Paul Tudor Jones, one of the greatest hedge fund managers of all time, said this a few years ago:
“No man is better than a machine, and no machine is better than a man with a machine.”
Jones was talking about the power of software, algorithms, artificial intelligence, and machine learning as applied to investing. But his deeper point was that human talent should not be replaced by machine talent. The two should be combined for maximum results.
Machines can do certain things far better than humans. But humans can do certain things far better than machines. There are layers of wisdom, talent, and judgement that can’t be built into a software program.
So rather than choosing one or the other — machine-based process or human-based process — the most powerful course of action is bringing them together. That is what Jones meant.
This is also a description of what we do at TradeSmith:
- We use algorithms and software to improve the investing process, and we try to give as much heavy lifting to the “machines” as possible.
- But we also tap into deep reservoirs of non-replicable human experience. We do this by tracking the world’s best investors, observing what they invest in, and plugging that data into our software.
The money managers in our Billionaires’ Club don’t necessarily have access to privileged information. But they do have volumes of world-class information that others don’t — like satellite image feeds that tell them whether the parking lots of a big-box retail chain are trending empty or full, for example.
More importantly than that, the billionaire money managers we track have layers of nuanced judgment built up over the course of many years, with high quality information sources updating the outputs of that judgment on a daily basis.
And so, at TradeSmith, we execute on the man-machine combination by tracking the stocks that world-class money managers and investors buy; noting the changes made to those portfolios on a quarterly basis; and maximizing that data with algorithms.
The power of this approach was recently brought to light by an amusing story: The arrival of cutting-edge technology in a 200-year-old fish market.
On Aug. 1, the New Yorker published a piece titled, “The Last Robot-Proof Job in America?” You can read the piece here.
The story is not about robot-proof employment so much as the deep, non-replicable value of human experience and judgment — and the way “old school” human skills are being combined with machines.
The Fulton Fish Market is a seafood wholesale market that is two centuries old. It is the second largest fish market in the world, behind only the Tsukiji market in Tokyo.
With roots in Manhattan and the Bronx, the Fulton Fish Market had long focused on serving fresh seafood to restaurants and retailers in the New York City area. That is where cutting-edge technology comes in.
With the arrival of a website and an e-commerce plan, the Fulton Fish Market expanded its business to serve customers nationwide. This required a powerful infusion of software and automation to handle the intense logistics of delivering fresh seafood — while it is still fresh — to a far-flung customer base.
Mike Spindler, Fulton’s CEO, told the New Yorker he could “get a fish to Warren Buffett in Omaha, Nebraska, that’s as fresh as if he’d walked down to the pier and bought it that morning.” That is extremely hard to do.
Before the Fulton Fish Market figured it out, the general consensus was that selling seafood on the internet is impossible. There were too many logistical issues. The argument was: You can’t pack and ship something as time-sensitive and delicate as seafood, maintain high standards of excellence and quality, and still turn a decent profit all at the same time.
But they figured out how to do it with a combination of humans and machines. To tackle fresh seafood as an e-commerce item, they created an “Amazon-esque warehouse and logistics system” as the New Yorker puts it — and coupled it with the judgment of human experts.
The “Last Robot-Proof Job” the New Yorker speaks of in the article title belongs to Bobby Tuna, the most respected fish picker in Manhattan (and possibly the entire Western Hemisphere).
Bobby Tuna’s real name is Robert DiGregorio. He has been in the seafood business for 47 years, and literally wrote the book — there is an actual guidebook — on Tuna Grading.
His value to the operation is a level of experience, discernment, and judgment that no computer can match. “I’ve bought and sold literally millions of fish,” he says. Bobby Tuna knows so much about seafood, it would be impossible for a computer to model the sea of connections in his brain. That knowledge is put to work every morning in real time.
It takes a deep reservoir of experience to pick the right fish for an order. Seafood is an especially tricky challenge, not just due to the freshness requirement, but because everything is different on a day-to-day basis: The daily catch is different. The individual fish are different (in terms of size and quality). And the mix of orders is different.
That is why the Fulton Fish Market has humans presiding over all this — Bobby Tuna and a five-man team — making choices in real time and feeding their selections into the machine.
“Think of it as a power assist,” the CEO says of the Amazon-style technology that moves the seafood after Bobby and his team make the call on which fish goes where. “It’s like power steering on your car.” The subtle point being: The “car” still has human drivers.
In our view, this is the future of investing, too — and an early version of the future is already here. Machines, software, and algorithms will only grow more powerful in the coming years. But that added power won’t replace the value of human talent. Instead, it will make the man-machine connection all the more powerful, by expanding the reach and capability of what experienced humans can do.
At TradeSmith, we put this man-machine mix into practice on a daily basis. We couple the sorting and filtering capability of our algorithms with the stock selection input of human investment legends (the members of our Billionaires’ Club, whose portfolios we track and update every quarter).
You can apply this logic to your own investing, too. Don’t think of investment software as a means of replacing your input or judgment completely. Think of it as a way to elevate your performance.
When algorithms handle the tasks best suited to a computer, the human mind is that much more freed up to focus on elements of human value-add — like adjusting behavior and regulating emotions.
Here and now in the 21st century, we can all use a software “power assist” to improve our long-term investing results. The man-machine combination shows us how.
