October Volatility: Is It Crowded In Here Or Is It Just Me? by By Stan Altshuller, NOVUS
Many investors have observed the slow, relentless decline of alpha generated by hedge fund managers. As the industry continues to grow, fewer unique opportunities for alpha exist. Those pockets of dislocation attract a large number of smart, driven managers focused on exploiting those opportunities. Multiple managers participating in similar trade ideas leads to increased illiquidity. So when it’s time to sell, it can be difficult to find buyers. What we are talking about is often referred to as crowding – too many managers and dollars chasing the same prize. This installment of our “October Volatility” series will delve into the risks introduced through active management crowding. October presented a great case study of this phenomenon (as well as some others), and we have collected some empirical evidence to help shed light on the growing crowding dynamic and its consequences.
Growth of AUM and deterioration of liquidity
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We analyzed our Hedge Fund Universe (HFU), which is a value-weighted aggregation of publicly filed securities by over 1,000 hedge funds. Running this massive data set through our analytics platform, we have transparency into different aspects of the HFU, such as liquidity and concentration. We can clearly see that the market value controlled by hedge funds grew from 1999 to today. Consequently, aggregate liquidity has suffered greatly.
Assets controlled by hedge funds have ballooned
Even as managers moved up the market cap spectrum
It has not been enough to offset the decline in liquidity
By our estimates it would take hedge funds a total of 30 consecutive trading days to liquidate just a scant 20% of their aggregate holdings compared to 50% a decade ago – assuming they sell all together*. But if you ask any one particular manager about their liquidity, they are likely to say that their book is just as liquid as it was years ago. Here lies the problem: they are calculating liquidity assuming they were to sell alone, but these days they have many other hedge fund peers to contend with. For instance, if a hedge fund manager wanted to cut Cheniere Energy, Inc. (NYSEMKT:LNG) during the turbulence, he would benefit from knowing that there were 82 other managers that might want to do the same thing. This hidden, aggregate illiquidity is one of the factors contributing to volatile hedge fund performance this year and was especially evident in March and April.
Here is the same concept viewed from a different angle. Looking at the top 20 stocks of hedge funds by market value invested, on the rise is the number of consecutive trading days that hedge funds (assuming they sell together) would require to liquidate just their top 20 positions*. We also see that hedge funds today represent on average 17% of outstanding shares for those 20 stocks. In 2010 that number was 13% and in 1999, that number was only 3%.
*Assuming they represent no more than 20% of 90 day ADV; Icahn Enterprises removed as an outlier
Focusing on October 2014, if we compare the expected volatility and implied betas of hedge fund names against their realized volatility/betas, we can take a step towards isolating crowding as a driver of volatility and underperformance. We hypothesize that crowding is driving the difference in realized volatility compared to the expected behavior found through historical simulation. In doing so, we also isolate differences in security composition, when comparing hedge fund names to broader market indices. The differences in October for our High Conviction hedge fund filter are stark:
With regards to performance, it makes sense to beta-adjust the Hedge Fund holdings when comparing their performance, and from that, we can see there is negative alpha in October between a beta-adjusted market exposure (Tracking Return) and the Hedge Fund Conviction portfolio which historically generates significant alpha:
It’s not surprising that the effects of crowding seem to be more pronounced. Data suggests there is a premium to account for when liquidating highly crowded names. Our clients analyze crowding to better understand their exposure to this risk factor and at times like October it proves to be a powerful tool in their arsenal.