Quant Hedge Funds Trail Old-School Ones, But Reap All the New Money
On the TV show Billions, swashbuckling hedge fund magnate Bobby Axelrod fires his quant team. Axe thinks this crew is a waste of money when good old fundamental research (not to mention a bit of chicanery) has done just fine for him in the past.
While many on Wall Street nowadays view such an attitude as outdated, the fictional character Axe’s take on the wonky world of quantitative money management has some merit: Quants have not yet, at least, proven to be superior. The odd thing is that investors favor the quants anyway.
Quants are billed as the new wizards of finance, their computers combing through reams of data, concocting complex trading algorithms, with the goal of getting a leg up on crusty old methods. The enticing promise of data-driven strategies is why quants now make up 30% of hedge fund investments—a tally that is growing, according to the Hedge Fund Research’s count. Quants made up just 26% in 2010.
But even wizards can come up short. Through mid-year, quant hedge funds were down 1.1%, while hedge portfolios in total were up 0.81%, according to HFR. At the same time, the S&P 500 recorded a total return (with dividends reinvested) of almost 3.6%.
In fact, while quant funds have enjoyed some very strong years, in general they have lagged behind conventional hedge funds. Over the past 10 years, quants have averaged 2.15% annually, versus 3.45% for non-quant funds, HFR finds.
Part of the reason for the underperformance may be that markets, since the financial crisis, have been rocked by trends that are difficult to construct a mathematical model for. Quant funds specializing in commodities, for instance, have found themselves whipsawed thanks to unforeseeable developments ranging from China’s fluctuating need for raw materials to President Donald Trump’s tariffs.
Moreover, the stock market has steadily climbed since its March 2009 nadir, with little volatility. Quant funds tend “to do well when there’s volatility, when they find inefficiencies” to exploit, noted Don Steinbrugge, chief executive at Agecroft Partners, a hedge fund consulting firm.
To be sure, quant returns have been a mixed bag, with a fair number of stand-outs. “Some of the top ones are performing very well this year,” said Amy Bensted, head of hedge funds at research firm Preqin. Indeed, the Financial Times reported July 25 that the two largest quant funds, both offered by Renaissance Technologies, were up 3% and 4% this year. By the same token, Systematica, another noted quant shop, lost 6.9% through May, Bloomberg said. Renaissance and Systematica didn’t answer requests for comment.
Regardless of their performance, quant funds are gaining popularity at the expense of more conventional hedge funds. For the past three years, non-quant hedge funds have suffered an outflow of investment money, while quant ones continued to gain. As of mid-year 2018, HFR data indicate, quants attracted a net $4.6 billion and non-quants had withdrawals of $6.6 billion.
The flashy promise of quant funds, especially those deploying artificial intelligence, plainly is overcoming their overall uninspiring returns. To be sure, judging a hedge fund by its track record alone is questionable. Although many people think that hedge funds are supposed to outpace investing benchmarks like the S&P 500, hedge operators say, with some justice, that they really are offering diversification.
And quant hedge funds are arguably even better vehicles for diversifying investor holdings. Human financial managers may be swayed by the madness of crowds, which translates into market index movements, but statistics are immune from that influence. “Money is still going into quant funds because they are not correlated” to traditional stock and bond benchmarks, Steinbrugge pointed out.
Exponential growth of information available through computers is spurring quants’ usefulness to hedge funds. “Twitter feeds, satellite images, increasing amounts of data, all will make quants grow,” said Hossein Kazemi, senior advisor at the Chartered Alternative Investment Analyst Association.
Along with that, the divide between quant and non-quant funds is becoming increasingly blurred as old-school hedge operators look for an edge. “More and more of the big hedge funds,” long dependent on human guidance, Kazemi said, “are using quant strategies, too.”
Much like infantry soldiers these days depend on aerial support from helicopter gunships, many of the top hedge funds now believe that quant insights are a vital supplement to their fundamental research.
Unlike Bobby Axelrod, Ken Griffin’s hedge fund firm, Citadel, has a penchant for hiring quantitative analysts, and earlier this year brought aboard a 10-person quant team from Hutchin Hill Capital after that hedge fund closed. At the Tudor Investment hedge fund firm, founder Paul Tudor Jones in 2016 hired a theoretical physicist to sparkplug his burgeoning quant unit.
Magnetar Capital, an old-style hedge fund, has bolstered its customary human decision-making with data-generated perceptions, such as the one on executive ownership of company stock. The common assumption is that increased insider buying of stock means good news is ahead for a company and selling (apart from planned sales to improve diversification) connotes the opposite.
But a quant examination of this belief divined that executives’ internal stock ownership was a weak harbinger of a company’s fortunes—thus Magnetar stock pickers should disregard it, the quant team maintained. “There are times,” the company said in a statement, “when quantitative analysis debunks some active managers’ rules of thumb for picking stocks.”
So, while quant methods may not be an infallible source of investing wins, the additional intellectual firepower they bring ensures ever-expanding acceptance among hedge funds.