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Too dispersed to monitor? Ownership dispersion, monitoring and the prediction of bank distress

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  • Tristan Auvray

    () (LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux - UT1 - Université Toulouse 1 Capitole - UT2 - Université Toulouse 2 - Institut d'Études Politiques [IEP] - Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville)

  • Olivier Brossard

    () (LEREPS - Laboratoire d'Etude et de Recherche sur l'Economie, les Politiques et les Systèmes Sociaux - UT1 - Université Toulouse 1 Capitole - UT2 - Université Toulouse 2 - Institut d'Études Politiques [IEP] - Toulouse - ENSFEA - École Nationale Supérieure de Formation de l'Enseignement Agricole de Toulouse-Auzeville)

Abstract

This paper conducts an empirical assessment of the theories stating that ownership concentration improves the quality of shareholders' monitoring. In contrast with other studies, we do not use regressions of risk/performance on ownership concentration. Instead, we build an early warning model of bank distress that includes a leading indicator derived from banks' share price, the Merton-KMV distance to default (DD). The significance of this indicator depends on the efficacy of shareholders' monitoring. On a sample of European banks, we show that the predictive power of the DD is satisfactory only when banks' shareholding is characterized by the presence of blockholders.

Suggested Citation

  • Tristan Auvray & Olivier Brossard, 2010. "Too dispersed to monitor? Ownership dispersion, monitoring and the prediction of bank distress," Working Papers hal-00638913, HAL.
  • Handle: RePEc:hal:wpaper:hal-00638913
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-00638913
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    References listed on IDEAS

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    Cited by:

    1. Olivier Brossard & Stéphanie Lavigne & Mustafa Erdem Sakinç, 2013. "Ownership structures and R&D in Europe: the good institutional investors, the bad and ugly impatient shareholders," Industrial and Corporate Change, Oxford University Press, vol. 22(4), pages 1031-1068, August.
    2. Allen, D.E. & Powell, R.J. & Singh, A.K., 2016. "Take it to the limit: Innovative CVaR applications to extreme credit risk measurement," European Journal of Operational Research, Elsevier, vol. 249(2), pages 465-475.

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