Quantitative investment has a black-box reputation, or a mysterious quality that Investopedia describes as something that “produces useful information without revealing any information about its internal workings”.
But the black-box status of the statistically significant investment style is misleading, according to Jan Rohof, Northern Trust Asset Management (NTAM) Asia-Pacific quantitative solutions director – at least for those firms plying the now well-established factor-based routes.
“Quant investing means different things to many people,” Rohof said, from opaque high-frequency trading shops to the more “transparent” factor-houses like NTAM.
“We’re a glass box,” Rohof said.
He said the NTAM quant model provides clients look-through to underlying holdings as well as an economic rationale for whatever portfolio emerges from the number-crunching process.
While sophisticated maths, complex algorithms, deep data reservoirs and computing grunt might underpin portfolio construction, quant managers also need to supply a real-world explanation of outcomes, Rohof said.
“Technology helps us be quant investors but we still have to understand what happened.”
Variously known as systematic, smart beta or factor-based investing, the quant method followed by NTAM traces its roots to the Nobel Prize-winning theoretical insights of Eugene Fama and Ken French in the 1990s.
The Fama-French research initially added two new persistent market ‘factors’ – value and size – to the-then capital asset-pricing model assumption that overall market risk (defined by volatility) drove returns.
Over time the Fama-French theory has been refined as well as multiplied by some studies into a ‘zoo’ holding hundreds of, mostly ephemeral, risk factors.
NTAM, however, relies on a handful of classic factor animals – quality, value, volatility, and momentum – in its quant modelling, notably downplaying the original Fama-French outright ‘size’ tilt that weights more to small-cap stocks. Nonetheless, Rohof said the manager does “acknowledge the importance of managing size tilts and the alpha-rich nature of the small cap universe” with a long-running strategy in the asset class.
The group has been offering quant-based strategies to institutional investors for more than 30 years.
“We believe in multi-factor investing,” Rohof said, to combat the well-documented propensity of the single market risk elements to underperform for sometimes long periods.
Value, for instance, has struggled to fire as a factor since the end of the global financial crisis.
If certain market risk factors appear entrenched, possibly reflecting human behavioural biases, quant-investing is not set-and-forget.
Rohof said the global economy has changed dramatically since the birth of the factor movement along with rapid advances in the technology used by quants to research and trade markets.
“The premise of factor-investing hasn’t changed but the market has,” he said.
Quants need both the technological tools to keep on top of market developments as well as investment expertise and access to ever-more granular datasets to identify and harvest the factor fruits.
In February this year the US-headquartered NTAM, part of wider Northen Trust banking group, signalled further confidence in the factor-future after a hiring spree that saw 13 quant specialists join the team in Amsterdam – many moving across from the Dutch pension fund giant, APG Asset Management.
The Melbourne-based Rohof, too, is a recent NTAM recruit, shifting across last December from the Australian arm of another famed Dutch quant house, Robeco.
Currently, NTAM manages about US$43 billion of factor-money including a sizable chunk for NZ institutional investors.
The NZ Superannuation Fund reported NTAM managed about $4.5 billion in a multi-factor global equities portfolio as at June 30 last year (as well as over $8 billion in pure index plays) while both ANZ and Westpac also have significant allocations to similar strategies.
Rohof said the manager’s investment style would continue to hinge on “risk efficiency” by exploiting the alpha opportunities available to well-resourced factor-hunters.
But he said the manager was also exploring newly available “alternative datasets” or artificial intelligence (AI) techniques that could bring further depth to the quant mix such as incorporating sustainability into the equation.
Any innovation, though, must be minus the mystique often attached to AI and the like.
“People worry that AI is just another quant black box,” Rohof said. “But in my view, the biggest black box in the universe is the human brain.”