Critical Finance Review > Vol 7 > Issue

Diseconomies of Scale in the Actively-Managed Mutual Fund Industry: What Do the Outliers in the Data Tell Us?

John Adams, University of Texas at Arlington, USA, jcadams@uta.edu Darren Hayunga, University of Georgia, USA, hayunga@uga.edu Sattar Mansi, Virginia Tech, USA, smansi@vt.edu
 
Suggested Citation
John Adams, Darren Hayunga and Sattar Mansi (2018), "Diseconomies of Scale in the Actively-Managed Mutual Fund Industry: What Do the Outliers in the Data Tell Us?", Critical Finance Review: Vol. 7: No. . http://dx.doi.org/10.1561/104.00000063

Forthcoming: 31 Oct 2018
© 2018 2018 John Adams, Darren Hayunga and Sattar Mansi
 
Subjects
 
Keywords
G10G11G12
Diseconomies of scaleMutual fundLiquidityInfluential observationsOutliers
 

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In this article:
1. Introduction
2. Effect of Scale on Performance: Replication of the Chen et al. (2004) Results
3. The Impact of Outliers on the Chen et al. (2004) Estimates
4. Liquidity, Organization, and Out of Sample Tests
5. How Widespread is the Outlier Problem in Finance Research?
6. Conclusion
Appendix A: Univariate Identification and Treatment of Multivariate Outliers: An Illustration
Appendix B: Results for Alternative Robust Estimators
Appendix C: Robustness Checks
References

Abstract

Recent research suggests that improper identification of outliers can lead to distorted inference. We investigate this issue by examining the role that multivariate outliers play in research outcomes using the Chen et al. (2004) study. We find that the documented negative relation between scale and return performance in the actively managed mutual fund industry is an artifact of extreme observations. A manual examination of the most influential observations with verifications against outside sources shows that these outliers are largely bad data. Removing the errors reduces the point estimates on the effect of fund size, rendering it economically and statistically insignificant. Further analysis employing regressions that mitigate outlier-induced bias and extending the sample through 2014 confirm our findings. Our evidence contributes to the recent research on the importance of outlier identification in finance research.

DOI:10.1561/104.00000063