Uncovering investment management performance using SPIVA data

Which performs better, passive or active funds management, a question that both fund managers and academics fiercely debate. Why does fund size matter? These are a number of typical questions that puzzle practitioners and academics alike. To date, the data has been shown to be somewhat problematic. This paper exploits the SPIVA and passive fund datasets with several novel methods in order to build a foundation for unbiased fund performance analysis and comparison. For this, we address a number of questions including: passive versus active management, fund size, time horizon and fund style on performance. We find that in general, passive funds outperform active funds due to lower management costs, larger funds tend to perform better and funds with longer (3+ years) records of accomplishment tend to perform better. Short termism tends to have a significant detrimental effect on performance. We introduce Dynamic Generalized Method of Moments to show that competition has a significant effect on fund performance. Furthermore, this demonstrates that SPIVA data has a significant dynamic panel time series that was largely ignored by prior research. This integrated dataset and associated methods that we illustrate here, provide both academic researchers and industry analysts alike with an environment to investigate and potentially draw conclusions about the fund factors that affect performance without the inherent limitations of the original sources.