Assessing asset-liability risk with neural networks

Patrick Cheridito, John Ery and Mario V. W\"uthrich

Papers from arXiv.org

Abstract: We introduce a neural network approach for assessing the risk of a portfolio of assets and liabilities over a given time period. This requires a conditional valuation of the portfolio given the state of the world at a later time, a problem that is particularly challenging if the portfolio contains structured products or complex insurance contracts which do not admit closed form valuation formulas. We illustrate the method on different examples from banking and insurance. We focus on value-at-risk and expected shortfall, but the approach also works for other risk measures.

Date: 2021-05
New Economics Papers: this item is included in nep-cmp, nep-ias and nep-rmg
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Published in Risks 2020, 8, 16

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2105.12432

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