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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/72429

    Title: Efficient Simulation of Value at Risk with Heavy-Tailed Risk Factors
    Authors: Fuh, Cheng-Der;Hu, Inchi;Hsu, Ya-Hui;Wang, Ren-Her
    Contributors: 淡江大學財務金融學系
    Keywords: importance sampling;moderate deviation;multivariate t distribution;quadratic approximation;component VaR
    Date: 2011-11
    Issue Date: 2011-10-24 10:27:17 (UTC+8)
    Publisher: Hanover: Institute for Operations Research and the Management Sciences (I N F O R M S)
    Abstract: Simulation of small probabilities has important applications in many disciplines. The probabilities considered in value-at-risk (VaR) are moderately small. However, the variance reduction techniques developed in the literature for VaR computation are based on large-deviations methods, which are good for very small probabilities. Modeling heavy-tailed risk factors using multivariate t distributions, we develop a new method for VaR computation. We show that the proposed method minimizes the variance of the importance-sampling estimator exactly, whereas previous methods produce approximations to the exact solution. Thus, the proposed method consistently outperforms existing methods derived from large deviations theory under various settings. The results are confirmed by a simulation study.
    Relation: Operations Research 59(6), pp.1395-1406
    Appears in Collections:[財務金融學系暨研究所] 期刊論文

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