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標題:Efficient Importance Sampling for Rare Event Simulation with Applications
學年100
學期1
發表日期2011/12/20
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 Workshop on Statistical Computing in Quantitative Finance and Biostatistics: A Satellite Meeting for the 7th IASC-ARS Conference
會議地點Taichung, Taiwan
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, we propose a simple general account for finding the optimal tilting measure. To this end, we first obtain an explicit expression of the optimal alternative distribution, and then propose a recursive approximation algorithm for the tilting measure. The proposed algorithm is quite general to cover many interesting examples and can also be applied to a locally asymptotically normal (LAN) family around the original distribution. 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;Local asymptotic normal;Moderate deviation;Value at Risk
語言英文
收錄於
會議性質國內
校內研討會地點
研討會時間20111220~20111221
通訊作者
國別中華民國
公開徵稿Y
出版型式
出處International Workshop on Statistical Computing in Quantitative Finance and Biostatistics: A Satellite Meeting for the 7th IASC-ARS Conference
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