Strategisches ALM

Spillmann, Martin; Döhnert, Karsten; Rissi, Roger

doi:10.1007/978-3-658-25202-1_7

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The Alm Optimization Problem1

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2023

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“…ALM involves many stakeholders that have detailed and potentially different preferences on the ALM policy and the resulting evolution of balance sheet positions. Even the fundamental goal of ALM is ambiguous because the bank must trade off profitability versus hedging; see Spillmann et al ( 2019 , Chapter 2). As profits are recognized in equity, we act as if preferences in the ALM problem could actually be reduced to characteristics of the bank's equity distribution at the horizon T .…”

Section: The Alm Optimization Problemmentioning

confidence: 99%

Deep treasury management for banks

Englisch¹,

Krabichler

Müller³

et al. 2023

Front. Artif. Intell.

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Retail banks use Asset Liability Management (ALM) to hedge interest rate risk associated with differences in maturity and predictability of their loan and deposit portfolios. The opposing goals of profiting from maturity transformation and hedging interest rate risk while adhering to numerous regulatory constraints make ALM a challenging problem. We formulate ALM as a high-dimensional stochastic control problem in which monthly investment and financing decisions drive the evolution of the bank's balance sheet. To find strategies that maximize long-term utility in the presence of constraints and stochastic interest rates, we train neural networks that parametrize the decision process. Our experiments provide practical insights and demonstrate that the approach of Deep ALM deduces dynamic strategies that outperform static benchmarks.

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Section: The Alm Optimization Problemmentioning

confidence: 99%