JustasS

The probability density function of a continuous uniform distribution is best described by a:

A) line segment with a curvilinear slope.

B) line segment with a 45-degree slope.

C) horizontal line segment.

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By definition, for a continuous uniform distribution, the probability density function is a horizontal line segment over a range of values such that the area under the segment (total probability of an outcome in the range) equals one.

JustasS

A discount brokerage firm states that the time between a customer order for a trade and the execution of the order is uniformly distributed between three minutes and fifteen minutes. If a customer orders a trade at 11:54 A.M., what is the probability that the order is executed after noon?

A) 0.750.

B) 0.500.

C) 0.250.

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The limits of the uniform distribution are three and 15. Since the problem concerns time, it is continuous. Noon is six minutes after 11:54 A.M. The probability the order is executed after noon is (15 − 6) / (15 − 3) = 0.75.

JustasS

A portfolio begins the year with a value of $100,000 and ends the year with a value of $95,000. The manager’s performance is measured against an index that declined by 7% on a total return basis during the year. The tracking error of this portfolio is closest to:

A) −2%.

B) −5%.

C) 2%.

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Tracking error is the portfolio total return minus the benchmark total return. The portfolio return is ($95,000 − $100,000) / $100,000 = −5%. Tracking error = −5% − (−7%) = +2%.

JustasS

Tracking error for a portfolio is best described as the:

A) sample mean minus population mean.

B) portfolio return minus a benchmark return.

C) standard deviation of differences between an index return and portfolio return.

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Tracking error is the difference between the total return on a portfolio and the total return on the benchmark used to measure the portfolio’s performance. The difference between a sample statistic and a population parameter is sampling error. The standard deviation of the difference between a portfolio return and an index (or any chosen benchmark return) is more often referred to as tracking risk.

JustasS

A stock priced at $100 has a 70% probability of moving up and a 30% probability of moving down. If it moves up, it increases by a factor of 1.02. If it moves down, it decreases by a factor of 1/1.02. What is the probability that the stock will be $100 after two successive periods?

A) 21%.

B) 9%.

C) 42%.

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For the stock to be $100 after two periods, it must move up once and move down once: $100 × 1.02 × (1/1.02) = $100. This can happen in one of two ways: 1) the stock moves up during period one and down during period two; or 2) the stock moves down during period one and up during period two. The probability of either event is 0.70 × 0.30 = 0.21. The combined probability of either event is 2(0.21) = 0.42 or 42%.

JustasS

A stock priced at $20 has an 80% probability of moving up and a 20% probability of moving down. If it moves up, it increases by a factor of 1.05. If it moves down, it decreases by a factor of 1/1.05. What is the expected stock price after two successive periods?

A) $21.24.

B) $20.05.

C) $22.05.

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If the stock moves up twice, it will be worth $20 × 1.05 × 1.05 = $22.05. The probability of this occurring is 0.80 × 0.80 = 0.64. If the stock moves down twice, it will be worth $20 × (1/1.05) × (1/1.05) = $18.14. The probability of this occurring is 0.20 × 0.20 = 0.04. If the stock moves up once and down once, it will be worth $20 × 1.05 × (1/1.05) = $20.00. This can occur if either the stock goes up then down or down then up. The probability of this occurring is 0.80 × 0.20 + 0.20 × 0.80 = 0.32. Multiplying the potential stock prices by the probability of them occurring provides the expected stock price: ($22.05 × 0.64) + ($18.14 × 0.04) + ($20.00 × 0.32) = $21.24.

JustasS

A stock priced at $10 has a 60% probability of moving up and a 40% probability of moving down. If it moves up, it increases by a factor of 1.06. If it moves down, it decreases by a factor of 1/1.06. What is the expected stock price after two successive periods?

A) $10.27.

B) $10.03.

C) $11.24.

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If the stock moves up twice, it will be worth $10 × 1.06 × 1.06 = $11.24. The probability of this occurring is 0.60 × 0.60 = 0.36. If the stock moves down twice, it will be worth $10 × (1/1.06) × (1/1.06) = $8.90. The probability of this occurring is 0.40 × 0.40 = 0.16. If the stock moves up once and down once, it will be worth $10 × 1.06 × (1/1.06) = $10.00. This can occur if either the stock goes up then down or down then up. The probability of this occurring is 0.60 × 0.40 + 0.40 × 0.60 = 0.48. Multiplying the potential stock prices by the probability of them occurring provides the expected stock price: ($11.24 × 0.36) + ($8.90 × 0.16) + ($10.00 × 0.48) = $10.27.

JustasS

For a certain class of junk bonds, the probability of default in a given year is 0.2. Whether one bond defaults is independent of whether another bond defaults. For a portfolio of five of these junk bonds, what is the probability that zero or one bond of the five defaults in the year ahead?

A) 0.0819.

B) 0.4096.

C) 0.7373.

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The outcome follows a binomial distribution where n = 5 and p = 0.2. In this case p(0) = 0.85 = 0.3277 and p(1) = 5 × 0.84 × 0.2 = 0.4096, so P(X=0 or X=1) = 0.3277 + 0.4096.

JustasS

Which of the following is NOT an assumption of the binomial distribution?

A) The trials are independent.

B) The expected value is a whole number.

C) Random variable X is discrete.

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The expected value is n × p. A simple example shows us that the expected value does not have to be a whole number: n = 5, p = 0.5, n × p = 2.5. The other conditions are necessary for the binomial distribution.

JustasS

Which of the following could be the set of all possible outcomes for a random variable that follows a binomial distribution?

A) (-1, 0, 1).

B) (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11).

C) (1, 2).

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This reflects a basic property of binomial outcomes. They take on whole number values that must start at zero up to the upper limit n. The upper limit in this case is 11.