Bank strategic asset allocation under a unified risk measure

Abstract

Most available bank asset allocation models use several risk measures as constraints; as a consequence, the comparison of the risk between different asset allocation strategies is often difficult, since each strategy is subject to several risks. With this research, we create a simulation–optimization methodology that measures interest rate, credit and liquidity risks in a unified manner. The associated risk events, such as interest rate increases, liquidity outflows or spikes in defaults are generated using the same simulation engine, giving as output a single risk measure (the probability of failure, used by ratings agencies) that aggregates those risks under the same simulation engine. Finally, we use our methodology to determine Pareto fronts for the optimal balance sheet allocations and minimum-risk strategies. As a result, several findings emerge, such as: 1) Risk is dependent on the income stream; 2) Allocation to book value assets is preferable; 3) Under low rate environments, a full allocation to cash is very risky and is not the minimum risk strategy; 4) Banks can make investments in stocks in environments of high prospective returns and low leverage.