quantfold @quant_fold
Quant trader · Wall Street alpha through mathematics New York Joined July 2026-
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Andrew W. Lo: one MIT professor, two proofs. 1988: the market can be beaten. 2007: every winning strategy gets eaten by the crowd. In 1988, Lo and A. Craig MacKinlay published a paper with a title that read like a dare: “Stock Market Prices Do Not Follow Random Walks.” They tested weekly returns from 1962 to 1985. The random walk model was strongly rejected for the whole sample and for every subperiod. A decade later, in 1999, he turned the argument into a book, “A Non-Random Walk Down Wall Street,” and founded AlphaSimplex Group, a quant fund he chaired until 2018. Then came August 2007. During the week of August 6, a group of highly successful quantitative equity funds lost money at a speed nobody had seen. Most of the damage came on August 7, 8 and 9. On the 10th it partly reversed. Goldman’s Global Equity Opportunities fund lost more than 30% in a week. A $1.8 billion New York quant firm lost about 20% in its biggest fund. Goldman’s CFO explained it on August 13: “We were seeing things that were 25-standard deviation moves, several days in a row.” Two Goldman funds each lost over a quarter of their value, and the bank put in about $3 billion. Lo went back to the data. His answer, called the unwind hypothesis, had no villain. Many funds held portfolios built the same way. When one de-levered, prices moved against all the others. Their losses forced them to sell too, which pushed prices further, which forced more selling. Nobody’s model was wrong in isolation. The edge was real. It was shared. That is what an edge does. It exists because the market is not random, and it expires because other people find it. Every bot, every fund, every strategy starts that clock the day it works. Speed is necessary, never sufficient. What survives is a hard risk layer that never negotiates, and an honest backtest that does not assume you are the only one who found the trade. Before you deploy the next strategy, ask one question: if ten more people have this exact trade, what happens when we all exit through the same door?
Most on-chain bots lose by being fast but wrong. The winners do three things before the block closes: detect, simulate, include. In this article I show EXACTLY how to build an on-chain HFT bot that trades every block, from scratch. x.com/i/article/2107…
Ray Dalio, 1982: one bet, one employee left. He went on to build the world's largest hedge fund. What did he change? In 1982, Dalio was 33 and ran Bridgewater, a small firm he had started in his apartment. He had studied debt cycles harder than almost anyone. He saw a crisis coming, and he was right: the debt crisis of emerging markets was real and it arrived. Then he made the call that mattered. He concluded that the whole U.S. economy was heading into a depression, and he bet nearly everything on it, publicly. The depression never came. Stocks started a bull run. The next 18 years became one of the longest stretches of non-inflationary growth in American history. The bet failed. Dalio lost almost all of his own money and most of his clients' money. He could no longer pay the people who worked for him, so he let them all go, one by one, until Bridgewater had a single employee: Dalio himself. To cover his family's bills, he borrowed $4,000 from his father. Run his career through the formula: his skill was real. His multiplier, one bet with almost all the capital, was too big. And time was against him, because the market did not move on his schedule. One term close to zero, and the product collapsed with it. Later he said going broke was the best thing that ever happened to him. It changed his question. Before 1982 he asked, "am I right?" After it, he asked, "how do I know I'm not wrong?" That second question became the foundation of how he built Bridgewater: write down decisions, test them against opposing views, and spread bets across many things that do not move together. He had the skill early. What he did not have was a way to survive being wrong. The three terms multiply. Skill gets you into the game. Leverage multiplies what you bring. Time decides whether you are still there when the market finally agrees with you. Before your next big bet, ask one question: if I am right but early, can I survive long enough to collect?
Larry Fink, 1986: lost $100 million in one quarter. Two years later he started BlackRock. What did he see that the bank didn't? Fink joined First Boston at 23, straight out of graduate school. By 27 he was the youngest managing director in the firm's history. By 31 he sat on its executive committee and ran one of the most profitable departments on Wall Street, trading mortgage-backed securities when almost nobody understood them. His team was making more money than anyone had imagined. Fink later described it in his own words: "We were children in a candy shop." The problem was that nobody could see how much risk it took to earn that money. The bank had no tools to measure it. Fink says today that his team "probably should have been fired for making too much money," because the profit hid exposure that nobody understood, including him. The bank's answer to the profit was to give him more capital. Then came the second quarter of 1986. After a record first quarter, his department lost about $100 million. When the profits stopped, so did the partnership. Fink says that when the team made money, everyone was a partner, and when it lost, there was no support from above. He left the firm. He says he never forgave himself. He did not go back to another trading desk. He spent nearly two years thinking about what had gone wrong, and the answer was not a better trade. It was a better way to see risk. If investors could measure what they were exposed to before the loss, not after, a different kind of firm was possible. In 1988 he started BlackRock, built around risk analytics. Its system, Aladdin, was designed to show a portfolio's exposure in real time. The loss that ended his career at First Boston became the foundation of the firm that now manages trillions of dollars. In his own words: "The ashes of my failure at First Boston was a fertilizer of the beginnings of BlackRock." Every big decision needs two numbers: what you could make, and what you could lose. Fink had the first one for years. He built a company after learning what happens when you do not have the second. Before your next trade, ask one question: can I measure what I could lose, or only what I could win?
@mrcsxbt That $650k bid was genuinely cheap if you calculate the lifetime value of mentorship from someone running a $600b portfolio
@0x_Ito buffett point about ford assembly line wages hits different when you realize ceos actually got better outcomes after failure than workers did during it
@0x_Ito the real test isn't the math, it's whether you can actually hold when your portfolio is down that much without checking it every day
Charlie Munger, 1975: +73.2% in a single year. His investors were still down 19%. Here is the arithmetic nobody explains. In 1962, Munger left law to run an investment partnership, Wheeler, Munger & Co. For its first eleven years it did what almost no fund does. It beat the market by a wide margin and kept doing it. By 1975 the record read 19.8% a year, against 5.0% for the Dow. Most managers would have framed it. But Munger did not diversify the way his peers did. At the end of 1974, two stocks made up 84% of his portfolio: Blue Chip Stamps at 61% and New America Fund at 23%. He had found businesses he understood and he had bet on them. That is also where the problem began. Then 1973 arrived. The fund fell 31.9%. In 1974 it fell another 31.5%. A $1,000 investment on January 1, 1973 was worth $467 two years later. Blue Chip Stamps, the company that would soon lead to See's Candies, was falling with the rest of the market. Here is what the number hides. When you lose 53%, a gain of 53% does not bring you back. You need 100%. The loss is easy to cause and slow to repair. In 1975 the fund rose 73.2%. It was the kind of year most managers never see in a career. $467 times 1.732 is about $808. Every investor who stayed was still down 19%, after the best year of the decade. Munger shut the partnership down that year. He went on to become Berkshire's vice chairman and one of the most quoted investors alive. But the lesson in his record is not that concentration works. It is what concentration costs when you are early or wrong for a while: two years, more than half your capital, and a recovery that still leaves everyone short. Every principle in a list of billionaire rules has a hidden condition attached. How much control do you have? What are you waiting for? How long can you afford to be wrong? Before copying one, finish a sentence: this makes sense for me because I can survive being wrong for this long. If you cannot finish it, the rule was never yours to borrow.
Warren Buffett's partner compounded at 32.9% a year over 18 years. In 1974, he sold Berkshire at $40 a share. The market didn't beat him. Who did? His name was Rick Guerin. In the early 1970s he, Buffett and Charlie Munger were a three-man club. Guerin brought them the idea of Blue Chip Stamps, the company whose float paid for See's Candies. His own fund put in $2 million of the roughly $24 million that bought 60% control. In his 1984 Columbia speech, Buffett put Guerin's fund, Pacific Partners, among nine record-beating funds he called Superinvestors. From 1965 to 1983, it returned 32.9% a year, against 7.8% for the S&P 500. On paper, he was ahead of Buffett's own partnership, which Buffett listed at 29.5%. But Guerin wanted to compound faster. He bought stocks with borrowed money. Then came 1973 and 1974. The S&P 500 fell roughly 48% peak to trough, and his lenders demanded cash. It no longer mattered whether the businesses would recover. His debt had its own deadline. His Berkshire stock was the only liquid asset left, and he sold it to Buffett for less than $40 a share. The pain was not his alone. Munger's own partnership fell about 53% over those same two years. The difference was who could force a sale. Decades later, one Class A share passed $700,000. Mohnish Pabrai and Guy Spier paid $650,100 at a charity auction for lunch with Buffett. Pabrai asked what happened to Guerin. Buffett said: "Charlie and I always knew we were going to be rich, but we were not in a hurry. And Rick was in a hurry." Leverage did not make Guerin's investments bad. It took away the one thing compounding requires: the ability to wait. Buffett and Munger decided when to sell. Guerin's lenders decided for him. Every principle in that list assumes you are still in the game to use it. Before any leveraged trade, ask one question: if the price falls first, who controls the sell button, you or your lender?
@0x_Ito bezos had the luxury of control and a public market that couldn't force him out. most founders get crushed before they get ten years to prove it.
Franklin D. Roosevelt, 1933, 1 million homes saved - the government rewired the mortgage itself, and buried inside the new math was a trick almost nobody still knows how to use. Before 1933, a mortgage looked nothing like it does now. You put down half the price in cash. You paid interest only for about five years. Then the entire principal came due in a single payment, and you rolled it into a new loan and did it again. It worked as long as banks kept rolling. In the early thirties they stopped, and people who had paid on time for years lost their houses anyway. Roosevelt signed the Home Owners' Loan Act on June 13, 1933. It created the Home Owners' Loan Corporation, and HOLC didn't hand out charity. It bought defaulted mortgages from lenders and reissued them in a completely different shape: one fixed payment a month, every month, for the life of the loan, covering interest and principal together. No balloon. No renewal. By 1935 it had rewritten slightly more than a million of them. The rule underneath it is one line. Each month's interest is your remaining balance times the annual rate, divided by twelve. Whatever is left of the payment goes to principal. Take a $300,000 loan at 6.5 percent over 30 years. The payment is $1,896. Month one, the balance is still the full $300,000, so interest is $300,000 times 0.065 divided by 12 - $1,625. Principal: $271. You aren't being cheated. You're paying rent on money you still fully owe. Run it forward and the shape becomes visible. After ten years you've paid about $182,000 in interest and cut the balance by only $45,672 - about 15 percent, not a third. Half the balance isn't gone until month 257, past the twenty-one-year mark. Over the full term the interest totals $382,633 on a $300,000 loan. But the same rule that makes the first decade heavy hands you the lever against it: interest is only ever charged on what's left, so anything you cut off the balance early removes interest from every month after it. An extra $200 a month against principal ends that same loan in 23 years instead of 30 and removes $103,449 of interest from the total. Balance times rate divided by twelve is this month's interest. What's left is what you actually bought. The formula was built in 1933 to save a million homes - ninety years later almost nobody reads it as a lever, only as a bill.
@0x_Ito the fire phone bit reframes everything. bezos wasn't learning to trust his gut after a massive failure, he was learning to structure bets so his judgment mattering less actually became the point
Anne Mulcahy, Xerox, 2001, $19 billion in debt: advisers told her to file bankruptcy. She said no. What did she do instead? She had spent twenty-eight years inside Xerox with no MBA, starting in sales and working her way up through corporate staff roles, human resources, and operations, long before anyone considered her a candidate to run the company. In 2000, Xerox disclosed that accounting irregularities at its Mexican subsidiary had led to improperly recognized revenue, and the SEC opened a formal investigation that would eventually force Xerox to restate more than $6 billion in revenue across several years. The stock, which had hit $63.69 in the spring of 1999, collapsed to $4.63 by the end of 2000. The company was carrying roughly $19 billion in debt, had lost access to the commercial paper market entirely, and its own auditors were being sued by the SEC. In August 2001, the board made Mulcahy CEO in the middle of all of it. Her own financial advisers told her bankruptcy protection was the responsible move, the clean way to restructure the debt. She refused. A Chapter 11 filing would have meant watching Xerox's enterprise customers, the companies leasing its copiers and printers on multi-year service contracts, quietly walk to competitors rather than stay with a vendor in bankruptcy court. For Xerox's business model, bankruptcy wasn't a reset button. It was closer to a death sentence dressed up as a legal process. So she went bank by bank instead. With commercial paper gone, Xerox was entirely dependent on a $7 billion revolving credit facility held by a syndicate of 58 banks. The terms required every single lender to agree to renew the facility within a rolling 24-month window, or the line died and Xerox defaulted immediately, with no filing needed to trigger it. She personally sat across from representatives of all 58 banks, repeatedly, walking them through the numbers herself rather than delegating it to the CFO. At the same time, she cut costs by roughly $1.7 billion, laid off close to a quarter of the workforce, and sold off businesses including Xerox's stake in Fuji Xerox's China operations and its ContentGuard patents, raising cash without touching the core copier and printing business that still generated the company's revenue. Not one of the 58 banks refused to renew. Over the following several years, the $19 billion in debt was cut roughly in half. The stock, left for dead under $5, recovered many times over through the following decade. Mulcahy ran Xerox until 2009, stepping down as one of the most consistently cited corporate turnaround stories of the 2000s, and handed the company to Ursula Burns, making Xerox the first Fortune 500 company to pass its CEO role from one woman directly to another. She didn't defeat $19 billion in debt. She defeated it 58 signatures at a time.
Warren Buffett, Omaha, 2008, down 50%: Berkshire's stock got cut in half, and he still called the traders panicking around him the real risk. What was he actually afraid of? By September 2008, Lehman Brothers had collapsed, AIG needed a government bailout to survive the week, and credit markets had effectively frozen. Hedge funds were facing redemptions they couldn't meet, forced to sell good assets at terrible prices just to raise cash fast enough. Nobody was asking whether the market would keep falling. Everyone was asking how much further, and who would run out of cash first. Berkshire Hathaway's own stock dropped right alongside everything else, roughly 54% peak to trough, from about $151,650 a share in December 2007 to around $70,050 by March 2009. On paper, Buffett was losing exactly like everyone else. But Berkshire had no debt forcing a sale, no margin calls, no investors who could pull their money on a bad month. The insurance float that funds Berkshire's investments doesn't get redeemed in a panic. That single structural difference meant the 54% drop was a number on a screen, not a forced decision. Buffett didn't sell. He didn't deleverage, because there was no leverage to unwind in the first place. In October 2008, with the market still falling and most of Wall Street frozen, he published an op-ed in The New York Times with the headline "Buy American. I Am." He put $5 billion into Goldman Sachs preferred stock at a 10% dividend, with warrants attached. He put $3 billion into General Electric on nearly identical terms. Both deals were only possible because everyone else needed cash immediately that week, and he was one of the only buyers left standing who didn't. The Goldman warrants alone were worth billions more by the time Berkshire exercised and sold them years later. Buffett's own rule, the one he's repeated in some form since the 1980s, is just two lines: never lose money, and never forget the first rule. Critics have pointed out that Berkshire's stock has fallen hard more than once, in 1974, in 2000, in 2008 itself. The rule was never about the stock price holding steady. It was about never being structurally forced to sell at the bottom, the exact failure that took down Long-Term Capital Management a decade earlier, when 25-to-1 leverage turned a real edge into a forced liquidation during the 1998 Russian default. The stock that had been cut in half went on to compound for another decade and a half after 2009, and Buffett was still running Berkshire into his nineties, the same patient structure intact the whole way through. He never defined risk as the price falling. He defined it as being forced to sell when every correlation breaks at once.
@0x_Ito the real skill wasn't picking winners. buffett and munger had better returns per dollar because they could afford to ignore the margin calls and stay in the game
Harry Markowitz, Chicago, 1952, age 25: a paper so overlooked it sat unread for years - until it rewrote every portfolio on Wall Street. What did everyone miss? He wasn't a finance guy. He was a University of Chicago economics grad student who'd been reading about stock valuation and noticed a gap nobody had bothered to close: everyone talked about maximizing expected return, but almost no one had a rigorous way to price the risk you were taking to get there. He borrowed the math from operations research - the same world of linear programming he was studying under George Dantzig at RAND Corporation - and turned it on a problem nobody thought needed formalizing. His paper, "Portfolio Selection," ran in The Journal of Finance in 1952. Fourteen pages. A few years later, at his PhD defense, Milton Friedman reportedly told him the work was elegant but wasn't economics at all - it was somewhere between math and an accounting identity. The idea itself: mean-variance optimization. Don't just pick assets with the best individual returns - measure how they move relative to each other. If two assets don't move in sync, combining them can lower the portfolio's overall risk without lowering its expected return at all. Plot every possible combination and you get what he called the efficient frontier: the best return available for any given level of risk, and nothing on that curve is a mistake. Everything off it, is. Wall Street had no real use for it for decades. Diversification existed as folk wisdom - "don't put all your eggs in one basket" - but nobody had reduced it to a formula a fund could actually run. Then in 1990, thirty-eight years after that first paper, Markowitz shared the Nobel Prize in Economics with Merton Miller and William Sharpe, the man who'd go on to build CAPM directly on top of Markowitz's framework. He kept working for another thirty-three years after that. He died in 2023, at 95, having lived long enough to watch mean-variance optimization become the default setting inside nearly every retirement account, pension fund, and robo-advisor on earth. Benter counted one bet at a time. Markowitz counted an entire portfolio at once - and it took the market almost four decades to understand why that was the harder, better problem to solve.
In 1986 a guy got kicked out of every casino in Vegas for counting cards. So he flew to Hong Kong with $180,000 and started betting on horses instead. He walked away with almost $900 million. It's Bill Benter. He figured horse racing was just another counting problem. Same math,
Matt Abrahams, one Stanford lecture filmed in 2014, quietly outperformed every $2,000-a-session speaking coach on the planet - and it's still free. He teaches strategic communication at Stanford's Graduate School of Business, and every year during Alumni Weekend he gives some version of the same lecture on speaking under pressure, without a script, in the moment someone puts you on the spot. In 2014, someone filmed it and put it on YouTube. It never came down. His entire method fits on one napkin, the same way the actual math behind your finances fits on one napkin. Don't try to sound impressive when you're caught off guard, dare to be dull instead. Treat whatever you're asked as an offer to build on, not a threat to defend against. When your mind goes blank, use one of two structures: what happened, so what does it mean, now what should we do about it, or for a pitch, the problem, the solution, the benefit. That's it. No script, no forty-five minute answer, no elaborate framework. Just enough structure to survive the ten seconds where most people either freeze or start rambling. Founders spend tens of thousands of dollars on pitch coaches and still blank the moment an investor asks one real follow-up question that wasn't in the deck. Employees rehearse every accomplishment before a review and go silent on the one behavioral question that actually decides the promotion. The skill that decides the outcome isn't on the slide. It's the ninety seconds of unscripted speaking that happens after the slide. The lecture is still free on Stanford's channel. Abrahams still teaches the same course. Fifty-four million views in, most people who watched it have never once used the framework the next time someone actually put them on the spot. Knowing the equations that run your money and knowing the structure that runs your next hard conversation are the same kind of free. Almost nobody treats either one like it's worth using.
Tony Robbins, 1987, $100 million by lunch - that's what his own trading client made, while the rest of Wall Street spent that same day watching in real time as accounts built over years went to zero. By the time of the October 1987 crash, the worst single-day drop in stock market history, Jones was already one of Robbins' clients. He shorted into the chaos and came out the other side having roughly tripled his money while the rest of Wall Street was wiped out. Then, years later, he went cold. Same brain. Same data. Same models he'd used to call the biggest crash of his career. He started losing money month after month and couldn't explain why no matter how many times he reran the numbers. Robbins flew out and just watched him trade for a full day. Shoulders down, breathing shallow, slumped in his chair the entire session. Then he pulled up old footage of Jones at his peak - standing, moving, voice raised, commanding the room like he owned it. He sat Jones down and played both tapes side by side. Jones watched himself twice and said it looked like two different people. Robbins told him the fix wasn't a new strategy. It was a new posture. He changed how Jones stood at his desk, how he breathed between trades, how he used his voice on the phone. The performance came back before the strategy ever changed. Robbins has said the body decides first, and the mind just follows along afterward. Change the physiology and the decision changes with it. Most people check their portfolio the same way they check everything else at the end of a long day: slumped on a couch, phone low, shoulders caved in.
Jim Chanos, January 2001. Wall Street analysts told him, word for word, that Enron was "a black box nobody can actually analyze." They kept telling clients to buy it anyway. Eleven months later, $74 billion was gone. Chanos wasn't inside Enron and he wasn't a regulator. He ran a short-selling fund called Kynikos Associates - Greek for "cynic," which turned out to be the right name for the job. In late 2000, he read a Wall Street Journal article about an accounting method called "gain-on-sale" - companies booking today's profit off trades that hadn't actually paid out yet. He pulled Enron's own 1999 annual report and ran one calculation: return on capital versus cost of capital. Enron's return on capital came out to about 7% before taxes. His estimate of what it cost Enron to raise that capital: roughly 9%. The company was destroying value on every deal it signed, while reporting record profits. He opened a short position in November 2000. Two months later, he sat down with the analysts who covered the stock and asked them to walk him through it. Their answer wasn't reassurance. It was a shrug: nobody could actually verify Enron's numbers, they said - it was a "trust me" story. They kept their buy ratings. He wasn't the only one who noticed. In March 2001, journalist Bethany McLean published a Fortune article asking one plain question: how exactly does Enron make its money? Enron's own executives couldn't answer it without getting angry. CFO Andrew Fastow snapped that Enron was "not a trading company." CEO Jeff Skilling dismissed her, saying she hadn't "gone through the business in detail." Neither of them actually explained the number. The warning signs kept stacking after that. Cryptic related-party transactions buried in filings. Heavy insider selling by executives. Then, in August 2001, Skilling resigned without real explanation - Chanos later called it the most ominous signal yet. On December 2, 2001, Enron filed for bankruptcy - the largest corporate collapse in U.S. history at the time. The stock that once traded above $90 closed at $0.61 before the filing. Shareholders lost roughly $74 billion, with $40-45 billion of that tied directly to the fraud. Chanos later testified before Congress about exactly how he'd seen it coming. Nobody needed inside information to catch it. The math was sitting in a public filing a full year before the collapse. The only thing standing between that number and everyone else was whether anyone bothered to check it.
Harry Markopolos, 2005, sent U.S. regulators a report titled "The World's Largest Hedge Fund is a Fraud." It named Bernie Madoff directly. It sat ignored for three more years while $65 billion disappeared. Verifying who actually custodies your money sounds like the boring, tedious check nobody bothers with - right up until it's the only thing that would have mattered. Markopolos wasn't an investigator. In 1999 he was a portfolio manager at a rival firm, asked by a colleague to reverse-engineer Madoff's options strategy so they could compete with it. He opened the numbers expecting to learn something. Instead, within about five minutes he suspected fraud, and within roughly four hours of mathematical modeling he had proof: the returns weren't just unlikely, they were structurally impossible for the strategy Madoff claimed to run. His own description of the red flag: "His performance line went up at a 45 degree angle. It would be like a baseball player with a .964 batting average." No real strategy produces a line that straight. Markets don't move that smoothly, not for one year, let alone the fifteen Madoff claimed. He filed at least five formal submissions to the SEC between 2000 and 2008, with detailed, documented cases in 2000, 2001, and 2005 - that last one spelling the fraud out directly in the title so there was no ambiguity left to hide behind. Each time, the case was reviewed briefly and set aside. It wasn't only professional risk. Markopolos came to believe some of the money running through Madoff's feeder funds belonged to Russian and Colombian criminal networks - money that doesn't forgive being stolen quietly. He bought a gun and started checking his car for bombs before he left for work. Madoff's fraud finally collapsed in December 2008 - not because regulators caught it, but because he ran out of new money to pay old investors and confessed to his own sons. Nine years after the first warning. $65 billion in claimed assets, most of which had never existed at all. He was sentenced to 150 years and died in a federal prison in 2021. The wrapper was never the problem. Dozens of "independently diversified" feeder funds all led back to one man. Diversifying across them changed nothing, because there was only ever one thing to verify - and for nine years, almost nobody did.
Enron stock went from $90 to under a dollar. $850 million in employee retirement savings went with it. Most of those employees never worked in finance - they just trusted their employer's match. For years, Enron matched 401(k) contributions with its own stock instead of cash. Employees weren't allowed to sell that stock until they turned 50. Charles Prestwood spent 33.5 years working in the gas business, most of it at Enron. He never touched his retirement account. By 2001, it held $1,310,000 - every dollar of it in Enron stock. Then the company collapsed. Prestwood lost 99 percent of it. He wasn't reckless. He wasn't chasing a hot tip. He did exactly what his employer told him to do, for over three decades. Fifteen thousand people went through some version of the same thing. Total losses in Enron stock inside 401(k) accounts: an estimated $850 million. This is what "concentration risk" actually looks like when it isn't a Wall Street term. It's someone's entire working life, sitting in one company's stock, because that's just how the retirement plan was set up. Nobody sends a warning before the account hits zero.
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Beaver @Beaver_0x
2K Followers 267 Following Ideas that compound. Thoughts on building, thinking clearly, and doing the work.
Roan @RohOnChain
78K Followers 420 Following building my life around AI agents, LLMs & quant systems for prediction markets + crypto
Mavian Mur @0xMavian
566 Followers 95 Following I sit across from your trade. Usually on the right side of it.
Dorian Vale @iamdorianvale
11 Followers 30 Following thinking in probibilities is my key to greatness WSOP 2017 final table
Nash Archive @imperiumNash
1K Followers 47 Following Playing with numbers and probability since 2009 No luck, just math and my edge
Mary @Mary_0nx
637 Followers 269 Following Finance decoded to first principles. Leverage, risk, incentives. Every claim sourced.
Mavrick J. @Mavrickoss
240 Followers 88 Following Department of Statistics. Stanford University graduate. Quant Finance | Statistical Modeling | Probabilistic Methods
Alxcapital @Allx032
1K Followers 168 Following "Numbers rule the universe." Pythagoras Now AI reads what he saw 2,500 years ago.
Jey @0xJeyx
1K Followers 193 Following Senior Software Engineer | Building & teaching practical AI agents, multi-agent systems & workflows Follow for daily builds & free guides
Oracle Boar @bored2boar
26K Followers 601 Following 𝟱+ 𝘆𝗲𝗮𝗿𝘀 𝗶𝗻 𝗮𝗿𝗯𝗶𝘁𝗿𝗮𝗴𝗲 / 𝟬.𝟮% 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 𝗺𝗮𝗿𝗸𝗲𝘁𝘀 / 𝟲 𝗳𝗶𝗴𝘀 𝗼𝗻 𝗺𝗲𝗺𝗲𝘀
Krynex @kryneeex
291 Followers 249 Following the math behind trading and sizing. no hype, just the equations
Сarm1ne @carm1nee
16K Followers 200 Following ✦ Researcher & Analyst ✦ Wall Street / AI / News | @zscdao
Soler @Solerfin
433 Followers 89 Following One story a day: the professors and traders whose math still runs markets. MIT, Yale,Taleb no tickers.
Sawyer @0xSawyer
45 Followers 71 Following quant, probability & market structure. the math behind why edge survives and noise doesn't.
Knox @knoxodds
3K Followers 198 Following Stream Clips, Media & Updates | DM for credit/submissions | Turn Notis ON
Ryuk @RyuksHorizon
45 Followers 93 Following AI/ML · most of what you read is noise. I forge what actually ships and prove it. data @Netflix
Superior @andreysuperior
17K Followers 802 Following reading the future for a living. occasionally posting it
Loran @0xLoran
2K Followers 104 Following quant math, market structure, and the difference between edge and noise
Tigerflow @tigerfl0w
11K Followers 145 Following Tiger mode. No panic. Just flow https://t.co/o0hpGCrTJn
Voltex @VoltexGar
3K Followers 147 Following hunting alpha in quant, math and ai - none of it secret.
Zyron @Zyron5m
3K Followers 199 Following One old lecture a day from the people who actually beat the system. Markets, risk, and complex systems. No hot takes. Just the tape. All free.
Andrej Drats @AndrejDrats
9K Followers 1K Following Private X content partner for tech & health founders | Worked with multiple 9-figure founders | 600M+ views generated | $3M in revenue for clients








































