A hybrid importance sampling algorithm for value-at-risk

Tian Shyr Dai*, Shih Kuei Lin, Li Min Liu

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

Value-at-Risk (VaR) provides a number that measures the risk of a financial portfolio under significant loss. Glasserman et al. suggest that the performance of Mote Calo simulation can be improved by importance sampling [3]. However, their technique might perform poorly for some complex portfolios like shorting straddle options. In this paper, we investigate the hybrid importance sampling algorithm which can efficiently estimate the VaR for complex portfolios.

原文English
主出版物標題Second International Conference on Innovative Computing, Information and Control, ICICIC 2007
發行者IEEE Computer Society
ISBN(列印)0769528821, 9780769528823
DOIs
出版狀態Published - 1 1月 2007
事件2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 - Kumamoto, 日本
持續時間: 5 9月 20077 9月 2007

出版系列

名字Second International Conference on Innovative Computing, Information and Control, ICICIC 2007

Conference

Conference2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007
國家/地區日本
城市Kumamoto
期間5/09/077/09/07

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