At 40, Jim Simons left a famed math career to launch the most successful hedge fund ever: Renaissance Tech.
Even though it only won 51% of trades, the fund made 66%/yr for 30yrs (Simons worth = $25B). It's a story of genius, but also of how hard it is to beat markets.
THREAD🧵
1/ The crown jewel of RenTech is The Medallion Fund (launched in 1988).
◻️ From 1988-2018, it posted a return of 66%/yr (39% after fees)
◻️$1 invested in 1988 is now worth $14m+
◻️ Cumulative profit = $100B+ even with an avg. fund size of only $4.5B
2/ Before creating what Bloomberg calls the “greatest money-making machine ever”, Simons was a legendary mathematician.
3/ While at Stony Brook, Simons started trading commodities (with money staked by former MIT classmates).
The side investing was good enough that Simons -- also going through a divorce -- decided to leave academia and launch his own money management firm in 1978: Monemetrics.
4/ At the time, there were 2 main investment approaches:
◻️ Fundamental (understanding and forecasting an asset based on key drivers)
◻️ Technical analysis (studying price charts)
Simons’ strategy was to place a “fundamental lens” on currencies (eg. supply and demand).
5/ While Monemetrics found moderate success, Simons called the emotional swings of day-trading “gut-wrenching”.
He wanted something more systematic and set out to create a 3rd approach: using complex math models to find signals that predicted price movements.
6/ Simons, a former codebreaker, said: "There are patterns in the market, I know we can find them."
The job wasn’t for MBAs. It was for PHDs and scientists.
His first hires were former colleagues from Stony Brook and NSA. In 1982, he renamed the firm Renaissance Technologies.
7/ It took years, but they created a 3-step process to find "statistically significant moneymaking strategies" (AKA signals):
1⃣ Find an anomalous pattern in historic pricing data
2⃣Be statistically significance, non-random and consistent over time
3⃣Be somewhat explainable
8/ These signals were called "tradeable effects". While many are now common in quant funds, RenTech did them first and better:
9/ In 1988, the single trading model -- it would remain *one* model -- officially became The Medallion Fund (named after one of Simon's math awards).
The 1st fund was $20m. Early returns were OK...
1988: +16%
1989: +1%
...but then:
1990: +78%
1991: +54%
1992: +47%
10/ By 1993, Simons stopped accepting outside money to The Medallion Fund.
He also jacked up the fees for investors, including employees.
Basically everyone agreed to the new terms:
11/ At the same time, Simons made personnel moves that would define RenTech for decades.
He hired a number of scientists and PHDs from IBM’s Thomas Watson Research Centre.
Its speech recognition unit yielded RenTech's future Co-CEOs: linguists Rob Mercer and Peter Brown.
12/ As an IBM colleague observed “speech recognition and translation are the intersection of math and computer science.”
Mercer and Brown actually pitched IBM to apply computational stats to manage its $28B pension.
IBM said "no" and they (along with others) joined Simons.
13/ The IBM move opened up the world of tradable assets. To that point, Medallion had notched near all gains on currency/commodity futures.
After bringing in algorithm and coding skills from IBM, it added 1000s of equities to its model, allowing the fund to scale up in size.
14/ The fund never got too big, though.
The short-term nature of its strategies limits how much money can be deployed.
Today, the fund is capped at ~$10B with annual profit distributions to partners (now restricted to its 300+ employees...1/3rd are PHDs).
15/ The capped fund size and the fact that the money barely compounds makes the total cash generated — $100B+ profits — all the more remarkable.
Net of its massive 5/44 fees, the 1988-2018 annualized return for Medallion is a crazy 39% (vs. crazier gross return of 66%).
16/ Interestingly, the Fund only won 50.75% of its trades.
An army of top PHDs are basically a coin flip. Markets are hard AF (most should buy and hold).
Per Mercer: “We’re right 50.75% of the time . . . but we’re 100% right 50.75% of the time. You can make billions that way.”
17/ How was The Medallion Fund able to pull it off?
Let's break down 9 reasons:
◻️ Simons the manager
◻️ Culture for top talent
◻️ Never override the computer
◻️ Data edge
◻️ Great execution
◻️ “Don’t ask why”
◻️ Stealth trading
◻️ Extreme diversification
◻️ Leverage
18/ SIMONS THE MANAGER
From his Stony Brook U. days, Simons has long experience managing intellectual egos.
His academic credentials and trading chops earn universal respect.
Per Bloomberg: Simons is the “benevolent father figure” that inspired “super nerds to stick together.”
19/ CULTURE FOR TOP TALENT
A big part of Simons' job was creating a place for top scientists to want to work:
20/ NEVER OVERRIDE THE COMPUTER
The driving logic behind RenTech was to create a systematic trading approach that wouldn't be compromised by human emotion.
Medallion performs best during volatile times...because it lets the model run while everyone else is losing their minds.
21/ DATA EDGE
RenTech’s unofficial motto is “There’s no data like more data.”
Earlier than most, the fund gathered data of all sorts (weather, prices, newspaper blurbs) for its model.
Today, its system ingests 1 terabyte of data a year to improve the trading model.
22/ GREAT EXECUTION
RenTech does 150k-300k small trades a day and holding periods are very short (~2 days).
A key part of the trading model is estimating the exact bet size so as to not adversely impact the trade (RenTech's term for transaction costs is “slippage”).
23/ "DON'T ASK WHY"
RenTech believes that market participants vastly underestimate how many variables drive an asset.
The team rarely offers up hypotheses. Instead, they let the data speak and if a signal works -- even if they don't fully understand why -- they will trade it.
24/ STEALTH TRADING
When RenTech finds a market inefficiency, it goes to great lengths as to not give away the trade:
25/ EXTREME DIVERSIFICATION
The move into equities allowed RenTech to trade many more assets (and deploy up to $10B/yr).
At any one time, The Medallion Fund can have 4k long and 4k short trades.
Such a diversified portfolio reduces overall risk, giving RenTech access to...
26/ LEVERAGE
Having built a trading machine on great data and execution combined with diversification, banks (Deutsche, Barclays) are happy to lend RenTech money.
Medallion typically levers 12.5x (and can get up to 20x). Without leverage, its returns are comparable to S&P 500.
27/ Add it all up and the Medallion Fund's returns (1988-2018) are absurd:
◻️ Since 1990, its *worst* year is +32%
◻️ In 24 of the 31 years, it's up at least 50%
◻️ It has three 100%+ return years, all in the worst market conditions: 2000 (+128%), 2007 (+137%) and 2008 (+152%)
28/ In 2005, RenTech booted outsiders from Medallion and launched 3 public funds (RIEF, RIDE, RIDGE) with different strategies.
It once managed $55B+ of public money but after 2020 (worst returns across all 3), $10B+ has been pulled.
Medallion was fine, though (+76% in 2020).
29/ Simons officially retired from RenTech in 2009.
A lifelong Democrat, he had to deal with controversy around Robert Mercer: one of Donald Trump's top donors in 2016.
Mercer stepped down from Renaissance Technologies in 2017 over his politics (Peter Brown remains CEO).
30/ Today, Simons (and his wife Marilyn) are focussed primarily on philanthropy.
Through their Flatiron Institute, he's donating billions to scientific research...in the search for signals, specifically for astrophysics, biology and quantum physics.
31/ For all his success, Simons says "luck plays quite a role in life". He's dealt with very bad personal luck: losing two sons.
Taken all together, Simons laid out his life principles during a 2014 lecture at SF University:
32/ For other threads like that, def smash the FOLLOW on @TrungTPhan.
Here's one I did after interviewing Stanley Druckenmiller:
35/ Of all the Jim Simons videos, fave part was when MIT professor Andrew Lo asked him if his ringing cell phone was a “margin call”.
36/ Renaissance Technologies has generated $100B+ in profits since 1988.
It has spent $0 on its website, with
the worst-looking landing page ever for a company with the word “Technologies” in its name:
37/ Three more nuggets from Simons story:
◻️ Fired from NSA/IDA for telling Newsweek his opposition to the Vietnam War
◻️ Found the Chern–Simons form, a theory widely used in quantum computing
◻️ A chainsmoker who can pay "whatever the fine is" for smoking in his own buildings
38/ UPDATE: Jim Simons and other RenTech execs agree to pay $7B in back taxes related to accounting of options trades:
This timelapse of Alex Honnold’s 1 hour 35 minute free solo climb of Taipei 101 is unreal.
He said the main challenge was “not getting complacent up the bamboo boxes, because it’s 64 of the same sequence over and over.”
His music playlist (mostly Tool) helped because each bamboo box took about the length of a song and he could keep pace.
Honnold wants to climb other mega skyscrapers if allowed.
Thinks Taipei 101 was the ideal challenge, though: “This one is so perfect for climbing. There are some buildings that are almost too easy for climbing. Like, ones that have a window washing track on the outside, where you’re just hand over handing on some track the whole way. You can climb it, but it’s not a challenge. The thing about Taipei 101 is it’s perfectly in the sweet spot for me, where it’s possible, and it’s not too insanely hard.”
“The dragons, they’re also probably the scariest thing to actually do. I mean, they’re really fun, they’re really cool. It’s an incredible sequence, cool position. But every time I set up on the dragon, I’d be like, “this is kind of crazy.” You’re like, out over the abyss. It’s cool.”
Matt Damon and Ben Affleck on Rogan taking about how Netflix has changed filmmaking.
A major considerations is dealing with distracted viewers. To keep them tuned in, “you re-iterate the plot 3-4x in the dialogue because people are on their phones.”
Then, in action films, you change the ordering of climatic fights.
In traditional action films, you’d have “three set pieces” in every act (I, II, III) and each would “ramp up” (spend the big money on third set piece).
But streaming has to hook viewers within 5 minute, so the incentive is to put a major battle or action sequence much earlier.
Also, the directors have less incentive to make a film look great because so many people watch on laptops and phones.
They do say that streaming allows for more bets on risky projects since the theatre economics are geared towards IP, sequels and super-heroes.
Example: an independent film with a $25m budget would spend $25m on marketing (1:1 ratio). But since it splits box office with the theatre, the film needs to make $100m (1/2 of which is $50m) just to break even.
They’re realistic about the state of film and call it a supply-demand issue. If the demand is for at-home viewing (eg. Netflix 300m+ subs), then filmmaking approach will change to feed the algo.
When there’s demand for theatre, Damon will go team up with Christopher Nolan to make “The Odyssey”.
A similar dynamic is happening to streaming TV shows. The incentives for story arc, dialogue and character types warped thr medium.
The Economist has a great piece on strategy sportsbetting apps use to throttle smart bettors:
▫️Skilled players are “sharps” and given “stake restrictions” if they play too well (bets are capped).
▫️Rest of players called “Square”.
▫️In 2025, 4.3% of active UK accounts had a “stake factor” below the maximum bet allowance of 100%.
▫️Sportsbook will take bets with a profit margin as low as 4.5%.
▫️If they are able to do good “player-profiling” and keep the “sharps” from playing, the profit margin can reach 10-20%.
▫️As important as keeping out “sharps” is hooking “whales”, the deep-pocketed players that are willing to keep playing (and losing) large sums.
▫️Some “whales” are actually “sharps” in disguise, though. They’ll lose a bunch of bets to lull the sportsbook then put down a massive bet when they have an edge.
▫️While there is a risk of a “whale” being a “sharp”, the value of a real “whale” is so high that sportsbook will take the risk
▫️“In March 2024 PointsBet, raised its share of online sports-gambling revenue in New Jersey from 11% to 24% after wooing a single cash-spouting customer away from DraftKings.” (I can confirm that this wasn’t me).
▫️How sportsbook profile players:
> Playing on Mobile is a good sign (where majority of people play)
> Playing on PCs is a bad sign (it’s easier to compare odds and run models)
> E-wallets are a red flag (sportsbooks prefer debit direct deposit that can attach a player to a single account; e-wallet is more anonymized and players can move cash between sportsbook more quickly to shop for the best odds)
> Women bettors are a red flag (most bettors are men and “sharps” often use women to place bets)
▫️First wagers are a major tells (typical bettors go after top leagues — NFL, NBA, EPL — and do so near the start of the game).
▫️Popular bets for “squares”: who will win, scoring margins and how star player will perform (also, they love multi-leg parlays).
▫️“Sharps” go after less popular leagues and place bets as soon as odds are published, when they are most mispriced. They also go after less popular bets such as “pts in Q3” or stats from a random player (“Sharps” rarely do parlays and don’t withdrawal winnings often).
▫️One gambling consultant tells The Economist that “By the time a customer places his first bet, [sportsbooks] are 80-90% certain they know the lifetime value of the account.”
▫️”Sportsbooks look at a player’s ‘closing-line value’ — a measure that compares the odds at which he bets with those available right before a match begins. If it is consistently ahead of the market over his first ten wagers, he is highly likely to beat the book in the long run.”
▫️Sportsbook mathematically monitor players and creates a new risk score every 6-8 hours (risk score = estimate of probability that customers will wind up unprofitable).
▫️E-wallet users, women and bets over $100 are flagged. These suspicious bettors are given 30% of maximum bet (and proven sharps only allowed 1%).
▫️High-skilled players will often get a “beard” to bet on their behalf. Most sportsbooks ban this practice but it is widespread.
▫️Safest “beards” are close friends and relatives because you can mostly rely on them to pay out any winnings. The “beards” try to look like degens (playing at 3am, bet non-stop and doing ridiculous parlays) before placing a winning bet.
▫️The most effective strategy for “sharps” is “whale-flipping”. Find a losing gambler, then ask to put a (likely) large winning bet amongst their pool of guaranteed losers.
▫️Once “sharps” max out the people they can use as “beards”, they tap professional networks called “movers”. These “movers” employ a bunch of “mules” who can put down bets on the behalf of the network. Low-end movers charge 10-20% while high-end movers charge 50% of winnings.
On a related note, I wrote on how slot machines make $10B+ a year in Las Vegas (~70% of all casino gaming revenue).
The history, psychology and design of the device…which went from a throwaway game to the industry’s “cash cow” and “gambling’s crack cocaine.”readtrung.com/p/the-ludicrou…
Satya Nadella on why Microsoft Excel has been so durable after 40 years:
> the power of lists and tables
> the malleability of the software (“a blinking canvas”)
> spreadsheet software is Turing complete (“I can make it do everything”)
> it’s the world’s most approachable programming environment (“you get into it without even thinking your programming”)
The invention of bánh mì is a combination of climate, trade and urban layout of Saigon in late-19th century designed by French colonist.
When the French captured the area in 1859, most economic activity in the region took place along the Saigon river.
The population built makeshift homes tightly bundled by the river banks. Outgrowth from this eventually lead to narrow alleyways between many buildings that is trademark of the city (the Khmer named the region Prey Nokor then French renamed it Saigon and then it was renamed to Ho Chi Minh City in 1976 after end of Vietnam War).
Over decades, the French created European street grids and built wide Paris-type boulevards in the city to funnel commerce to larger markets (also make the city easier to administer).
It was at these markets that French baguettes were introduced and traded.
Bánh mì bread is known for being flaky and crispy on the outside while fluffier on inside (so god damn good).
Two features of Saigon helped create this texture:
▫️Climate: The heat and humidity in Southeast Asia leads dough to ferment faster, which creates air pockets in bread (light and fluffy).
▫️Ingredient: Wide availability of rice meant locals added rice flour to wheat flour imports (which were quite expensive). Rice flour is more resistant to moisture and creates a drier, crispier crust.
Fast forward to the 1930s: the French-designed street layout is largely complete. Now, the city centre has wide boulevards intersected by countless narrow alleyways.
The design was ideal for street vendor carts. These businesses were inspired by shophosue of colonial architecture to sell all types of goods as chaotic traffic rushed by.
Vietnam has some of the most slapping rice and soup dishes, but many people on the move in the mornings wanted something more portable and edible by hand.
Bánh mì was traditionally upper class fare but it met the need for on-the-go food.
Just fill the bread with some Vietnamese ingredients (braised pork, pickled vegetable, Vietnamese coriander, chilies) along with French goodies (pate).
Pair it with cà phê sữa đá (aka coffee with condensed milk aka caffeinated crack) and you’re laughing.
Haven’t lived in Saigon for 10+ years but ate a banh mi every other day when I did.
While there, I also sold a comedy script to Fox (pitch: “The Fugitive meets Harold & Kumar set in Southeast Asia”).