It is virtually impossible to obtain accurate historical data on the entire universe of hedge funds. The authors identify previously unexplored data sources that allow them to gain insight into the performance of hard-to-observe hedge fund companies that do not participate in major commercial databases.
Decades of hedge funds’ choosing whether to provide reports to publicly available, commercial databases has left the hedge fund industry without a standardized, comprehensive source of performance data. Even those managers who choose to report performance often do so selectively, reporting some but not all of their product offerings. The authors seek to bridge these data gaps to explore similarities and differences between mega firms that report performance to commercial databases and those that do not. Controlling for size, the authors find evidence that the unconditional return distribution of nonreporting hedge funds is similar to that of their reporting counterparts as well as to that of such publicly available hedge fund indices as the Hedge Fund Research Fund Weighted Composite Index (HFRI) and the Dow Jones Credit Suisse Hedge Fund Index (DJCSI).
How Is This Research Useful to Practitioners?
The hedge fund industry is notably more opaque than such asset classes as equity and fixed income. A substantial amount of the hedge fund industry’s growth can be traced to increases in assets under management (AUM) at a small number of management firms in the industry, which underscores the significant role nonreporting mega firms play in measuring the performance of assets invested in the industry. By identifying previously unexplored sources of reliable hedge fund data, the authors reveal methods that significantly extend the dataset and AUM coverage of commercially available hedge fund databases. Their research provides practitioners with greater insight into the performance of assets outside the mainstream commercial databases and helps analysts better assess the effect of missing returns on observed return distributions and thus on the performance characteristics of the hedge fund industry in general.
By exploring market conditions in which significant divergences between reporting and nonreporting mega hedge fund firms can occur, the authors provide insight into the degree to which nonreporting mega firms’ returns can be deduced from their reporting counterparts. Another benefit of examining missing returns from reporting funds is that the authors are able to closely examine and contribute to the literature by comparing the effects of hedge funds that voluntarily delist with those that are involuntarily delisted. The authors also study the drivers of commonly reported serial correlation in hedge funds.
How Did the Authors Conduct This Research?
The authors construct a consolidated database of hedge fund firms by exploring nonreporting hedge fund management firms that are in the Institutional Investor “Hedge Fund 100” list (II100) and the Absolute Return+Alpha “Billion Dollar Club” list (ARBDC) and do not participate in the three largest commercial databases: BarclayHedge, Hedge Fund Research Inc. (HFR), and Lipper TASS (Trading Advisor Selection System). For a nonreporting firm to be included, it has to be in the II100 or ARBDC surveys for that year. The authors’ integration of commercial databases and privately collected data is unique to the literature. The ability to locate returns of hedge funds that stopped reporting to commercial databases but continued to report performance to investors provides a rare opportunity to glean insight into the behavior of missing returns.
Following II100’s methodology, the authors use the hedge fund firm as a whole rather than its individual products as the unit of study. Because year-end AUM figures tend to coincide with accounting audits and are deemed more reliable, they use annual AUM data and engage institutional service providers that serve as custodians of hedge fund assets to verify the magnitude of the missing assets. To examine the return properties of nonreporting hedge fund firms against those of the observable reporting universe, the authors create equal- and asset-weighted indices of nonreporting firms to compare with publicly available hedge fund indices. Their construction methodology is consistent with the index construction methods of the hedge fund indices, and they use statistical procedures that are robust to nonnormality to compare the various return series.
Mega hedge fund management companies collectively manage more than 50% of the industry’s assets, so the authors’ research and basic unit of analysis should be of interest to hedge fund investors and students of the field. By showing that nonreporting and reporting mega hedge fund firms do not, in general, behave differently and by tracing transitory divergences in performance to such specific risk factors as differential exposure to credit markets, the authors contribute to our understanding of hedge fund performance dynamics. The results provide hedge fund researchers with a way to extend research conclusions based on commercially available data to previously unobserved large hedge fund firms.