Olivia
Online
Loran
@0xLoran
quant math, market structure, and the difference between edge and noise
Wall Street
Joined July 2024
38 Following
241 Followers
46 Posts
@VoltexGar new alpha from Voltex! Good job, man!
@velesxbt Interesting post - I'll come back here to check it out!
@Rossst_03 nice job, man!
A billionaire has spent 40 years and a fortune in lawyers trying to erase one hour of film. It shows him turning a crash into $100 million in a single afternoon, a crash he called on camera three months early.
His name is Paul Tudor Jones. The tape survived. It is sitting on YouTube right now, free.
The film is called "Trader." PBS shot it in 1987, three months before Black Monday. Jones is 32, running money out of a cramped New York office in shorts and a t-shirt, screaming into phones, hurling paper across the room, sleeping under his desk. The camera catches him and his partner Peter Borish laying a chart of the 1929 crash over 1987, month by month. The two lines track within one percent. Borish says it is 1929 all over again. Jones says if the pattern holds, it breaks in October.
On October 19, 1987, the Dow dropped 22.6 percent in one day. Still the worst single day in market history. That afternoon Jones covered his shorts and walked away with roughly $100 million. He was 33. Almost no one else on the street came out alive. He printed.
Then he tried to make the tape disappear. It made him look reckless in a world that punished swagger. Twenty years of lawyers could not kill it. Someone kept a copy. Today it has fewer views than a random makeup tutorial.
Here is the part nobody expects. The film is not about a crash. It is about one boring philosophy, repeated until it turns into a reflex. Jones builds conviction slowly, sizes small, waits, then hits hard when the setup finally shows. Not a single random bet in the whole hour. The same motion, five times a day, every day, for three months.
One line he has repeated for 45 years:
"The most important rule of trading is to play great defense, not great offense."
He is not trying to be right. He is trying not to lose. Tight stops, fast cuts, never adding to a loser. Every trade in the film obeys it.
Tudor Investment, the fund he started in 1980, has compounded near 19 percent a year for 45 years. He is 71 and still at the screen. The method has not changed since the tape.
The lesson: greatness in markets is a refusal, not a gift. Refusal to be reckless. Refusal to be certain. Refusal to average down. Refusal to trust yourself mid-drawdown. He has held those refusals for 45 years straight.
The tape is free. The philosophy is in every trade he makes. Most people will still never press play.
A billionaire has spent 40 years and a fortune in lawyers trying to erase one hour of film. It shows him turning a crash into $100 million in a single afternoon, a crash he called on camera three months early.
His name is Paul Tudor Jones. The tape survived. It is sitting on YouTube right now, free.
The film is called "Trader." PBS shot it in 1987, three months before Black Monday. Jones is 32, running money out of a cramped New York office in shorts and a t-shirt, screaming into phones, hurling paper across the room, sleeping under his desk. The camera catches him and his partner Peter Borish laying a chart of the 1929 crash over 1987, month by month. The two lines track within one percent. Borish says it is 1929 all over again. Jones says if the pattern holds, it breaks in October.
On October 19, 1987, the Dow dropped 22.6 percent in one day. Still the worst single day in market history. That afternoon Jones covered his shorts and walked away with roughly $100 million. He was 33. Almost no one else on the street came out alive. He printed.
Then he tried to make the tape disappear. It made him look reckless in a world that punished swagger. Twenty years of lawyers could not kill it. Someone kept a copy. Today it has fewer views than a random makeup tutorial.
Here is the part nobody expects. The film is not about a crash. It is about one boring philosophy, repeated until it turns into a reflex. Jones builds conviction slowly, sizes small, waits, then hits hard when the setup finally shows. Not a single random bet in the whole hour. The same motion, five times a day, every day, for three months.
One line he has repeated for 45 years:
"The most important rule of trading is to play great defense, not great offense."
He is not trying to be right. He is trying not to lose. Tight stops, fast cuts, never adding to a loser. Every trade in the film obeys it.
Tudor Investment, the fund he started in 1980, has compounded near 19 percent a year for 45 years. He is 71 and still at the screen. The method has not changed since the tape.
The lesson: greatness in markets is a refusal, not a gift. Refusal to be reckless. Refusal to be certain. Refusal to average down. Refusal to trust yourself mid-drawdown. He has held those refusals for 45 years straight.
The tape is free. The philosophy is in every trade he makes. Most people will still never press play.
https://t.co/3e7n3vCb0b
@VoltexGar Your work inspires me every time, I never would have thought that milliseconds could be so valuable))
Terence Tao, UCLA professor and the most decorated mathematician alive:
"Hedge funds hand you $750K a year for a single skill: telling a real pattern from noise. I've spent a lifetime on it, and almost everyone has it flipped."
this free lecture is the entire "find the signal" problem those firms are paying for, delivered at UCLA by the most awarded mathematician alive and put online for nothing.
at the chalkboard it's plain. Tao's lifelong idea is that almost nothing is purely one thing. there's flawless structure, like a clock, and flawless randomness, like a coin toss, and nearly everything real sits somewhere between the two. the work is pulling them apart.
the primes are the cleanest test. they look scattered and lawless, yet Tao and Ben Green proved they hold evenly spaced runs of any length you ask for. order was buried inside the apparent chaos the whole time. that's "signal detection" with the marketing stripped off.
he gave this at UCLA and it has stayed free ever since. exactly the point of the article above: the mathematics those firms pay half a million for is public, written down and free to anyone tonight.
the lecture costs nothing and anyone can press play. what no one can sell you is the judgment to tell when a pattern is real and when your own eyes invented it. that judgment is the entire job, and it takes years to earn.
Terence Tao, UCLA professor and the most decorated mathematician alive:
"Hedge funds hand you $750K a year for a single skill: telling a real pattern from noise. I've spent a lifetime on it, and almost everyone has it flipped."
this free lecture is the entire "find the signal" problem those firms are paying for, delivered at UCLA by the most awarded mathematician alive and put online for nothing.
at the chalkboard it's plain. Tao's lifelong idea is that almost nothing is purely one thing. there's flawless structure, like a clock, and flawless randomness, like a coin toss, and nearly everything real sits somewhere between the two. the work is pulling them apart.
the primes are the cleanest test. they look scattered and lawless, yet Tao and Ben Green proved they hold evenly spaced runs of any length you ask for. order was buried inside the apparent chaos the whole time. that's "signal detection" with the marketing stripped off.
he gave this at UCLA and it has stayed free ever since. exactly the point of the article above: the mathematics those firms pay half a million for is public, written down and free to anyone tonight.
the lecture costs nothing and anyone can press play. what no one can sell you is the judgment to tell when a pattern is real and when your own eyes invented it. that judgment is the entire job, and it takes years to earn.
https://t.co/iZLuBLz082
everyone's filming China's "magic AI blackboard" and asking how it works.
my bet: there's a Kimi behind the glass.
same week this video dropped, Kimi K3 became the first open Chinese model to crack the top 3 in the world. 2.8 trillion parameters. 1 million token context. weights public, $3 a million tokens.
the West is still arguing about whether to open-source anything. China put a frontier model on a chalkboard and let a kid ask it questions.
the tool everyone's filming isn't the story. what's writing on the board is.
everyone's filming China's "magic AI blackboard" and asking how it works.
my bet: there's a Kimi behind the glass.
same week this video dropped, Kimi K3 became the first open Chinese model to crack the top 3 in the world. 2.8 trillion parameters. 1 million token context. weights public, $3 a million tokens.
the West is still arguing about whether to open-source anything. China put a frontier model on a chalkboard and let a kid ask it questions.
the tool everyone's filming isn't the story. what's writing on the board is.
https://t.co/mhi1YY7QHj
Yann Dubois, the Stanford researcher:
"Meta just paid $14 billion for Scale AI. not a model. not a chip. a company that labels and cleans data."
that number is the whole lecture in one line.
OpenAI, Google, Anthropic, Meta all train on the same transformer. same open weights, same math. the model is a commodity.
so they fight over the only thing that's scarce. Meta dangled $100M packages to poach researchers and $14B to lock up a data pipeline.
that's the boring 95% nobody posts about, because you can't screenshot a labeling queue.
it's the same reason one AI resolves a prediction market faster than the crowd and another just guesses. not a smarter model. a cleaner feed.
the edge was never the model. it's what you feed it, and Meta just priced it at $14 billion.
Yann Dubois, the Stanford researcher:
"Meta just paid $14 billion for Scale AI. not a model. not a chip. a company that labels and cleans data."
that number is the whole lecture in one line.
OpenAI, Google, Anthropic, Meta all train on the same transformer. same open weights, same math. the model is a commodity.
so they fight over the only thing that's scarce. Meta dangled $100M packages to poach researchers and $14B to lock up a data pipeline.
that's the boring 95% nobody posts about, because you can't screenshot a labeling queue.
it's the same reason one AI resolves a prediction market faster than the crowd and another just guesses. not a smarter model. a cleaner feed.
the edge was never the model. it's what you feed it, and Meta just priced it at $14 billion.
https://t.co/8HHG7saiut
@Rossst_03 $750K - that's a really high salary, but after watching this video, I realize they've earned it honestly.
Daniel Kahneman, Nobel laureate and author of "Thinking, Fast and Slow":
"You have two minds. one is fast, certain, and almost always wrong about money. the other can actually do the math, but it is lazy and shows up late. I won a Nobel proving the casino makes its entire living in the gap between them."
this free talk is the Nobel laureate himself explaining why your gut is the most expensive thing you own, and it has been free for years.
at the board it's simple. Kahneman split thinking into two systems. System 1 is instant, effortless, and wildly overconfident. System 2 can actually compute the odds, but it is slow and hates being used, so it usually just rubber-stamps whatever System 1 already decided. You feel the answer first and invent the reasons after. Every casino, every hot tip, every "act now" is timed to close the trade in that first second, before the part of you that can do math ever wakes up. That's the whole "gut instinct", minus the marketing.
Kahneman spent fifty years proving this and put it in one book in 2011. Same point as my article above: the house does not beat you with better odds, it beats you by reaching your fast mind before your slow one arrives.
the science is free and half the world has read the book. what nobody can sell you is the one-second pause that lets System 2 catch up before you click. That pause is the entire edge, and almost nobody takes it.
Daniel Kahneman, Nobel laureate and author of "Thinking, Fast and Slow":
"You have two minds. one is fast, certain, and almost always wrong about money. the other can actually do the math, but it is lazy and shows up late. I won a Nobel proving the casino makes its entire living in the gap between them."
this free talk is the Nobel laureate himself explaining why your gut is the most expensive thing you own, and it has been free for years.
at the board it's simple. Kahneman split thinking into two systems. System 1 is instant, effortless, and wildly overconfident. System 2 can actually compute the odds, but it is slow and hates being used, so it usually just rubber-stamps whatever System 1 already decided. You feel the answer first and invent the reasons after. Every casino, every hot tip, every "act now" is timed to close the trade in that first second, before the part of you that can do math ever wakes up. That's the whole "gut instinct", minus the marketing.
Kahneman spent fifty years proving this and put it in one book in 2011. Same point as my article above: the house does not beat you with better odds, it beats you by reaching your fast mind before your slow one arrives.
the science is free and half the world has read the book. what nobody can sell you is the one-second pause that lets System 2 catch up before you click. That pause is the entire edge, and almost nobody takes it.
https://t.co/mvYfX85y61
@VoltexGar Dude, this is really powerful, I'm going to sit down and watch it closely.
In 2011 a machine walked onto the most famous quiz show in America and destroyed the two greatest champions who had ever played it. One of them had won seventy four games in a row. He never stood a chance.
Beaten and grinning, that champion wrote a single line under his final answer on live television: "I, for one, welcome our new computer overlords."
The machine was called Watson. The footage is on YouTube.
Jeopardy is not a trivia quiz. It is a language trap. The clues are built out of puns, jokes, hidden references and deliberate misdirection, the exact kind of thing computers had always been hopeless at. Chess is clean and mathematical, and a machine had already conquered it. Human language, full of ambiguity and wordplay, was supposed to be the thing that kept us safe.
IBM spent four years and an enormous amount of money building a machine to break into it anyway. Watson did not think like a person. It had no idea what any word meant. What it had was a vast library of text and the ability to run thousands of interpretations of a clue at once, score how confident it was in each, and answer only when the odds crossed a line. It was not understanding. It was probability at a scale no human brain can reach.
On the night, against Ken Jennings, the greatest human player alive, it was not close. Watson buzzed faster, stayed calmer, and sized its bets with cold arithmetic no nervous champion could match. Jennings lost, laughed, and welcomed the overlords.
This is not really a story about a game show. It is about the same shift my casino piece above describes. For centuries the edge in any hard human contest lived in human intuition, in feel, in years of practice. Watson proved that a machine holding enough data and enough probability can walk into the one arena we were sure was ours and win going away.
It did not need to understand. It only needed better odds, computed faster, bet more coldly. That is the entire game now.
The film is free. The match is on YouTube. Most people still think the parts that make us human are the parts a machine can't reach.
In 2011 a machine walked onto the most famous quiz show in America and destroyed the two greatest champions who had ever played it. One of them had won seventy four games in a row. He never stood a chance.
Beaten and grinning, that champion wrote a single line under his final answer on live television: "I, for one, welcome our new computer overlords."
The machine was called Watson. The footage is on YouTube.
Jeopardy is not a trivia quiz. It is a language trap. The clues are built out of puns, jokes, hidden references and deliberate misdirection, the exact kind of thing computers had always been hopeless at. Chess is clean and mathematical, and a machine had already conquered it. Human language, full of ambiguity and wordplay, was supposed to be the thing that kept us safe.
IBM spent four years and an enormous amount of money building a machine to break into it anyway. Watson did not think like a person. It had no idea what any word meant. What it had was a vast library of text and the ability to run thousands of interpretations of a clue at once, score how confident it was in each, and answer only when the odds crossed a line. It was not understanding. It was probability at a scale no human brain can reach.
On the night, against Ken Jennings, the greatest human player alive, it was not close. Watson buzzed faster, stayed calmer, and sized its bets with cold arithmetic no nervous champion could match. Jennings lost, laughed, and welcomed the overlords.
This is not really a story about a game show. It is about the same shift my casino piece above describes. For centuries the edge in any hard human contest lived in human intuition, in feel, in years of practice. Watson proved that a machine holding enough data and enough probability can walk into the one arena we were sure was ours and win going away.
It did not need to understand. It only needed better odds, computed faster, bet more coldly. That is the entire game now.
The film is free. The match is on YouTube. Most people still think the parts that make us human are the parts a machine can't reach.
https://t.co/mvYfX85y61
@Rossst_03 Richard Feynman - he's truly an extraordinary person. I'm willing to watch his videos over and over again.
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