BNP Paribas

A wide variety of solutions have been proposed in order to cope with the deficiencies of Modern Portfolio Theory. The ideal portfolio should optimise the investor’s expected utility. Robustness can be achieved by ensuring that the optimal portfolio does not diverge too much from a predetermined allocation. Information geometry proposes interesting and relatively simple ways to model divergence. These techniques can be applied to the risk budgeting framework in order to extend risk budgeting and to unify various classical approaches in a single, parametric framework. By switching from entropy to divergence functions, the entropy-based techniques that are useful for risk budgeting can be applied to more traditional, constrained portfolio allocation. Using these divergence functions opens new opportunities for portfolio risk managers. This presentation is based on two papers published by the BNP Paribas QIS Lab, `The properties of alpha risk parity’ (2022, Entropy) and `Turning tail risks into tailwinds’ (2020, The Journal of Portfolio Management).

Since summer 2007 financial markets moved in unprecedented ways. Volatility was extremely high. Correlations across the board increased dramatically. More importantly, also much deeper fundamental changes took place. In this talk we will concentrate on the following two aspects, namely, inter-bank unsecured lending at LIBOR and 40% recovery.

Before the crisis it was very realistic for the banks to consider that risk free rate of inter-bank lending, and hence also of funding, is equivalent to 3M LIBOR. This logic was extended to terms which are multiples of 3M via compounding and to arbitrary periods by interpolation and extrapolation. Driven by advances in financial mathematics arbitrage free term structure models have been developed for pricing of interest rate exotics, like LIBOR Market Model (or BGM). We explain how this methodology was challenged in the current market environment. We also point to mathematical questions that need to be addressed in order to incorporate in the pre-crisis pricing and risk management methodology the current market reality.

We also discuss historically validated and universally accepted pre-crisis assumption of 40% recovery. We expose its inconsistency with the prices observed now in the structured credit markets. We propose ways of addressing the problem and point to mathematical questions that need to be resolved.