Linear Programming - Investment and Debt : Maximizing Net Present Value ( NPV )
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I have to determine how much investment and debt to undertake during the next year. Each dollar invested reduces the NPV of my company by 10 cents, and each dollar of debt increases the NPV by 50 cents (due to deductibility of interest payments). I can invest at most $1 million during the coming year. Debt can be at most 40% of investment. I now have $800,000.00 in cash available. All investment must be paid for from current cash or borrowed money. Set up an Linear Programming (LP) whose solution will tell me how to maximize its NPV. Then graphically solve the LP.
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Solution Summary
NPV is maximized using linear programming (graphical method). The solution is detailed and well presented. The response received a rating of "5/5" from the student who originally posted the question.
Education
- BSc , Wuhan Univ. China
- MA, Shandong Univ.
Recent Feedback
- "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
- "excellent work"
- "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
- "Thank you"
- "Thank you very much for your valuable time and assistance!"
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