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Which of the following statements is correct regarding the use of antithetic variates during a Monte Carlo simulation exercise?
A
The antithetic variates reduce the sampling error through the correlation coefficient.
B
The antithetic variates method involves taking one over each random draw and then repeating the experiment using those values as the draws.
C
The antithetic variates method reduces the variance of the simulation results.
D
All the above
Explanation:
The correct answer is D) All the above.
Explanation:
Option A is correct: Antithetic variates reduce sampling error by introducing negative correlation between pairs of simulation runs. This correlation helps to reduce the variance of the estimator.
Option B is correct: The antithetic variates method indeed involves taking the complement (or negative) of each random draw (e.g., if u is a uniform random variable, using 1-u as the antithetic variate) and then repeating the simulation with these antithetic values.
Option C is correct: The primary purpose of antithetic variates is to reduce the variance of simulation results, which in turn reduces the standard error and improves the efficiency of Monte Carlo simulations.
How antithetic variates work:
This technique is particularly useful in Monte Carlo simulations for option pricing, risk measurement, and other financial applications where variance reduction is important for computational efficiency.