Quizsummary
0 of 10 questions completed
Questions:
 1
 2
 3
 4
 5
 6
 7
 8
 9
 10
Information
Certdemy Access
You have already completed the quiz before. Hence you can not start it again.
Quiz is loading...
You must sign in or sign up to start the quiz.
You have to finish following quiz, to start this quiz:
Results
0 of 10 questions answered correctly
Your time:
Time has elapsed
You have reached 0 of 0 points, (0)
Categories
 Not categorized 0%
 1
 2
 3
 4
 5
 6
 7
 8
 9
 10
 Answered
 Review

Question 1 of 10
1. Question
In some fields it is more common to refer to the normal distribution as which of the following?
I. the Heisenberg distribution
II. the Freudor distribution
III. the Gaussian distribution
IV. the weight distributionCorrect
In some fields it is more common to refer to the normal distribution as the Gaussian distribution, after the famous German mathematician Johann Gauss, who is credited with some of the earliest work with the distribution.
Incorrect
In some fields it is more common to refer to the normal distribution as the Gaussian distribution, after the famous German mathematician Johann Gauss, who is credited with some of the earliest work with the distribution.

Question 2 of 10
2. Question
Normal distributions can generate numbers from negative infinity to positive infinity. For a particular normal distribution, the most extreme values might be considered to be?
I. Extremely unlikely but can still occur
II. Extremely likely
III. Plausible
IV. Extremely unlikelyCorrect
Normal distributions can generate numbers from negative infinity to positive infinity. For a particular normal distribution, the most extreme values might be extremely unlikely, but they can occur.
Incorrect
Normal distributions can generate numbers from negative infinity to positive infinity. For a particular normal distribution, the most extreme values might be extremely unlikely, but they can occur.

Question 3 of 10
3. Question
Normally distributed log returns are widely used in financial simulations, and form the basis of a number of financial models, including which of the following?
I. The equity pricing model.
II. The Projectbased pricing model
III. The Valuebased pricing model.
IV. The BlackScholes option pricing model.Correct
Normally distributed log returns are widely used in financial simulations, and form the basis of a number of financial models, including the BlackScholes option pricing model.
Incorrect
Normally distributed log returns are widely used in financial simulations, and form the basis of a number of financial models, including the BlackScholes option pricing model.

Question 4 of 10
4. Question
Because the normal distribution is so widely used, most practitioners are expected to have at least a rough idea of how much of the distribution falls within which of the following?
I. one standard deviation
II. two standard deviations
III. three standard deviations
IV five standard deviationsCorrect
Because the normal distribution is so widely used, most practitioners are expected to have at least a rough idea of how much of the distribution falls within one, two, or three standard deviations.
Incorrect
Because the normal distribution is so widely used, most practitioners are expected to have at least a rough idea of how much of the distribution falls within one, two, or three standard deviations.

Question 5 of 10
5. Question
In risk management it is also useful to know how many standard deviations are needed to encompass how many percent of outcomes?
I. 75 percent of outcomes.
II. 95 percent of outcomes.
III. 99 percent of outcomes.
IV. 100 percent of outcomes.Correct
In risk management it is also useful to know how many standard deviations are needed to encompass 95 percent or 99 percent of outcomes.
Incorrect
In risk management it is also useful to know how many standard deviations are needed to encompass 95 percent or 99 percent of outcomes.

Question 6 of 10
6. Question
While some problems in risk management have explicit analytic solutions, many problems have no exact mathematical solution. In these cases, we can often approximate a solution by creating which of the following?
I. A Monte Carlo simulation.
II. A probability simulation.
III. A Waldo simulation.
IV. A Carana simulation.Correct
While some problems in risk management have explicit analytic solutions, many problems have no exact mathematical solution. In these cases, we can often approximate a solution by creating a Monte Carlo simulation.
Incorrect
While some problems in risk management have explicit analytic solutions, many problems have no exact mathematical solution. In these cases, we can often approximate a solution by creating a Monte Carlo simulation.

Question 7 of 10
7. Question
What is the present value of an offer of $14,000 one year from now if the opportunity cost of capital (discount rate) is 11% per year simple interest?
I. $12,613.3
II. $12,689.1
III. $15,877.5
IV. $13,758.1Correct
Answer: 14000/1.11=$12,613.3
Incorrect
Answer: 14000/1.11=$12,613.3

Question 8 of 10
8. Question
If you invested $15,000 at one point in time and received back $30,000 five years later, what annual interest (or growth) rate (compounded annually) would you have obtained?
I. 15%
II. 13%
III. 14.87%
IV. 14.59%Correct
(30000/15000)(1/5) – 1 = 14.87%
Incorrect

Question 9 of 10
9. Question
A time series is an equation or set of equations describing which of the following?
I. How variables evolves over time.
II. How a random variable evolves over time.
III. How certain assumptions evolves over time.
IV. How equation variables evolves over time.Correct
A time series is an equation or set of equations describing how a random variable or variables evolves over time.
Incorrect
A time series is an equation or set of equations describing how a random variable or variables evolves over time.

Question 10 of 10
10. Question
the most popular statistic for describing linear regressions is
I. The coefficient of determination
II. The Rsquared
III. The TSquared
IV. The casio regressionCorrect
Probably the most popular statistic for describing linear regressions is the coefficient of determination, commonly known as Rsquared, or just R2. R2 is often described as the goodness of fit of the linear regression.
Incorrect
Probably the most popular statistic for describing linear regressions is the coefficient of determination, commonly known as Rsquared, or just R2. R2 is often described as the goodness of fit of the linear regression.