The consequences of crowding are ever-present. Normally it’s restricted to inhibiting alpha generation, particularly for fund managers with a less sophisticated investment process than their peers. Occasionally, however, the effects are devasting, particularly when it’s associated with high leverage.
There’s no substitute for experience and I’ve witnessed this firsthand in August 2007 during the so-called Great Quant Unwind. We survived this event – indeed our quant fund registered a positive return that month. More on this later. First, let’s look at how crowding risks typically play out.
In broad terms, here’s the sequence of events:
An investment strategy, or investment style, generates strong alpha.
Allocators – who tend to chase what’s hot – invest more money in this strategy.
New entrants emerge to satiate investor demand. A virtuous circle ensues.
It gets more difficult for the fund managers to generate alpha as the mispricing opportunities get arbitraged away.
Fund managers deploy more leverage to generate the returns investors are accustomed to.
A forced unwind event occurs. It can be difficult to determine the precise catalyst (e.g. during the Great Quant Unwind).
Panic ensues as fund managers are forced to de-lever at the worst possible time.
Forced unwinding exacerbates the share price moves, resulting in extreme losses.
Other investors sit on the sidelines until the opportunity set becomes so attractive that they take the opposite side of the unwind trades. In extreme cases, a bailout package may be required to restore market order.
The crowded investment strategy is now out-of-favour and the relative paucity of money makes it easier for the “survivors” to once again exploit the mispricing opportunities they’re targeting.
The catalyst for this research note is an excellent Bloomberg news story I’ve just read titled “Citadel and Peers Face More Scrutiny as Pod Shop Risks Grow”.
We’ve spoken to several multi-manager firms (we’ll use this description rather than pod shop). I’ve been surprised that nearly all of them look at quant funds through the same risk lens using standard risk models.
Many are fixated on idiosyncratic risk, focussing primarily on this risk metric (which is perceived as a “good” form of risk). We believe this only makes sense for a subset of quantitative investment strategies, such as risk-arb, index-arb, and pairs. It doesn’t make sense for a multi-factor investment process such as ours, as documented in the following research note: https://www.oqfundsmanagement.com/post/the-potential-pitfalls-of-focusing-on-idiosyncratic-risk
This exacerbates crowding risk. The multi-manager firms are getting large inflows and deploying the money to similar quant strategies.
These strategies also require high leverage. Factor risk should be neutralised (hence the focus on idiosyncratic risk) and stock concentration risk isn’t compatible with the anomaly being targeted. This leaves leverage risk as the only appropriate way to generate return volatility and decent headline performance. This combination of crowding and high leverage is extremely dangerous.
Fortunately, we’re exploiting an alpha source which currently isn’t crowded. And even if this changes, by maintaining a conservative level of leverage by taking appropriate alpha and risk factor bets, we can withstand the risks associated with forced unwinds.
This brings me to my experience during the Great Quant Unwind. Leading into this event we had relatively low gross exposure and during the unwind we never came remotely close to margin calls. This meant we were able to exploit the extreme liquidity distortions and generate a positive return during a month which wiped out numerous multi-factor quant funds.
We’re also grateful that, despite recent industry trends, not all allocators focus solely on idiosyncratic risk and generic risk models that aren’t compatible with our investment process. We’re continuing to attract inflows from sophisticated investors who recognise the benefits of our investment approach and ability to exploit an uncrowded alpha source.
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