Bayesian risk measures for derivatives via random Esscher transform

Tak Kuen Siu*, Howell Tong, Hailiang Yang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


This paper proposes a model for measuring risks for derivatives that is easy to implement and satisfies a set of four coherent properties introduced in Artzner et al. (1999). We construct our model within the context of Gerber-Shiu’s option-pricing framework. A new concept, namely Bayesian Esscher scenarios, which extends the concept of generalized scenarios, is introduced via a random Esscher transform. Our risk measure involves the use of the risk-neutral Bayesian Esscher scenario for pricing and a family of real-world Bayesian Esscher scenarios for risk measurement. Closed-form expressions for our risk measure can be obtained in some special cases.

Original languageEnglish
Pages (from-to)78-91
Number of pages14
JournalNorth American Actuarial Journal
Issue number3
Publication statusPublished - 1 Jul 2001
Externally publishedYes


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