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Answer: Unlike Monte Carlo simulation, bootstrapping does not require the specification of a model to estimate the confidence interval.
**Explanation:** **Key differences between Monte Carlo and Bootstrapping:** - **Option A is incorrect**: Bootstrapping is non-parametric and doesn't assume any specific distribution. It resamples from the actual data, preserving the empirical distribution. - **Option B is incorrect**: Bootstrapping doesn't require distributional assumptions, so incorrect assumptions about the underlying distribution don't affect its results. - **Option C is correct**: This is a key advantage of bootstrapping. It's a non-parametric method that resamples from the observed data without requiring a model specification for the data-generating process. - **Option D is incorrect**: Bootstrapping doesn't necessarily increase accuracy compared to Monte Carlo. Both methods have their strengths depending on the context. Bootstrapping is particularly useful when the underlying distribution is unknown or complex. **Bootstrapping advantages:** - Model-free approach - Preserves the empirical distribution of data - Particularly useful for small sample sizes - No distributional assumptions required
Author: LeetQuiz Editorial Team
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A risk manager at an investment management firm is using historical data to estimate the variation in returns of a group of assets over time. The manager is considering switching from the Monte Carlo simulation method, which the firm currently uses, to the bootstrapping method to estimate confidence intervals for asset returns. Which of the following statements will the manager find to be correct regarding bootstrapping?
A
Similar to Monte Carlo simulation, bootstrapping requires a normal distribution of returns to generate an accurate estimate of the confidence interval.
B
Similar to Monte Carlo simulation, an incorrect assumption about the distribution of returns when using bootstrapping will produce an inaccurate confidence interval.
C
Unlike Monte Carlo simulation, bootstrapping does not require the specification of a model to estimate the confidence interval.
D
Unlike Monte Carlo simulation, bootstrapping can increase the accuracy of the estimated confidence interval.
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