The Shapley decomposition for portfolio risk

Mussard, Stéphane; Terraza, Virginie

doi:10.1080/13504850600748968

Cited by 20 publications

(9 citation statements)

References 4 publications

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“…This is because the process of portfolio formation can be interpreted as a cooperative game where the assets are the players that form coalitions to reduce risk (see Kadan, ; Colini‐Baldeschi et al, ). Consequently, the corresponding Shapley values of the assets reflect their contribution to the overall portfolio risk (see Mussard and Terraza, ) . They consider all possible asset coalitions and by averaging their marginal effects obtain a multidimensional contribution.…”

Section: Introductionmentioning

confidence: 99%

Can cooperative game theory solve the low‐risk puzzle?

Auer

Hiller

2018

Int. J Fin Econ

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In this article, we illustrate that cooperative game theory may have the potential to solve the low‐risk puzzle, which has become one of the most important in modern finance because its implication of a negative risk‐return trade‐off poses a challenge to traditional models of asset prices. Using several simulation settings, we highlight that quantifying risk by means of assets' Shapley values, that is, assets' contributions to overall portfolio risk, instead of classic measures supplies a (more) positive risk‐return relationship in many practically relevant cases. This is partially attributable to the fact that the game‐theoretic risk measure captures more investment‐relevant information than commonly used alternatives.

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Section: Introductionmentioning

confidence: 99%

Can cooperative game theory solve the low‐risk puzzle?

Auer

Hiller

2018

Int. J Fin Econ

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“…A non-exhaustive list of recent applications include Israeli[9], Mussard and Terraza[14], and Sastre and Trannoy[16].…”

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confidence: 99%

Shapley-value decompositions of changes in wage distributions: a note

Devicienti

2008

J Econ Inequal

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“…Some authors have suggested that the use of SHAP values is the only explainable AI approach that has been established in an economic field (Bussmann et al, 2021 ). Shapley-based XAI models have been used in many research studies in the field of finance (Mussard and Terraza, 2008 ; Ariza-Garzón et al, 2020 ; Bussmann et al, 2020 ; Giudici and Raffinetti, 2020 ).…”

Section: Artificial Intelligencementioning

confidence: 99%

Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence

Černevičienė

Kabašinskas

2022

Front. Artif. Intell.

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The influence of Artificial Intelligence is growing, as is the need to make it as explainable as possible. Explainability is one of the main obstacles that AI faces today on the way to more practical implementation. In practise, companies need to use models that balance interpretability and accuracy to make more effective decisions, especially in the field of finance. The main advantages of the multi-criteria decision-making principle (MCDM) in financial decision-making are the ability to structure complex evaluation tasks that allow for well-founded financial decisions, the application of quantitative and qualitative criteria in the analysis process, the possibility of transparency of evaluation and the introduction of improved, universal and practical academic methods to the financial decision-making process. This article presents a review and classification of multi-criteria decision-making methods that help to achieve the goal of forthcoming research: to create artificial intelligence-based methods that are explainable, transparent, and interpretable for most investment decision-makers.

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The Shapley decomposition for portfolio risk

Abstract: The aim of this article is to provide an application of the Shapley value to decompose financial portfolio risk. Decomposing the sample covariance risk measure, gives us relative measures, which can be, classified securities of a portfolio according to risk scales.

Cited by 20 publications

References 4 publications

Can cooperative game theory solve the low‐risk puzzle?

Can cooperative game theory solve the low‐risk puzzle?

Shapley-value decompositions of changes in wage distributions: a note

Review of Multi-Criteria Decision-Making Methods in Finance Using Explainable Artificial Intelligence

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