Advances and Applications in Statistics
Volume 31, Issue 1, Pages 43 - 54
(November 2012)
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THE DATA-BASED CHOICE OF BANDWIDTH FOR KERNEL QUANTILE ESTIMATOR OF VaR
Xin Yang
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Abstract: Value-at-Risk is an important risk measure, has been wildly applied in market practice and financial risk measurement. We use the smooth kernel estimator for the quantile proposed by Parzen [13] as a VaR estimator and propose a data-based choice method of optimal bandwidth via normal reference distribution, which is easy to compute. The simulations show that the choice method of bandwidth is effective, and the smooth kernel estimator has better performance than the sample quantile estimator. |
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