Value at Risk Computation in a Non-Stationary Setting
This chapter recalls the main tools useful to compute Value at Risk associated with a m-dimensional portfolio. Then, the limitations of the use of these tools is explained, as soon as non-stationarities are observed in time series. Indeed, specific behaviours observed by financial assets, like volatility, jumps, explosions, and pseudo-seasonalities, provoke non-stationarities which affect the distribution function of the portfolio. Thus, a new way for computing VaR is proposed which allows the potential non-invariance of the m-dimensional portfolio distribution function to be avoided.
|Date of creation:||2010|
|Date of revision:|
|Publication status:||Published, Handbook on Model Risk : Measuring, managing and mitigating model risk, lessons from financial crisis, John Wiley (Ed.), 2010, 431-454 - chapter 19|
|Note:||View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00511995|
|Contact details of provider:|| Web page: http://hal.archives-ouvertes.fr/|
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- Dominique Guegan & Pierre-André Maugis, 2010.
"New Prospects on Vines,"
Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers)
- Dominique Guegan & Pierre-André Maugis, 2008. "New prospects on vines," Documents de travail du Centre d'Economie de la Sorbonne b08095, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Mar 2010.
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