Financial Regulation: More Accurate Measurements for Control Enhancements and the Capture of the Intrinsic Uncertainty of the VaR

Dominique Guegan (1, 2, 3, 4)

1 UP1 - Université Paris 1 Panthéon-Sorbonne
2 CES - Centre d'économie de la Sorbonne
3 Labex ReFi
4 University of Ca’ Foscari [Venice, Italy]

During the crisis, the failure of models and the lack of capture of extreme exposures led the regulator to change the way risks were analysed either by requiring financial institution to use sub-exponential probability distribution (), either to change the way correlations were captured () or to suggest switching from the VaR to sub-additive risk measures (). Indeed, models have had played a major role during this crisis either as catalysts or triggers. Before capturing dependencies, the technical point is the choice of the probability distribution and its use to provide a risk measure which is the key point for Bankers and regulators. It is now well known and admitted by practitioners that the important information for risk management is inside the tails of the distributions which characterize the risk factors. The purpose of this paper is to discuss the issue of considering the distributions used to characterise the risks and the associated risk measures independently, as we will argue that distributions and risk measures are indivisible.

Mots clés: Regulation; Financial markets; Distribution; Risk measures

Domaines: Economies et finances

Dominique Guegan. Financial Regulation: More Accurate Measurements for Control Enhancements and the Capture of the Intrinsic Uncertainty of the VaR. vsbf: 2016 Vietnam Symposium in Banking and Finance, Nov 2016, Hanoi, Vietnam. ⟨halshs-01906496⟩