Renaissance Technologies has one of the greatest investment track records in history. Since 1988, their Medallion fund has returned 66% per year gross of fees or an estimated $100 billion in profits.
The crazy thing is no one really knows how Jim Simons and his band of mathematicians, PhDs, rocket scientists, and former codebreakers does it.
Gregory Zuckerman tried to get to the bottom of this one in his book The Man Who Solved the Market: How Jim Simons Launched a Quant Revolution. The book doesn’t completely give away the secret sauce1 because Simons is notoriously secretive about his process but it does pull back the curtain in many ways.
This was different than most books about legendary investors because, unlike books about Buffett or Graham, you don’t immediately think to yourself ‘I could do that.’
Ren Tech uses a number of non-intuitive signals so it’s only fitting that the lessons from Simons and his firm are non-intuitive as well. Here are the main lessons:
Keep it simple. Most quant investors employ multiple models or sleeves within their main strategies. Simons decided the Medallion fund would use a single model to make things easier. Zuckerman explained:
The beauty of the approach was that, by combining all their trading signals and portfolio requirements into a single, monolithic model, Renaissance could easily test and add new signals, instantly knowing if the gains from a potential new strategy were likely to top its costs.
None of us are going to have a strategy as complex as Ren Tech but it’s nice to know even one of the most complex trading models in the world still keeps things simple in other ways.
Know who’s on the other side of your trades. If Renaissance made $100 billion in profits that means someone had to be on the losing end of their trades. One of their researchers joked it was mostly overconfident dentists who frequently traded that they took advantage of.
Simons gave a different answer:
Over time, Simons came to the conclusion that the losers probably weren’t those who trade infrequently, such as buy-and-hold individual investors, or even the “treasurer of a multinational corporation,” who adjusts her portfolio of foreign currencies every once in a while to suit her company’s needs, as Simons told his investors.
Instead, it seemed Renaissance was exploiting the foibles and faults of fellow speculators, both big and small.
The manager of a global hedge fund is guessing on a frequent basis the direction of the French bond market may be a more exploitable participant,” Simons said.
There are so many market participants that it can be difficult to discern who is on the other end when you’re buying or selling. But many investors assume the person on the other end is wrong or irrational.
Sometimes the person on the other side of your trade could be Jim Simons and his band of PhDs. This should give us all pause when we try to outsmart the market over the short-term.
Sometimes the whys don’t matter. One of the reasons Simons and his researchers have been successful is they didn’t come from an investing background.
So they didn’t care about how or why something worked, just that it did.
These trends and oddities sometimes happened so quickly that they were unnoticeable to most investors. They were so faint, the team took to calling them ghosts, yet they kept reappearing with enough frequency to be worthy additions to their mix of ideas. Simons had come around to the view that the whys didn’t matter, just that the trades worked.
By 1997, though, more than half of the trading signals Simons’s team was discovering were nonintuitive, or those they couldn’t fully understand.
At one point someone at Ren Tech fat-fingered a trade causing them to buy five times as many wheat contracts as intended, nudging prices higher. Analysts and the financial media blamed a poor wheat harvest the next day for Ren Tech’s miscue.
The whys in the markets don’t always make sense.
Human behavior makes the market go round. Even after reading the book it’s still impossible to succinctly explain how Simons figured out how to mint money. But this was the best simplistic explanation from one of his researchers:
“What you’re really modeling is human behavior,” explains Penavic, the researcher. “Humans are most predictable in times of high stress — they act instinctively and panic. Our entire premise was that human actors will react the way humans did in the past…we learned to take advantage.”
Many investors claim to take advantage of human nature. Ren tech actually does it.
Be humble. Zuckerman compared Ren Tech’s models with those of Long-Term Capital Management, another quant fund full of mathematicians and PhDs that blew up spectacularly in the late-1990s:
“LTCM’s basic error was believing its models were truth,” Patterson says. “We never believed our models reflected reality — just some aspects of reality.”
No one has the markets completely figured out. In fact, Ren Tech claimed to only be right on roughly 51% of their trades. People who think they’re right all the time will eventually be humbled by the markets.
Even the world’s greatest investors get nervous just like you and me. Last December, as the stock market was in the midst of a 20% decline, Simons became nervous about his investments. Simons was worth $23 billion at this point and knew he would be fine but he hated losing money.
So he called up the manager of his family office and asked, “Should we be selling short?”
The market bottomed the next day on Christmas Eve.
Don’t miss our podcast with Greg where we asked him a bunch of questions about the book and how he got some of his information:
And if you still can’t get enough on this topic, here’s a video Michael and Josh shot with Zuckerman last week in our offices:
1The secret sauce is obviously not just one thing either.