between the dependent variable and one of the explanatory variables
                                    D. A high positive correlation between two explanatory variables


                                    Question 5

                                    An asset price S is lognormally distributed if:

                                    A. ln(1+dS/S) is normally distributed
                                    B. 1/S is normally distributed
                                    C. the change in price (dS) is normally distributed
                                    D. ln(dS/S) is normally distributed


                                    Solutions:

                                    Question 1
                                    Answer: C
                                    Question 2
                                    Answer: B
                                    Question 3
                                    Answer: D
                                    Question 4
                                    Answer: D
                                    Question 5
                                    Answer: A

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