The Centre for the Analysis of Risk and Optimisation Modelling Applications (CARISMA), Brunel University
Abstract
We introduce a modelling paradigm which integrates credit risk and market
risk in describing the random dynamical behaviour of the underlying fixed income assets.
We then consider an asset and liability management (ALM) problem and develop a mul-
tistage stochastic programming model which focuses on optimum risk decisions. These
models exploit the dynamical multiperiod structure of credit risk and provide insight
into the corrective recourse decisions whereby issues such as the timing risk of default is
appropriately taken into consideration. We also present a index tracking model in which
risk is measured (and optimised) by the CVaR of the tracking portfolio in relation to the
index. Both in- and out-of-sample (backtesting) experiments are undertaken to validate
our approach. In this way we are able to demonstrate the feasibility and flexibility of
the chosen framework