- The business scientist
- Posts
- Jim Simons
Jim Simons
This is the story of how a reclusive codebreaker became the most successful investor you've never heard of. No market hot takes. Just math, machines, and the most mind-bending returns ever recorded.
In partnership with
What you will learn:
Why Renaissance Technologies’ Medallion Fund makes Wall Street nervous
How Simons turned abstract geometry into real-world billions
What sets “quant” investing apart—and why others couldn’t copy it
Lessons in patience, hiring, and staying weird
I hope you enjoy it.
Did someone forward you this email? Sign up here
Jim Simons
When most people retire, they buy a boat.
When Jim Simons retired, he launched a fund that would embarrass Wall Street for three straight decades.
He had a wildly unconventional path.
Simons started in academia. After earning a Ph.D. in mathematics from UC Berkeley at just 23, he worked on top-secret codebreaking unit for the NSA during the Cold War. But when he publicly opposed the Vietnam War, he was fired.
He later went back to academia, became chair of Stony Brook’s math department, and co-developed the famous Chern–Simons theory, which later influenced quantum physics and string theory.
Then, in his 40s, Simons did something unthinkable: he walked away from theoretical math and bet that financial markets could be cracked like any other system.
And he was right.
In 1982, Jim Simons officially stepped away from academia and launched Renaissance Technologies in a strip mall office in Setauket, Long Island.
He had no experience in finance and no Wall Street connections
But he had a hunch: that markets moved in patterns but not obvious ones, but hidden structures buried beneath the noise, detectable only through rigorous math, massive data, and statistical modeling.
At the time, this idea was radical. Quantitative investing was still fringe. The efficient market hypothesis reigned supreme. Most traders still relied on gut instinct, technical charts, and “tape reading.”
Simons wanted none of it.
He began assembling a team of outsiders: cryptographers, physicists, speech recognition experts, pure mathematicians, and other similar people who had zero background in finance but shared one thing in common: they could find signal in noise.
One early hire, Leonard Baum, had helped develop the Baum-Welch algorithm, used in speech recognition and bioinformatics. Another, Henry Laufer, was a topologist and math professor. These guys were puzzle-solvers.
The team collected reams of historical pricing data—back when you couldn’t just download it—and began applying statistical models to look for anomalies. They noticed patterns: small, short-term price movements that weren’t random.
But exploiting those patterns wasn’t simple.
Their first model, based on commodities and currency data, lost millions. The fund went through periods of violent drawdowns. Employees walked. Simons nearly shut it down.
Even his wife, Marilyn, reportedly told him, “You should quit this and go back to mathematics. You were happier there.”
But Simons believed the math would win eventually. He tightened the team, doubled down on infrastructure, and developed one key insight:
The market is not efficient, but it’s just efficient enough to fool most people.
From that point forward, they focused on ultra-short-term anomalies. Think micro-predictions measured in hours or days, not months. Their advantage wasn’t in predicting Amazon’s 5-year outlook, it was in spotting a slight statistical bias in price movement between 10:06 and 10:12 a.m.
As their models improved, so did the returns. Then came a breakthrough.
The team figured out how to combine hundreds of tiny, uncorrelated signals into one massively reliable prediction engine, like assembling a symphony from the chaos of noise.
They were surfing the statistical residue left by slower, less disciplined players.
And slowly, they began building what would become the most successful trading machine the world had ever seen.
The Medallion Fund: Wall Street’s Enigma
By the late 1990s, Renaissance’s flagship Medallion Fund was achieving incredible returns: 66% annually before fees, 39% after, for over 30 years.
It was so profitable, the firm eventually returned outside capital and ran Medallion exclusively for employees. No one else was allowed in.
They ran it like a black box:
No public commentary
No media appearances
A fortress of secrecy even within the firm
To this day, no one has successfully reverse-engineered their strategy.
What’s known: it relied on high-frequency trading, pattern recognition across global markets, and meticulous risk control.
What’s unknown: basically everything else.
Lessons from Jim Simons
1. Hire strange geniuses.
He hired people who could see patterns where others saw noise: codebreakers, astronomers, puzzle addicts. He believed markets were math problems in disguise.
2. Bet on models, not moods.
While traditional traders made decisions on hunches, Simons trusted algorithms—even when they felt counterintuitive. He once said, “Models beat humans. Every time.”
3. Keep your edge private.
Their advantage came from secrecy, and they guarded it religiously. The less people knew, the longer they could win.
4. Compounding is a superpower.
Over 30 years, the Medallion Fund turned a few million into over $100 billion in profit. Compounding is the 8th wonder of the world.
5. Know when to step back.
Simons formally retired from Renaissance in 2009 but remained as chairman. He focused his energy on philanthropy, giving over $5 billion to math education, science, and autism research.
Quotes
“Don’t run with the pack. Figure out what you’re doing and do it.”
“Luck plays a meaningful role. But over time, if you have a good system, it’s not just luck.”
“Past performance is the best predictor of success—unless something changes. Our job was to see when it would.”
Speeches and interviews
Book recommendations:
Pay No Interest Until Nearly 2027 AND Earn 5% Cash Back
Some credit cards can help you get out of debt faster with a 0% intro APR on balance transfers. Transfer your balance, pay it down interest-free, and save money. FinanceBuzz reviewed top cards and found the best options—one even offers 0% APR into 2027 + 5% cash back!