starting with the finished version of example 6.2, change the decision criterion to \maximize expected…

starting with the finished version of example 6.2, change the decision criterion to \maximize expected utility,\ using an exponential utility function with risk tolerance $5,000,000. display certainty equivalents on the tree.\na. keep doubling the risk tolerance until the companys best strategy is the same as with the emv criterion - continue with development and then market if successful.\nthe risk tolerance must reach $160,000,000 before the risk averse company acts the same as the emv - maximizing company.\nb. with a risk tolerance of $320,000,000, the company views the optimal strategy as equivalent to receiving a sure $, even though the emv from the original strategy (with no risk tolerance) is $. (round your final answer to the nearest $100, if necessary.)

starting with the finished version of example 6.2, change the decision criterion to \maximize expected utility,\ using an exponential utility function with risk tolerance $5,000,000. display certainty equivalents on the tree.\na. keep doubling the risk tolerance until the companys best strategy is the same as with the emv criterion - continue with development and then market if successful.\nthe risk tolerance must reach $160,000,000 before the risk averse company acts the same as the emv - maximizing company.\nb. with a risk tolerance of $320,000,000, the company views the optimal strategy as equivalent to receiving a sure $, even though the emv from the original strategy (with no risk tolerance) is $. (round your final answer to the nearest $100, if necessary.)

Answer

Explanation:

Step1: Recall exponential utility function

The exponential utility function is $U(x)= -e^{-\frac{x}{R}}$, where $x$ is the monetary outcome and $R$ is the risk - tolerance. The expected utility $EU$ is calculated as the sum of the utilities of all possible outcomes weighted by their probabilities. However, since the original EMV (Expected Monetary Value) details and probabilities are not given in the problem statement, we assume a general approach. When the risk - tolerance is high, the behavior of the exponential - utility - based decision - maker approaches that of an EMV - maximizer.

Step2: Analyze part b

For part b, we need to use the properties of the exponential utility function and certainty equivalents. The certainty equivalent $CE$ is the amount of money for which a decision - maker is indifferent between taking a sure amount and taking a risky gamble. When $R = 320000000$, we would calculate the expected utility of the optimal strategy and then find the $CE$ such that $U(CE)=EU$. But without the full decision - tree details (probabilities and pay - offs of all branches), we assume a simplified case. In general, as $R$ increases, the risk - averse behavior diminishes. Since we don't have the original EMV value and full details of the decision tree, we can't perform a full calculation. But we know that as the risk - tolerance increases, the certainty equivalent of the optimal strategy will be closer to the EMV of the original (risk - neutral) strategy.

Answer:

Since the problem lacks the necessary details such as the original EMV value, probabilities of the decision - tree branches and pay - offs, we cannot provide a numerical answer for part b.