Explanation

The correct answer is C because:

• Multivariate Student's-t-distribution can capture fat tails (excess kurtosis) and potentially skewness in financial return data, which are common characteristics observed in real-world financial markets.
• Multivariate normal distribution assumes symmetric, bell-shaped distributions with no excess kurtosis, which often fails to capture the extreme events and tail risk present in financial data.
• Option A is incorrect because Student's-t-distribution typically requires estimating additional parameters (degrees of freedom) compared to the normal distribution.
• Option B is incorrect because both simulations would generally require similar computational steps in the Monte Carlo process; the distribution choice doesn't significantly affect the number of simulation steps.

This makes Simulation 2 more realistic for modeling financial returns where extreme events occur more frequently than predicted by normal distributions.