Efficient Importance Sampling for Rare Event Simulation with Applications
學年 101
學期 2
發表日期 2013-07-07
作品名稱 Efficient Importance Sampling for Rare Event Simulation with Applications
作品名稱（其他語言）
著者 Fuh, Cheng-der; Teng, Huei-Wen; Wang, Ren-Her
作品所屬單位 淡江大學財務金融學系
出版者
會議名稱 International conference on Business and information (BAI 2013)
會議地點 Bali, INDONESIA
摘要 Importance sampling has been known as a powerful tool to reduce the variance of Monte Carlo estimator for rare event simulation. Based on the criterion of minimizing the variance of Monte Carlo estimator within a parametric family, we propose a general account for finding the optimal tilting measure. To this end, when the moment generating function of the underlying distribution exists, we obtain a simple and explicit expression of the optimal alternative distribution. The proposed algorithm is quite general to cover many interesting examples, such as normal distribution, noncentral distribution, and compound Poisson processes. To illustrate the broad applicability of our method, we study value-at-risk (VaR) computation in financial risk management and bootstrap confidence regions in statistical inferences
關鍵字 Bootstrap;confidence region;exponential tilting;moderate deviation;VaR
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 20130707~20130709
通訊作者
國別 IDN
公開徵稿 Y
出版型式
出處 International conference on Business and information (BAI 2013)
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/90563 )

機構典藏連結