PRMIA 8002 P R M Practice Questions| TestInsights

Question 1

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?

A0.75

B1.125

C0.3333

D0.375

Correct : D

Options Selected by Other Users:

Mark Question:

Start a Discussions

Submit Your Answer:

A0.75

B1.125

C0.3333

D0.375

Question 2

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)?

AThe commodity prices are stationary

BThe commodity returns are stationary

CThe commodity returns are integrated of order 1

DNone of the above

Correct : D

Options Selected by Other Users:

Mark Question:

Start a Discussions

Submit Your Answer:

AThe commodity prices are stationary

BThe commodity returns are stationary

CThe commodity returns are integrated of order 1

DNone of the above

Question 3

Maximum likelihood estimation is a method for:

AFinding parameter estimates of a given density function

BEstimating the solution of a partial differential equation

CSolving a portfolio optimization problem

DEstimating the implied volatility of a simple European option

Correct : A

Options Selected by Other Users:

Mark Question:

Start a Discussions

Submit Your Answer:

AFinding parameter estimates of a given density function

BEstimating the solution of a partial differential equation

CSolving a portfolio optimization problem

DEstimating the implied volatility of a simple European option

Question 4

Which of the following statements are true about Maximum Likelihood Estimation?

(i) MLE can be applied even if the error terms are not i.i.d. normal.

(ii) MLE involves integrating a likelihood function or a log-likelihood function.

(iii) MLE yields parameter estimates that are consistent.

A(i) and (ii)

B(i) only

C(i) and (iii)

D(i), (ii), and (iii)

Correct : C

Options Selected by Other Users:

Mark Question:

Start a Discussions

Submit Your Answer:

A(i) and (ii)

B(i) only

C(i) and (iii)

D(i), (ii), and (iii)

Question 5

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

AThe estimated mean divided by the estimated variance has a t-distribution

BThe estimated mean divided by the estimated variance has a Chi2-distribution

CThe estimated mean divided by the estimated standard deviation has a t-distribution

DThe estimated mean divided by the estimated standard deviation has a Chi2-distribution

Correct : C

Options Selected by Other Users:

Mark Question:

Start a Discussions

Submit Your Answer:

AThe estimated mean divided by the estimated variance has a t-distribution

BThe estimated mean divided by the estimated variance has a Chi2-distribution

CThe estimated mean divided by the estimated standard deviation has a t-distribution

DThe estimated mean divided by the estimated standard deviation has a Chi2-distribution

Curious about Actual PRMIA Mathematical Foundations of Risk Measurement (8002) Exam Questions?

Options Selected by Other Users:

Options Selected by Other Users:

Options Selected by Other Users:

Options Selected by Other Users:

Options Selected by Other Users: