Financial Risk Manager Part 1

Explanation

Monte Carlo simulations have several disadvantages in financial applications:

1. Computational expense (Option A): Monte Carlo simulations require generating many random samples to achieve accurate results, which can be computationally intensive and time-consuming.

2. Potential lack of precision (Option B): The results depend on the quality of the random number generator and the number of simulations run. With insufficient simulations, results may not be precise.

3. Difficulty in replication (Option C is NOT a disadvantage): The statement says "The results are often easy to replicate" - this is actually NOT true and therefore NOT a disadvantage. In reality, Monte Carlo results are often hard to replicate because they depend on random number generation and specific simulation parameters.

4. Experiment-specific results (Option D): Simulation results are specific to the particular experiment setup, including the random seed, number of simulations, and model assumptions.

Option C is the correct answer because it states the opposite of what is true - Monte Carlo simulation results are typically not easy to replicate exactly due to their reliance on random number generation. The ability to easily replicate results would actually be an advantage, not a disadvantage.