In this paper we apply two optimization frameworks to determine the optimal wholesale funding mix of a bank given uncertainty in both credit and liquidity risk. A stochastic linear programming method is used to find the optimal strategy to be maintained across all scenarios. A recursive learning method is developed to provide the bank with a trading signal to dynamically adjust the wholesale funding mix as the macroeconomic environment changes. The performance of the two methodologies is compared in the final section. | Funding optimization for a bank integrating credit and liquidity risk
