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標題: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
語言英文
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
國別印尼
公開徵稿Y
出版型式
出處International conference on Business and information (BAI 2013)
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