Section: New Results

Financial risk analysis

Participant : Jacques Lévy Véhel.

Financial regulations have fundamentally changed since the Basel II Accords. Among other evolutions, Basel II and III explicitly impose that computations of capital requirements be model-based. This paradigm shift in risk management has been the source of strong debates among both practitioners and academics, who question whether such model-based regulations are indeed more efficient.

A common feeling in the industry is that regulations will sometimes give a false impression of security: risk manager tend to think that a financial company that would fulfil all the criteria of, say, the Basel III Accords on capital adequacy, is not necessarily on the safe side. This is so mainly because many risks, and most significantly systemic or system-wide risks, are not properly modelled, and also because it is easy to manipulate to some extent various risk measures, such as VaR.

In parallel, a fast growing body of academic research provides various arguments explaining why current regulations are not well fitted to address risk management in an adequate way, and may even, in certain cases, worsen the situation.

We use the term regulation risk to describe the fact that, in some situations, prudential rules are themselves the source of a systemic risk. We have shown how a combination of model risk and regulation risk leads to an effect which is exactly the opposite of what the regulator tries to enforce. More precisely, we explain how wrongly assuming a Gaussian dynamics (or, more generally, a left-light-tailed one) when the “true” one is pure jump (or, more generally, left-heavy-tailed), and imposing as a constraint minimizing VaR at constant volume results in effect in movements that will maximize VaR. This effect is related to the fact that regulations fail to consider that risk is endogenous. In a nutshell, the idea is simply that, by treating jumps in the evolution of prices as exceptional events and essentially ignoring them in model-based VaR computations, one misses an essential dimension of risk, and acts in a way that will in effect favour sudden large movements in the markets and ultimately increase VaR. Our simple setting predicts that VaR constraints result in an increased intensity of jumps and a decrease in volatility - a fact confirmed experimentally on certain datasets. This is a mathematical translation of the common feeling of practitioners that regulations give a false impression of security characterized by low volatility but increased risk of sudden large movements.