The new quant frontiers in under-utilised assets

With more traditional methods of finding alpha proving to be more difficult, the hunt is hotting up.

The result? It’s driving an increasing use of quant research techniques – among even traditional asset managers.

Many are taking a more flexible and unconstrained approach. They're diversifying their return stream into strategies they believe offer better risk-reward profiles than traditional asset classes.

Quantitative investing is gaining traction as investors evaluate an increasing number of data sets, time horizons, trends and computer models.

“Quant methods are spreading across the investment industry and will become status quo,” says Igor Tulchinsky, founder of WorldQuant. “Only firms with a truly unique approach to discovery and decision-making will set themselves apart and stay ahead of the crowd.

The chief investment officer of the UK hedge fund Man Group, Sandy Rattray, is like-minded. He has said that he sees this scenario growing ahead as quants extend their methodology to data-rich areas like private equity and venture capital.

Opaque, messy, and traded mostly by phone rather than on an exchange, these were previously considered unassailable and untouchable by computer-driven trading.

Firms now putting their resources behind ‘systematic credit investing’, however, range from big traditional money managers such as BlackRock to hedge fund grandees like Citadel and Man Group.

The coming decade, believes Man Group's Rattray, will see quants seizing ever more territory in areas of finance long considered dangerous terrain for algorithmic strategies.

Quant investing uses data and systematic computer-driven models to make investment decisions.

It has also proved highly effective of late in measuring new areas in finance such as the ESG landscape.

Here, quant techniques are helping to standardise ESG. They're uncovering ESG metrics – and complex concepts such as empowerment, bias, and selection – that are often proving alpha enhancing.

So where else is processing power, models, algorithms and big data managing to systematically squeeze money?

Another area is quant trading in crypto. This is despite its being challenging and different from other asset trading.

In 2021, the most common crypto hedge fund strategy was quant, according to data from PricewaterhouseCoopers.

As bitcoin and ethereum, and others, have become more acceptable to institutional investors, scores of quants and systematic traders have migrated to cryptocurrencies.

Crypto is not only a new asset class, however, but a technological breakthrough. It is new landscape for quant trading that is entirely different to traditional capital markets. That mean it's rife with market inefficiencies and paltry historical data.

But quants are finding their creative ways round this, for example, by backtesting and modelling volatility.

Unexplored sources of alpha, a new generation of financial primitives and unconventional risk models are just some of the factors pushing the boundaries of quant trading in crypto.

The potential is strong, says Jesus Rodriguez, the CEO of IntoTheBlock, a market intelligence platform for crypto assets. “Crypto might not have been designed for quant strategies. But it could end up being the asset class that catalyses a new wave of innovation in the quant space,” he adds.

Where it will end is unclear. But it’s certain that as the best quants continue to become more efficient, more rich seams of alpha will be uncovered.

Providing, that is, they ask: “what are the limitations of our methods, and where can they go wrong?”