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.