Hedge Funds Are Not Designed to Outperform Bitcoin

 As a hedge fund veteran – both as an allocator and a founder – I feel compelled to address what I believe was a misinterpretation of the hedge fund value proposition. 

Time frames are important to consider when it comes to performance assessment, and measuring outcomes on a single calendar year basis is suboptimal. Professional investors tend to assess performance over a market cycle of 3-5 years to allow for full consideration of an investment’s risk/return characteristics. Compressed timeframes make for more frequent headlines but judgments should not be rendered on the basis of a single arbitrary data point. Attempting to do so leads to spurious conclusions based on statistically insignificant data. Should we be talking about how bitcoin (+305%) meaningfully underperformed ethereum (+473%) in 2020?​  

The headline also makes a false comparison. For starters, the vast majority of traditional hedge funds have limited if any exposure to bitcoin (BTC). For every Tudo​r Investment Corporation there are thousands of other funds who give little consideration to crypto beyond what they read in the news. So why compare their collective performance to an asset that has virtually nothing to do with their funds? Doing so is akin to comparing the average global equity mutual fund’s performance to that of Microstrategy (MST​R).​  

Unless a fund manager specifically guided to such expectations (i.e., “Our performance should be measured against BTC”), this comparison still would not make sense even if the fund had meaningful exposure to BTC. The Ar​k Innovation ETF (ARK​ K)​ has Tesla (TSL​A)​ among its top holdings. Should we talk about how, despite a record year, ARKK (+149%) failed to keep pace with TSLA (+743%) in 2020?  

The fact of the matter is that most traditional hedge funds are relatively diversified, making comparison to any single asset – even relevant ones – an unproductive exercise. This is also true in a broader asset class sense. Borrowing from our own prior comment​s on the topic:​  

…in their purest form, hedge funds are NOT meant to relatively outperform any particular benchmark. They are instead designed to maximize absolute and risk-adjusted returns in relatively uncorrelated fashion. The risk-adjusted part is of particular relevance here. 

Professional investors are attempting to solve for several things when they make allocation decisions. In the world of alternative investing, risk-adjusted returns are the key focus for most. This is especially important in the context of crypto, where volatility is the primary ​gating mechanism​ for investors. 

(Note: The risk-adjusted return of an asset effectively explains how much risk is required to achieve a certain level of return. If two assets provide the same level of return, then the asset with lower risk will have the better risk-adjusted return.) 

For a proper treatment of this issue, we recommend a Cliff Asness post on the topic entitled ​The Hedgie in Winter​. By no means an apologist for hedge funds, Asness points to the flaw in comparing hedge fund performance to indices, which by definition represent a beta of one. 

Comparing hedge fund absolute returns to industry benchmarks is a common mistake. It is most often committed by journalists who lazily view relative underperformance of hedge fund hotshots as good headline fodder. It is therefore unsurprising that many crypto observers take a similarly simplistic approach when assessing fund performance. After all, most operators in this space have limited — if any — asset management experience. 

The above comments were made in reference to industry observers reveling in the relative underperformance of crypto hedge funds in 2019, but the point nonetheless applies. 

The article goes on to mention how loose monetary policy, bitcoin’s relatively small market capitalization, and base effects may help explain the cryptocurrency’s strong 2020 performance. Such dynamics could surely be explored on their own without making misplaced performance comparisons that lead to the wrong conclusions.