Comptes Rendus
no. 4
From statistical physics to social sciences / De la physique statistique aux sciences sociales
Lost in diversification
[Diversification infidèle]
Marco Bardoscia1  ; Daniele d'Arienzo2  ; Matteo Marsili3, 4  ; Valerio Volpati5
1 Bank of England, Threadneedle St., London EC2R 8AH, UK
2 Bocconi University, Department of Finance, Via Roentgen 1, 20136 Milan, Italy
3 The Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34151 Trieste, Italy
4 Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Trieste, Italy
5 Capital Fund Management, 23, rue de l'Université, 75007 Paris, France
Comptes Rendus. Physique, Volume 20 (2019) no. 4, pp. 364-370.

À mesure que la complexité des instruments financiers augmente, de plus en plus d'informations sont négligées par les méthodes d'optimisation des risques. Cela obscurcit l'origine du risque, ce qui a été l'une des causes principales de la crise financière mondiale de 2007–2008. Nous discutons la manière dont la perte de transparence peut être quantifiée en bits, à l'aide de concepts de théorie de l'information. Nous constatons i) que les transformations financières impliquent d'importantes pertes d'information, ii) que les portefeuilles sont plus sensibles que les stocks à l'information tant que si l'analyse fondamentale est suffisamment informative quant aux mouvements conjoints des actifs, iii) que la titrisation, dans la gamme pertinente de paramètres, produit des actifs moins sensibles à l'information que ceux initiaux, iv) que, lorsque la diversification (ou titrisation) est à son meilleur (c'est-à-dire lorsque les actifs sont non corrélés), les pertes d'information sont maximales. Nous abordons également la question de savoir si des systèmes de valorisation peuvent être mis en place pour faire face aux pertes d'information. Ceci est pertinent pour inciter les initiateurs à collecter des informations sur l'origine du risque. Dans le cadre simple d'une approximation moyenne–variance, nous constatons que les incitations de marché ne sont généralement pas suffisantes pour rendre la collecte d'information durable.

As financial instruments grow in complexity, more and more information is neglected by risk optimization practices. This brings down a curtain of opacity on the origination of risk, which has been one of the main culprits in the 2007–2008 global financial crisis. We discuss how the loss of transparency may be quantified in bits, using information theoretic concepts. We find i) that financial transformations imply large information losses, ii) that portfolios are more information sensitive than individual stocks only if fundamental analysis is sufficiently informative on the co-movement of assets, iii) that securitisation, in the relevant range of parameters, yields assets that are less information sensitive than the original stocks, and iv) that, when diversification (or securitisation) is at its best (i.e. when assets are uncorrelated), information losses are maximal. We also address the issue of whether pricing schemes can be introduced to deal with information losses. This is relevant for the transmission of incentives to gather information on the risk origination side. Within a simple mean variance scheme, we find that market incentives are not generally sufficient to make information harvesting sustainable.

Publié le :
DOI : 10.1016/j.crhy.2019.05.015
Keywords: Securitization, Asset-backed securities, Structured finance, Information theory
Mot clés : Titrisation, Titres adossés à des actifs, Finance structurée, Théorie de l'information
Marco Bardoscia 1 ; Daniele d'Arienzo 2 ; Matteo Marsili 3, 4 ; Valerio Volpati 5

1 Bank of England, Threadneedle St., London EC2R 8AH, UK
2 Bocconi University, Department of Finance, Via Roentgen 1, 20136 Milan, Italy
3 The Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34151 Trieste, Italy
4 Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Trieste, Italy
5 Capital Fund Management, 23, rue de l'Université, 75007 Paris, France 
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Marco Bardoscia; Daniele d'Arienzo; Matteo Marsili; Valerio Volpati. Lost in diversification. Comptes Rendus. Physique, Volume 20 (2019) no. 4, pp. 364-370. doi : 10.1016/j.crhy.2019.05.015. https://comptes-rendus.academie-sciences.fr/physique/articles/10.1016/j.crhy.2019.05.015/

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