On Bayesian Value-at-Risk: from linear to non-linear portfolios

Tak Kuen Siu*, Howell Tong, Hailiang Yang

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

7 Citations (Scopus)


This paper proposes the use of Bayesian approach to implement Value at Risk (VaR) model for both linear and non-linear portfolios. The Bayesian approach provides risk traders with the flexibility of adjusting their VaR models according to their subjective views. First, we deal with the case of linear portfolios. By imposing the conjugate-prior assumptions, a closed-form expression for the Bayesian VaR is obtained. The Bayesian VaR model can also be adjusted in order to deal with the ageing effect of the past data. By adopting Gerber-Shiu's option-pricing model, our Bayesian VaR model can also be applied to deal with non-linear portfolios of derivatives. We obtain an exact formula for the Bayesian VaR in the case of a single European call option. We adopt the method of back-testing to compare the non-adjusted and adjusted Bayesian VaR models with their corresponding classica' counterparts in both linear and non-linear cases.

Original languageEnglish
Pages (from-to)161-184
Number of pages24
JournalAsia-Pacific Financial Markets
Issue number2
Publication statusPublished - 2004
Externally publishedYes


  • Bayesian method
  • Gerber-Shiu's model
  • Leptokurtic effect
  • Model risk
  • Non-linear portfolios
  • Subjective VaR


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