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A risk analyst is tasked with assessing the market risk linked to a global equity portfolio, which has experienced significant volatility. To carry out this analysis, the analyst employs the bootstrap method, focusing on the independent and identically distributed (i.i.d.) bootstrap technique. They apply this method to the residuals that have been standardized from the model that fits the portfolio data. These standardized residuals, when subjected to bootstrapping, generate a range of possible future asset return trajectories. The final goal of this procedure is to use the simulated data to determine the portfolio's Value at Risk (VaR) for a one-month period. What insights will the analyst gain regarding the effectiveness and implications of using the i.i.d. bootstrap method in this context?
A
The VaR estimates will be reliable because they are based on random values generated from an assumed distribution that is not affected by external events or time.
B
The VaR estimates will be reliable because the lID bootstrap fully captures interdependencies in the observed asset return data
C
The VaR estimates will not be reliable because the lID bootstrap allows the possibility of future losses that are larger than those that have been realized in the past.
D
The VaR estimates will not be reliable because they are derived from the most current observations of the period that is characterized by higher volatility.