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Answer: Can easily examine effects on output variables when changing scenarios
The correct answer is C because Monte Carlo simulations allow for easy examination of effects on output variables when changing scenarios or strategies. This is one of the key advantages of Monte Carlo simulations - they can handle complex functions and correlations between inputs without requiring identification of the probability distribution of the output variable. Options A, B, and D are incorrect because: - A: Monte Carlo simulations CAN measure and incorporate correlations between investments - B: Monte Carlo simulations do NOT require accurate determination of the output's probability distribution - D: Monte Carlo simulations do NOT require assuming the output is normally distributed
Author: Nikitesh Somanthe
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John Neur, FRM, runs a Monte Carlo simulation to estimate the ending amount of capital in 25 years using monthly returns for three investments as the basis. Investments A and B are highly correlated while C has zero correlation with both A and B. In order to compute the output of the Monte Carlo simulation, John:
A
Cannot measure the correlations between the three investments
B
Must accurately determine the probability distribution of the output
C
Can easily examine effects on output variables when changing scenarios
D
Must assume that the output is normally distributed