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Browsing by Author "Hayunga, Darren"

Now showing 1 - 3 of 3
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    Diseconomies of Scale in the Actively-Managed Mutual Fund Industry: What Do the Outliers in the Data Tell Us?
    Adams, John; Hayunga, Darren; Mansi, Sattar A. (2018-12-31)
    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.
  • Index fund trading costs are inversely related to fund and family size
    Adams, John; Hayunga, Darren; Mansi, Sattar A. (Elsevier, 2022-07)
    Trading costs are a significant, but unobserved, drag on mutual fund performance. Because an index fund does not engage in securities selection or market timing, its trading costs are equivalent to its underperformance relative to its benchmark plus any securities lending in-come it earns. Using a large sample of index funds, we find positive returns to scale at the fund and family levels. We also find greater fund size helps alleviate the higher trading costs associated with illiquid equities and that net trading costs are comparable in magnitude to expense ratios.
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    Scale and Performance in Active Management are Not Negatively Related
    Adams, John; Hayunga, Darren; Mansi, Sattar A. (2021-08-16)
    We revisit the nature of returns to scale following Pástor, Stambaugh, and Taylor (2015). Using replicated versions of their domestic equity fund sample, we confirm their negative and significant relation between industry scale and performance. However, upon closer examination we find the diseconomies of scale at the industry level result is an artifact of data errors that comprise less than 0.05% of the sample―168 out of 332,516 observations―that occurred most often in the year 2000. We are unable to find industry level diseconomies of scale in the post 2001 era. A major source of these errors is the incorrect use of Morningstar’s current performance benchmarks to measure historical return performance. We confirm the non-result findings using Fama-French three-factor adjusted returns, which are not subject to benchmarking errors.