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Which of the following cases leads to the smallest underestimation of the actual value at risk (VAR) when estimating this measure based on a simulated random Weibull distribution? A. The investigator knows that the data is Weibull-distributed and a true VAR is calculated using true parameters. B. The investigator knows that the true return distribution is Weibull-distributed; however, he uses a normal quantile function as a best alternative to estimate VAR. C. The investigator knows that the return distribution is Weibull-distributed and depends on simulation methods to estimate Weibull parameters to compute the estimated VAR using a large sample of observations. D. The investigator assumes a normal returns distribution using estimates from a sample moment and does not know or ignores that the true data is Weibull-distributed. |