We introduce a new framework to compute, stress-test, and manage liquidity risk, funding risk and market risk in fully general multi-asset class portfolios, and we present a case study.
Our approach, which goes beyond the simple bid-ask spread overlay to a VaR number, relies on three pillars: first, the Fully Flexible Probabilities approach, to model and stress-test market risk even in highly non-normal markets with complex derivatives; second, the literature on optimal execution, to model liquidity risk as a function of the actual trading involved; third, an analytical conditional convolution, to model funding risk, whereby different trading decisions are made in different market scenarios.
Our approach can be implemented efficiently with portfolios of thousand of securities. As a side product of our approach we introduce a definition of
liquidity score, a monetary measure of portfolio liquidity based on the additional tail risk added by lack of liquidity.