Russia’s Gary Kasparov was the world’s No. 1 chess player for almost 20 years.
He is best known in the U.S. for losing a chess match to IBM’s supercomputer Deep Blue in 1997.
In his book Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins Kasparov concedes that human chess players don’t have a prayer against today’s powerful computers.
Why is that?
Computers don’t get tired. They don’t get moody. They don’t make mistakes.
They are never “off their game.”
Meanwhile, a human chess player has to screw up only once to lose a match.
The same reasoning applies to trading the financial markets…
Emotions are a trader’s worst enemy.
In contrast, quantitative (or quant) based algorithms are immune to both a trader’s and Mr. Market’s mood swings.
So the question arises: “Is quant investing destined to take over the investment world?”
Rise of the Quants
The biggest quant investing firms like Renaissance Technologies, Two Sigma Investments and D.E. Shaw Group today manage tens of billions of dollars. In total, quant-focused hedge funds manage almost $1 trillion in assets.
Throw in the newer breed of exchange-traded funds and mutual funds, and that number rises to $1.5 trillion.
When I started my investment career in the 1990s, quant investing was about identifying momentum in stocks, riding trending prices like a surfer rides a wave.
I developed my first profitable momentum-based trading system in 1994 using a now defunct computer program named “Windows on Wall Street.”
Today, cutting-edge quant hedge funds use artificial intelligence (AI) and machine learning.
This kind of trading requires more the skills of astrophysics PhDs than those of traditional financial analysts.
Over the past decade, this quant-driven approach to trading has exploded.
That’s partially because any edge stemming from fundamental research has all but disappeared.
In 1815, Baron Nathan de Rothschild boasted that he used carrier pigeons to learn about the outcome of the Battle of Waterloo ahead of other investors – and thereby made a fortune.
George Soros attributed his early success investing in European companies in the 1960s to being a “one-eyed king among the blind.”
Today, financial traders have more information on their smartphones than what the world’s top hedge funds did 20 years ago.
Being a one-eyed king just doesn’t cut it anymore.
Old-Style Hedge Funds Go Quant
Hedge fund manager Paul Tudor Jones’ trading skills were enough to catapult him into the Forbes 400.
Yet his Tudor Investment Corporation has fallen on hard times, and his firm’s returns have tumbled since 2008.
In 2016, Tudor Jones began to hire quantitative analysts to kick-start his firm’s lagging performance.
What is Tudor Jones’ new philosophy?
“No man is better than a machine, and no machine is better than a man with a machine.”
Hedge fund billionaire Steven A. Cohen calls this the “man plus machine” approach.
Here’s why I think this approach makes sense.
First, taken to the extreme, quant-driven strategies sometimes identify mathematical relationships that simply make no sense.
In a paper published more than 20 years ago, quant-investment managers David Leinweber and David Krider highlighted the absurd correlation between the butter production of Bangladesh and the returns of the U.S. stock market.
But it took human judgment to recognize that absurdity.
Second, the more money that is managed according to algorithms, the more likely it is to lead to massive market disruptions.
The experience on this is clear.
Quant-driven “portfolio insurance” exacerbated the market crash in October 1987.
Long-Term Capital Management’s quant models brought global financial markets to the brink of collapse in 1998.
And in the “flash crash” on May 6, 2010, quant traders caused the Dow Jones to plunge 998.5 points within 36 minutes.
Finally, quant investing is becoming just a bit too fashionable.
Just in February, BlackRock – the world’s biggest fund manager – announced it’s setting up an AI “lab” in Silicon Valley.
Blackrock is hoping that the magic fairy dust of Silicon Valley technology companies will rub off on mainstream investment houses as well.
Some newer quant-focused firms are even reluctant to call themselves hedge funds.
One firm – Empiric Capital – calls itself a “technology company operating in financial markets.”
Lessons of Gary Kasparov and Deep Blue
Gary Kasparov concedes that computers can outplay humans in a complex game like chess.
The question remains whether computers can outplay humans in the financial markets.
As I’ve noted, I’m skeptical.
For all its complexity, the game of chess has a limited set of rules even a now 20-year-old computer like Deep Blue could solve.
But global financial markets are infinitely more complex than chess.
My guess is that Kasparov would agree.
So hedge fund icon Paul Tudor Jones is correct when he says “no machine is better than a man with a machine.”
Yes, computers can provide information to help improve human judgment.
But because financial markets are more complex than chess, human judgment remains essential.
And that may be humanity’s greatest edge of all.
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