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Working paper
Accès libre
Anglais

The Cross-Sectional Distribution of Fund Skill Measures

Date de publication2018
Résumé

We develop a simple, non-parametric approach for estimating the entire distribution of skill. Our approach avoids the challenge of correctly specifying the distribution, and allows for a joint analysis of multiple measures–a key requirement for examining skill. Our results show that more than 85% of the funds are skilled at detecting profitable trades, but unskilled at overriding capacity constraints. Aggregating both skill dimensions using the value added, we find that around 70% of the funds are able to generate profits. The average value added after funds have reached their long-term size equals 7.1 mio. per year, which represents two thirds of the optimal value predicted by neoclassical theory. For all skill measures, the distribution is highly non-normal and reveals a strong heterogeneity across funds.

Mots-clés
  • Mutual fund skill
  • Non-parametric density estimation
  • Large panel
Classification
  • JEL : G11
Citation (format ISO)
BARRAS, Laurent, GAGLIARDINI, Patrick, SCAILLET, Olivier. The Cross-Sectional Distribution of Fund Skill Measures. 2018
Fichiers principaux (1)
Working paper
accessLevelPublic
Identifiants
  • PID : unige:110006
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Informations techniques

Création24.10.2018 14:54:00
Première validation24.10.2018 14:54:00
Heure de mise à jour15.03.2023 13:08:29
Changement de statut15.03.2023 13:08:28
Dernière indexation17.01.2024 03:57:51
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