Is “quant” a busted flush? Since last summer’s crisis, when fund managers following quantitative strategies started blaming black swans, most have suffered net outflows, while many of the weaker funds have been badly hurt. Even where money has stayed put, no fund-of-funds manager or other investor is looking at quant in quite the same way.
Quant strategies have been around in various guises for more than 20 years, but managers have rarely seen anything like the turmoil of that single week in August. The problem was an overcrowded market where a lot of funds had similar positions, especially in US small and mid-capitalisation equities.
When some large multi-strategy funds started to liquidate those holdings to cover credit losses elsewhere, prices tumbled, triggering further selling. Markets bounced a week later, but a lot of funds had to take money off the table, and so missed out.
An industry this big can survive, however. Globally, there is at least $1,000bn invested in quant strategies, and probably double that. Quant remains attractively simple, in spite of the elastic definition. Whatever the investment horizon, strategies basically boil down to mean reversion: computers grind teraflops of data to unearth relationships between securities that tend, over time, to be stable. Trading is automatic, and executed quickly and cheaply.
But in future, investors will be choosier in picking quant managers, and will require better explanations of exactly how returns emerge.
Vendors of off-the-shelf packages such as MSCI Barra and Northfield, whose popularity contributed to those strong correlations among statistical models, may struggle to sustain sales at the level they saw before the crunch. As with other strategies, gearing will be tamed: debt to equity of closer to two times, rather than up to 10.
The episode is a reminder that computer-driven models work fine, until they don’t. And that in times of high anxiety, reliance on blinking boxes often makes things worse.