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Too Dispersed to Monitor? Ownership Dispersion, Monitoring, and the Prediction of Bank Distress

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  • TRISTAN AUVRAY
  • OLIVIER BROSSARD

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.
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  • Tristan Auvray & Olivier Brossard, 2012. "Too Dispersed to Monitor? Ownership Dispersion, Monitoring, and the Prediction of Bank Distress," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(4), pages 685-714, June.
    • Handle: RePEc:mcb:jmoncb:v:44:y:2012:i:4:p:685-714
    DOI: j.1538-4616.2012.00506.x
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    Cited by:

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    2. Aktas, Nihat & Petmezas, Dimitris & Servaes, Henri & Karampatsas, Nikolaos, 2021. "Credit ratings and acquisitions," Journal of Corporate Finance, Elsevier, vol. 69(C).
    3. Dowling, Michael & O’Gorman, Colm & Puncheva, Petya & Vanwalleghem, Dieter, 2019. "Trust and SME attitudes towards equity financing across Europe," Journal of World Business, Elsevier, vol. 54(6), pages 1-1.
    4. Michael Dowling & Colm O’gorman & Petya Puncheva-Michelotti & Dieter Vanwalleghem, 2019. "Trust and SME attitudes towards equity financing across Europe," Post-Print hal-02194484, HAL.
    5. Ballester, Laura & González-Urteaga, Ana & Martínez, Beatriz, 2020. "The role of internal corporate governance mechanisms on default risk: A systematic review for different institutional settings," Research in International Business and Finance, Elsevier, vol. 54(C).
    6. 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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