Hedge fund titan’s new perspectives on fund management: 10½ Lessons from Experience

16 Jul, 2020 22:59
source: Singularity Financial

Singularity Financial Hong Kong July 16, 2020 – Hedge fund titan sees a quantamental future (Source: Bloomberg)

Marshall Wace LLP has shaped into one of the world’s biggest hedge funds, overseeing more than $44 billion and making billions for themselves in the process.

After more than three decades in finance, Marshall has just published a book, “10 ½ Lessons From Experience: Perspectives on Fund Management.”

His overall prognosis for the industry is optimistic, in that opportunities to make money will continue to arise, and there’ll still be humans around to take advantage of those moments. But he caps it all off with a cautionary tale for his peers — the half-lesson that makes the final chapter.

Financial markets are inefficient, prices have memories whereby today’s values influence tomorrow’s rates, and reflexivity creates feedback loops, Marshall writes. Moreover, nothing trades in a vacuum. Diamonds are relatively useless compared with water, yet the former are vastly more valuable — until you find yourself dying of thirst in a desert:

Markets are an exemplar of what cannot be contained within axiomatic thought. They are highly complex non-linear systems created by a myriad of half-informed or uninformed decisions made by fallible (human) agents with multiple cognitive biases.

Not only do those humans suffer from predetermined inclinations that are tough if not impossible to shake; they are also dumb. “You can’t model stupidity,” Marshall says. “It does not conform to any predictable rules.” But that fallibility helps to create the market inefficiencies that a good hedge fund manager can profit from. And a good trader has to be right only 52% or 53% of the time; a “truly great” manager can still be wrong 45% of the time, he says.

Marshall Wace splits its equity investment strategies about equally between fundamental stock picking managed by humans and systematic mathematical trading run by computers. Marshall reckons the former will continue to be important, albeit with more reliance on the latter.

“Machines have not won yet,” he writes. “Machines typically do not fare well in a crisis. They are not good at responding to a new paradigm until the rules of the new paradigm are plugged into them by a human.”

In the future, Marshall says people will become increasingly reliant on alternative data sets “to provide extra conviction to the mosaic they are building around a stock,” adopting a hybrid strategy between fundamental and systematic trading that’s been dubbed quantamental analysis. By harnessing a broader range of numbers than the traditional financial metrics, traders will gain an edge over the robots — even as competitors catch on to the usefulness of social media, credit-card spending and weather patterns to predict market moves.