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Funding optimization for a bank integrating credit and liquidity risk

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  • Petrus Strydom

Abstract

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.Mathematics Subject Classification: C61, G21, C53Keywords: Bank Funding, Optimization, Credit Risk, Liquidity Risk

Suggested Citation

  • Petrus Strydom, 2017. "Funding optimization for a bank integrating credit and liquidity risk," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(2), pages 1-1.
    • Handle: RePEc:spt:apfiba:v:7:y:2017:i:2:f:7_2_1
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    References listed on IDEAS

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