Monte Carlo Simulation and Sensitivity Analysis
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A decision maker is working on a problem that requires her to study the uncertainty surrounding the payoff of an investment. There are three possible levels of payoff -$1,000, $5,000, and $10,000. As a rough approximation, the decision maker believes that each possible payoff is equally likely. But she is not fully comfortable with the assessment that each probability is exactly 1/3, and so would like to conduct a sensitivity analysis. In fact, she believes that each probability could range from 0 to ½.
1. Show how a Monte Carlo simulation could facilitate a sensitivity analysis of the probabilities of the payoff
2. Suppose the decision maker is willing to say that each of the three probabilities could be chosen from a uniform distribution between 0 and 1. Could you incorporate this information into your simulation? If so, how? If not, explain why not, or what additional information you would need
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Solution Summary
Monte Carlo method used for taking some decision, using given data.
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1. For equally likely condition, expected pay-off, E(X) = (-1000+5000+10000)/3 = $4,666.67
An experiment carried out for sensitivity analysis: all three probability values varied randomly between 0 and 1/2 (Montecarlo simulation). Such 100 values generated randomly, their mean values with 95% confidence interval obtained as follows:
mean probability x1 = 0.239 +/- 1.96*0.156/sqrt(100) = [0.209, 0.270]
mean probability ...
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- BEng, Allahabad University, India
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