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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/72550


    Title: An Importance Sampling Method to Evaluate Value-at-Risk for Assets with Jump Risks
    Authors: 王仁和;Lin, S. K.;Fuh, C. D.
    Contributors: 淡江大學財務金融學系
    Keywords: Jump Diffusion Models;Value-at-Risk;Quick Simulation;Importance Sampling;Risk Management
    Date: 2009-09
    Issue Date: 2011-10-24 10:33:08 (UTC+8)
    Abstract: Risk management is an important issue when there is a catastrophic event that affects asset price in the market such as a sub-prime financial crisis or other financial crisis. By adding a jump term in the geometric Brownian motion, the jump diffusion model can be used to describe abnormal changes in asset prices when there is a serious event in the market. In this paper, we propose an importance sampling algorithm to compute the Value-at-Risk for linear and nonlinear assets under a multi-variate jump diffusion model. To be more precise, an efficient computational procedure is developed for estimating the portfolio loss probability for linear and nonlinear assets with jump risks. And the titling measure can be separated for the diffusion and the jump part under the assumption of independence. The simulation results show that the efficiency of importance sampling improves over the naive Monte Carlo simulation from 7 times to 285 times under various situations. We also show the robustness of the importance sampling algorithm by comparing it with the EVT-Copula method proposed by Oh and Moon (2006).
    Relation: Asia-Pacific Journal of Financial Studies 38, pp.745-772
    DOI: 10.1111/j.2041-6156.2009.tb00029.x
    Appears in Collections:[財務金融學系暨研究所] 期刊論文

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