Ensemble learning for portfolio valuation and risk management

Lotfi Boudabsa and Damir Filipović
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Lotfi Boudabsa: Ecole Polytechnique Fédérale de Lausanne - School of Basic Sciences
Damir Filipović: Ecole Polytechnique Fédérale de Lausanne; Swiss Finance Institute

No 22-30, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We introduce an ensemble learning method for dynamic portfolio valuation and risk management building on regression trees. We learn the dynamic value process of a derivative portfolio from a finite sample of its cumulative cash flow. The estimator is given in closed form. The method is fast and accurate, and scales well with sample size and path space dimension. The method can also be applied to Bermudan style options. Numerical experiments show good results in moderate dimension problems.

Keywords: dynamic portfolio valuation; ensemble learning; gradient boosting; random forest; regression trees; risk management; Bermudan options (search for similar items in EconPapers)
Pages: 34 pages
Date: 2022-04
New Economics Papers: this item is included in nep-cmp, nep-ecm, nep-ore and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2230

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