Reading 4: Common Probability Distributions

50 questions available

Discrete and Continuous Probability Distributions10 min
This section defines random variables, outcomes, and events. It distinguishes between discrete random variables, where outcomes can be counted (e.g., binomial), and continuous random variables, where outcomes are infinite within a range (e.g., normal). It explains probability functions p(x) and cumulative distribution functions F(x). For continuous distributions, the probability of any single specific value is zero; probabilities are calculated for ranges of values.

Key Points

  • Discrete random variables have countable outcomes.
  • Continuous random variables have infinite possible outcomes within a range.
  • The probability of a specific value in a continuous distribution is zero.
  • A cumulative distribution function (cdf) F(x) gives the probability that X is less than or equal to x.
Uniform and Binomial Distributions15 min
The Uniform Distribution represents variables where every outcome is equally likely. In its continuous form, probabilities are proportional to the length of the interval. The Binomial Distribution models the number of successes in n independent trials, given a constant probability of success p. The formula for binomial probability involves the number of combinations of choosing x successes from n trials.

Key Points

  • Uniform distribution probabilities are constant across the range of outcomes.
  • Binomial distribution applies to independent trials with two outcomes (success/failure).
  • Expected value of a binomial variable is n * p.
  • Variance of a binomial variable is n * p * (1 - p).
Normal Distribution and Related Concepts20 min
The Normal Distribution is a symmetric, bell-shaped continuous distribution defined by its mean and variance. Key properties include zero skewness and a kurtosis of 3. The standard normal distribution has a mean of 0 and a standard deviation of 1. Z-scores are used to standardize observations. The section also covers confidence intervals and multivariate normal distributions, emphasizing the role of correlation.

Key Points

  • Normal distribution is symmetric around the mean.
  • Standard normal distribution: Mean = 0, Standard Deviation = 1.
  • 90 percent confidence interval: Mean +/- 1.65 standard deviations.
  • 95 percent confidence interval: Mean +/- 1.96 standard deviations.
  • Linear combinations of normal variables are also normal.
Lognormal, t, Chi-Square, and F Distributions20 min
This section introduces distributions used for specific financial modeling and testing. The Lognormal distribution is right-skewed and non-negative, ideal for asset prices. The Student's t-distribution is used when population variance is unknown, characterized by degrees of freedom and fatter tails than the normal. The Chi-Square distribution relates to squared normal variables (variance), and the F-distribution relates to the ratio of two variances. Monte Carlo simulation is presented as a method to model complex systems using random variables.

Key Points

  • Lognormal distribution is bounded by zero and skewed to the right.
  • Student's t-distribution has fatter tails than the normal, defined by degrees of freedom (n-1).
  • Chi-square and F-distributions are bounded by zero and used in hypothesis testing.
  • Monte Carlo simulation generates distributions of outcomes based on random inputs.

Questions

Question 1

Which of the following best describes a discrete random variable?

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Question 2

For a continuous uniform distribution defined between a lower limit a and an upper limit b, what is the probability that the random variable X takes on a value greater than b?

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Question 3

In a binomial distribution with n trials and probability of success p, what is the expected number of successes?

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Question 4

Which of the following is a key property of the normal distribution?

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Question 5

A portfolio manager wants to determine the probability that a portfolio's return will fall below a minimum acceptable level. Which measure should be maximized to minimize this probability?

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Question 6

How is a z-value calculated for a random variable X from a normal population?

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Question 7

For a lognormal distribution, which of the following statements is true regarding the possible values of the random variable?

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Question 8

What is the 95 percent confidence interval for a standard normal random variable?

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Question 9

If an investor has a holding period return of 20 percent over one year, what is the continuously compounded annual rate of return?

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Question 10

The Student's t-distribution approaches the standard normal distribution as:

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Question 11

Which of the following parameters is necessary to completely describe a multivariate normal distribution for the returns of n assets?

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Question 12

A chi-square distribution is bounded from below by:

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Question 13

Monte Carlo simulation is best described as a technique that:

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Question 14

If the probability of success in a single trial is 0.40, what is the probability of exactly 2 successes in 5 independent trials (Binomial distribution)?

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Question 15

What is the probability that a continuous uniform random variable defined between 2 and 10 takes on a value of exactly 5?

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Question 16

An analyst estimates the mean return of a stock to be 10 percent with a standard deviation of 20 percent. If returns are normally distributed, the 90 percent confidence interval for the return is:

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Question 17

Which of the following is a property of the standard normal distribution?

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Question 18

Shortfall risk is best defined as:

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Question 19

If an asset's price today is 100 and it increases to 110 over one year, what is the continuously compounded annual return?

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Question 20

Compared to the normal distribution, the Student's t-distribution has:

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Question 21

The F-distribution is defined by:

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Question 22

If a cumulative distribution function F(x) represents the probability that X is less than or equal to x, how is the probability that X lies between a and b calculated?

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Question 23

Which distribution is typically used to test the equality of variances of two normal populations?

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Question 24

A stock has an expected return of 12 percent and a standard deviation of 15 percent. If the threshold return is 2 percent, what is the Safety-First Ratio?

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Question 25

In a continuous uniform distribution ranging from 0 to 20, what is the probability that the random variable falls between 5 and 15?

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Question 26

What is the variance of a binomial random variable with n=10 trials and probability of success p=0.5?

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Question 27

When using Roy's Safety-First Criterion to choose among portfolios, which portfolio is preferred?

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Question 28

Which of the following is a characteristic of the lognormal distribution?

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Question 29

For a standard normal distribution, what is the probability that a value lies to the left of 0?

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Question 30

If the continuously compounded annual rate of return is 10 percent, what is the holding period return after 2 years?

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Question 31

What is a limitation of Monte Carlo simulation?

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Question 32

Which distribution describes the sum of squared values of n independent standard normal random variables?

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Question 33

In a binomial experiment with 1 trial, the distribution is called a:

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Question 34

For a normal distribution with mean 50 and standard deviation 5, what is the z-score of an observation of 60?

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Question 35

If a cumulative distribution function F(x) = 0.60, what does this indicate?

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Question 36

With 10 degrees of freedom, the t-distribution is:

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Question 37

Which of the following is true regarding a linear combination of normally distributed random variables?

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Question 38

If a stock's price is modeled using a lognormal distribution, what can be said about the stock's returns?

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Question 39

For a discrete uniform distribution with n possible outcomes, what is the probability of each outcome?

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Question 40

Roy's Safety-First Criterion states that the optimal portfolio maximizes:

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Question 41

What is the approximate probability that a normally distributed random variable falls within one standard deviation of the mean?

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Question 42

When constructing confidence intervals for small samples from populations with unknown variance, which distribution is most appropriate?

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Question 43

Which of the following is true about the F-distribution?

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Question 44

If a cumulative distribution function F(x) = x/10 for x in {1, 2, 3, 4}, what is F(3)?

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Question 45

What is the critical z-value for a 95 percent confidence interval?

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Question 46

In a simulation of stock option values, the process of generating random values for risk factors based on assumed distributions is a key step in:

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Question 47

If two events are independent, the probability of both occurring is determined by:

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Question 48

Which distribution uses the parameter 'degrees of freedom' equal to n - 1?

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Question 49

What is the lower bound of a normal distribution?

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Question 50

A key difference between a univariate and a multivariate normal distribution is:

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