# See the problem below. Please make sure to add all the formulas and answer each part in problem#1

See the problem below.

Please make sure to add all the formulas and answer each part in problem#1 and develop the tee with their decision and chance nodes for problem#2.

Thanks,

Problem # 1

How much will an employee’s portfolio be worth after working for the company 30 years more? The Human Resource department at EcoCarnifex Corporation was asked to develop a financial planning model that would help employees address this question. Frank Joseph was asked to lead this effort, and he has decided to begin developing a financial plan for himself first. Frank has a degree in business and at the age of 30 in 2017. At the beginning of 2017, he is making the annual salary \$35,000 and has accumulated a portfolio valued at \$15,000.

a) 5% annual salary growth at the end of each year is reasonable.

b) He plans to contribute 5% of his monthly salary throughout each year.

c) 10% annual portfolio growth seems reasonable.

(1) Develop an Excel worksheet that calculates and shows the value at the end of each year of Frank’s portfolio after he will work for the company 35 years more (i.e., at the end of 2051).

(2) If Frank plans to work for the company 30 years more instead and hopes to accumulate a portfolio valued at \$1,000,000 for his retirement by the end of 2046. Can he, do it? Why or why not. Please explain in detail. If not, what he should do?

Frank has presented his findings based upon the above assumptions to his boss, but his boss does not agree with it. Instead, his boss made the following assumptions.

a) The annual salary growth should not be constant. It should vary from 0 to 8% following a uniform probability distribution.

b) The annual portfolio growth rate should be approximated by anormal probability distribution with a mean of 8% and a standard deviation of 5%.

(3) Develop an Excel worksheet with this new information and then use @Risk to perform this simulation (using 1000 iterations) that calculates and shows the value at the end of each year of Frank’s portfolio after he will work for the company 35 years more (i.e., at the end of 2051).

(4) Based on (3), can Frank accumulate a portfolio valued at\$1,000,000 for his retirement by the end of 2046? Why or why not. Please explain in detail.

(5) Attach the simulation graph result at the end of 35 years more as an output.

(6) Based upon the graph result, what is the probability that Frank will have at least \$1,000,000 of his portfolio value for his retirement at the end of 2051?

Note that Part 1 and Part 3 solutions must be separated.

Please note both problem#1 needs to be delivered in Excel format with all the formulas. For problem#2, it also needs to be delivered in Excel format too with the decision tree that shows the decision and and chance nodes.

Problem#2/

Ben Traders, a privately held U.S. metals broker, has acquired an option to purchase one million kilograms of partially refined molyzirconium ore from the Meldavian government for \$5.00 per kilogram. Molyzirconium can be processed into several different products which are used in semiconductor manufacturing, and George Ben, the owner of Ben Traders, estimates that he would be able to sell the ore for \$8.00 per kilogram after importing it. However, the U.S. government is currently negotiating with Meldavia over alleged dumping of certain manufactured goods which that country exports to the United States. As part of these negotiations, the U.S. government has threatened to ban the import from Meldavia of a class of materials that includes molyzirconium. If the U.S. government refuses to issue an import license for the molyzirconium after Ben has purchased it, then Ben will have to pay a penalty of \$1.00 per kilogram to the Meldavian government to annul the purchase of the molyzirconium. Ben has used the services of John A. Analyst, a decision analyst, to help in making decisions of this type in the past, and George Ben calls on him to assist with this analysis. From prior analyses, George Ben is well-versed in decision analysis terminology, and he is able to use decision analysis terms in his discussion with Analyst. Analyst: As I understand it, you can buy the one million kilograms of molyzirconium ore for \$5.00 a kilogram and sell it for \$8.00, which gives a profit of (\$8 00 – \$5 00) x 1 000 000 = \$3 000 000. However, there is some chance that you cannot obtain an import license, in which case you will have to pay \$1.00 per kilogram to annul the purchase contract. In that case, you will not have to actually take the molyzirconium and pay Meldavia for it, but you will lose \$100 x 1 000 000 = \$1 000 000 due to the cost of annulling the contract.

Ben: Actually, some chance may be an understatement. The internal politics of Meldavia make it hard for their government to agree to stop selling their manufactured goods at very low prices here in the United States. The chances are only fifty-fifty that I will be able to obtain the import license. As you know, Ben Traders is not a very large company. The \$1,000,000 loss would be serious, although certainly not fatal. On the other hand, making \$3,000,000 would help the balance sheet.

Which alternative should Ben select?

Suppose a source of perfect information existed that would let Ben know if the import license would be issued.

How much money would it be worth to obtain perfect information about issuance of the import license?