Efficient Simulation of Value-at-Risk Under a Jump Diffusion Model: A New Method for Moderate Deviation Events
學年 106
學期 2
出版（發表）日期 2018-03-13
作品名稱 Efficient Simulation of Value-at-Risk Under a Jump Diffusion Model: A New Method for Moderate Deviation Events
作品名稱（其他語言）
著者 Cheng-Der Fuh; Huei-Wen Teng; Ren-Her Wang
單位
出版者
著錄名稱、卷期、頁數 Computational Economics 51(4), p.973-990
摘要 Importance sampling is a powerful variance reduction technique for rare event simulation, and can be applied to evaluate a portfolio’s Value-at-Risk (VaR). 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 portfolio’s VaR under a multi-variate jump diffusion model. To be more precise, an efficient computational procedure is developed for estimating the portfolio loss probability for those assets with jump risks. And the tilting 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 9 to 277 times under various situations.
關鍵字 Importance sampling;Exponential tilting;Moderate deviation;Jump diffusion;VaR
語言 en_US
ISSN 1572-9974
期刊性質 國外
收錄於 SCI SSCI
產學合作
通訊作者 Ren-Her Wang
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/110431 )