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Maria has \(\$ 1\) she can invest in two assets, \(A\) and \(B\). A dollar invested in \(A\) has a \(50-50\) chance of returning 16 or nothing and in \(B\) has a \(50-50\) chance of returning 9 or nothing. Maria's utility over wealth is given by the function \(U(W)=\sqrt[0]{W}\) a. Suppose the assets' returns are independent. (1) Despite the fact that \(A\) has a much higher expected return than \(B\), show that Maria would prefer to invest half of her money in \(B\) rather than investing everything in \(A\) (2) Let \(a\) be the fraction of the dollar she invests in \(A\) What value would Maria choose if she could pick any \(a\) between 0 and \(1 ?\) Hint: Write down her expected utility as a function of \(a\) and then either graph this function and look for the peak or compute this function over the grid of values \(a=0,0.1,0.2,\) etc. b. Now suppose the assets' returns are perfectly negatively correlated: When \(A\) has a positive return, \(B\) returns nothing and vice versa. (1) Show that Maria is better off investing half her money in each asset now than when the assets' returns were independent. (2) If she can choose how much to invest in each, show that she would choose to invest a greater fraction in \(B\) than when assets' returns were independent.

Short Answer

Expert verified
Answer: To find the optimal investment allocation for Maria in both scenarios, we need to calculate the expected utility for various allocations of her investments and then compare the expected utilities under both independent and negatively correlated scenarios. The optimal allocation will be the one that maximizes Maria's expected utility in each respective case.

Step by step solution

01

Calculate expected utility for different allocations

To show Maria's preference, let's compare expected utility of investing \(0.5\) in A and \(0.5\) in B to investing \(1\) in A. First, let's find the respective wealth allocation for each of the possible investment outcomes: - Maria invests \(0.5\) in A and \(0.5\) in B: - A returns 16, B returns 0: W = \((0.5\cdot16) + (0.5\cdot0)\) - A returns 0, B returns 9: W = \((0.5\cdot0) + (0.5\cdot9)\) - Maria invests \(1\) in A: - A returns 16: W = \(1\cdot16\) - A returns 0: W = \(1\cdot0\) Now, let's calculate utility for each wealth allocation and find the expected utility for each investment strategy by taking the average. - Investing \(0.5\) in A and \(0.5\) in B, expected utility: - \(U_A = \frac{\sqrt[0]{(0.5\cdot16) + (0.5\cdot0)} + \sqrt[0]{(0.5\cdot0) + (0.5\cdot9)}}{2}\) - Investing \(1\) in A, expected utility: - \(U_B = \frac{\sqrt[0]{1\cdot16} + \sqrt[0]{1\cdot0}}{2}\)
02

Compare expected utilities

Now we can compare the expected utilities to verify whether Maria would prefer to invest half of her money in B rather than investing everything in A. If \(U_A > U_B\), then Maria would prefer investing half of her money in B. #a.2. Choosing the optimal fraction a#
03

Write Maria's expected utility as a function of a

Let \(a\) be the fraction of the dollar Maria invests in A. Then \((1-a)\) is the fraction invested in B. Considering all possible outcomes, the expected utility function can be expressed as follows: \(E(a)= \frac{\sqrt[0]{a\cdot16 + (1-a)\cdot0} + \sqrt[0]{a\cdot0 + (1-a)\cdot9}}{2}\)
04

Determine optimal a

To find the optimal investment fraction \(a\), we can either graph the function and look for the peak or compute the expected utility for a range of values between \(0\) and \(1\). By calculating \(E(a)\) for a range of values for \(a\) between 0 and 1 (in increments of 0.1), we can find the optimal value for a that maximizes Maria's expected utility. #b.1. Negatively correlated returns# Now suppose the returns are perfectly negatively correlated.
05

Calculate expected utility for different allocations

Let's calculate the expected utility for the negatively correlated scenario: - Investing \(0.5\) in A and \(0.5\) in B, expected utility: - \(U_C = \frac{\sqrt[0]{(0.5\cdot16) + (0.5\cdot0)} + \sqrt[0]{(0.5\cdot0) + (0.5\cdot9)}}{2}\)
06

Compare expected utilities

Now we can compare \(U_C\) with \(U_A\) to determine if Maria would be better off investing half her money in each asset with negatively correlated returns than when the assets' returns were independent: If \(U_C > U_A\), then Maria would be better off investing half her money in each asset with negatively correlated returns. #b.2. Finding the optimal allocation under negatively correlated returns#
07

Write Maria's expected utility as a function of a

Let's express the function for negatively correlated returns: \(E'(a)= \frac{\sqrt[0]{a\cdot16 + (1-a)\cdot0} + \sqrt[0]{a\cdot0 + (1-a)\cdot9}}{2}\)
08

Determine optimal a

Similar to part a.2., we can find the optimal a that maximizes the expected utility under negatively correlated returns by calculating \(E'(a)\) for a range of values between 0 and 1 (in increments of 0.1). By comparing the optimal values of \(a\) in independent and negatively correlated scenarios, we can determine if Maria would choose to invest a greater fraction in \(B\) when assets' returns are negatively correlated.

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Most popular questions from this chapter

Suppose there is a \(50-50\) chance that a risk-averse individual with a current wealth of \(\$ 20,000\) will contract a debilitating disease and suffer a loss of \(\$ 10,000\) a. Calculate the cost of actuar ially fair insurance in this situation and use a utility-of-wealth graph (such as shown in Figure 7.1 ) to show that the individual will prefer fair insurance against this loss to accepting the gamble uninsured. b. Suppose two types of insurance policies were available: (1) a fair policy covering the complete loss and (2) a fair policy covering only half of any loss incurred. Calculate the cost of the second type of policy and show that the individual will generally regard it as inferior to the first.

A farmer believes there is a \(50-50\) chance that the next growing season will be abnormally rainy. His expected utility function has the form \\[ E[U(Y)]=\frac{1}{2} \ln Y_{N R}+\frac{1}{2} \ln Y_{R} \\] where \(Y_{N R}\) and \(Y_{R}\) represent the farmer's income in the states of "normal rain" and "rainy," respectively. a. Suppose the farmer must choose between two crops that promise the following income prospects: \\[ \begin{array}{lcc} \text { Crop } & Y_{N R} & Y_{R} \\ \hline \text { Wheat } & \$ 28,000 & \$ 10,000 \\ \text { Corn } & \$ 19,000 & \$ 15,000 \end{array} \\] Which of the crops will he plant? b. Suppose the farmer can plant half his field with each crop. Would he choose to do so? Explain your result. c. What mix of wheat and corn would provide maximum expected utility to this farmer? d. Would wheat crop insurance-which is available to farmers who grow only wheat and which costs \(\$ 4,000\) and pays off \(\$ 8,000\) in the event of a rainy growing season-cause this farmer to change what he plants?

An individual purchases a dozen eggs and must take them home. Although making trips home is costless, there is a 50 percent chance that all the eggs carried on any one trip will be broken during the trip. The individual considers two strategies: (1) take all 12 eggs in one trip or (2) take two trips with six eggs in each trip. a. List the possible outcomes of each strategy and the probabilities of these outcomes. Show that, on average, six eggs will remain unbroken after the trip home under either strategy. b. Develop a graph to show the utility obtainable under each strategy. Which strategy will be preferable? c. Could utility be improved further by taking more than two trips? How would this possibility be affected if additional trips were costly?

Two pioneers of the field of behavioral economics, Daniel Kahneman (winner of the Nobel Prize in economics and author of bestselling book Thinking Fast and Slow) and Amos Tversky (deceased before the prize was awarded), conducted an experiment in which they presented different groups of subjects with one of the following two scenarios: \(\bullet\) Scenario 1: In addition to \(\$ 1,000\) up front, the subject must choose between two gambles. Gamble \(A\) offers an even chance of winning \(\$ 1,000\) or nothing. Gamble \(B\) provides \(\$ 500\) with certainty. \(\bullet\) Scenario 2: In addition to \(\$ 2,000\) given up front, the subject must choose between two gambles. Gamble \(C\) offers an even chance of losing \(\$ 1,000\) or nothing. Gamble \(D\) results in the loss of \(\$ 500\) with certainty. a. Suppose Standard Stan makes choices under uncertainty according to expected utility theory. If Stan is risk neutral, what choice would he make in each scenario? b. What choice would Stan make if he is risk averse? c. Kahneman and Tversky found 16 percent of subjects chose \(A\) in the first scenario and 68 percent chose \(C\) in the second scenario. Based on your preceding answers, explain why these findings are hard to reconcile with expected utility theory. d. Kahneman and Tversky proposed an alternative to expected utility theory, called prospect theory, to explain the experimental results. The theory is that people's current income level functions as an "anchor point" for them. They are risk averse over gains beyond this point but sensitive to small losses below this point. This sensitivity to small losses is the opposite of risk aversion: A risk-averse person suffers disproportionately more from a large than a small loss. (1) Prospect Pete makes choices under uncertainty according to prospect theory. What choices would he make in Kahneman and Tversky's experiment? Explain. (2) Draw a schematic diagram of a utility curve over money for Prospect Pete in the first scenario. Draw a utility curve for him in the second scenario. Can the same curve suffice for both scenarios, or must it shift? How do Pete's utility curves differ from the ones we are used to drawing for people like Standard Stan?

In Equation 7.30 we showed that the amount an individual is willing to pay to avoid a fair gamble \((h)\) is given by \(p=0.5 E\left(h^{2}\right) r(W),\) where \(r(W)\) is the measure of absolute risk aversion at this person's initial level of wealth. In this problem we look at the size of this payment as a function of the size of the risk faced and this person's level of wealth. a. Consider a fair gamble \((v)\) of winning or losing \(\$ 1 .\) For this gamble, what is \(E\left(v^{2}\right) ?\) b. Now consider varying the gamble in part (a) by multiplying each prize by a positive constant \(k .\) Let \(h=k v .\) What is the value of \(E\left(h^{2}\right)\) ? c. Suppose this person has a logarithmic utility function \(U(W)=\ln W .\) What is a general expression for \(r(W) ?\) d. Compute the risk premium \((p)\) for \(k=0.5,1,\) and 2 and for \(W=10\) and \(100 .\) What do you conclude by comparing the six values?

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