English  |  正體中文  |  简体中文  |  Items with full text/Total items : 49287/83828 (59%)
Visitors : 7149881      Online Users : 46
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/88839


    Title: Efficient Importance Sampling for Rare Event Simulation with Applications
    Authors: Fuh, Cheng-der;Teng, Huei-Wen;Wang, Ren-Her
    Contributors: 淡江大學財務金融學系
    Keywords: Bootstrap;Confidence region;Exponential tilting;Local asymptotic normal;Moderate deviation;Value at Risk
    Date: 2011-12
    Issue Date: 2013-04-29 20:23:51 (UTC+8)
    Abstract: 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.
    Relation: International Workshop on Statistical Computing in Quantitative Finance and Biostatistics: A Satellite Meeting for the 7th IASC-ARS Conference
    Appears in Collections:[財務金融學系暨研究所] 會議論文

    Files in This Item:

    File Description SizeFormat
    議程.pdf262KbAdobe PDF42View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback