A1573
Title: Joint-VaR: A new risk measure for financial markets
Authors: Leopoldo Catania - Aarhus BBS (Denmark)
Alessandra Luati - Imperial College London (United Kingdom)
Elisabetta Mensali - University of Bologna (Italy) [presenting]
Abstract: The Joint Value at Risk (JVaR) is defined as the quantile of the conditional distribution of an asset return, given an upper tail event affecting its log-volatility. The purpose of JVaR is to measure financial risk under a volatility stress scenario. A distinguishing feature of the proposed risk measure is that conditioning events are unobserved. The relations with the VaR and the CoVaR, that is the VaR conditional to some event, are made explicit. The properties of JVaR are studied based on a stochastic volatility representation of the underlying process. We prove that JVaR is leverage consistent, i.e. it is an increasing function of the dependence parameter in the stochastic representation. The difference between the JVaR and its reference state, represented by the VaR, provides a natural tool for monitoring risk under volatility distress. An empirical illustration with S&P500 data shows that, during financial crises, accounting for extreme volatility levels is relevant to monitor the evolution of risk.
