Rossst.03
@Rossst_03 • 6,483 subscribers
Where prediction markets meet AI. I hunt mispriced odds on Polymarket. @zscdao member
Videos
Mrityunjoy Chakraborty, IIT Kharagpur professor: "Jane Street pays a 22 year old $500,000 a year for one skill: turning uncertainty into a number you can bet on. that number is the first thing this professor teaches, and it is free" this free lecture is the foundation every quant bot and hedge fund model is secretly built on. before the AI, before the strategy, there is one question. what is the chance this happens, exactly. get that number right and every bet after it is just math. get it wrong and no model, no bot, no amount of compute can save you. Chakraborty builds probability from the axioms up, on a blackboard, in notation a 15 year old can follow. Wall Street sells this as a $500,000 edge. an IIT professor hands you the source code for nothing.
Rossst.03703,327 просмотров • 21 дней назад
Yilin Wang, MIT mathematician and one of the leading minds on the geometry of randomness: "there is a precise number for how far a shape is from pure chance. Citadel pays $500,000 to people who compute it instead of guessing it." her field is the mathematics of random curves. flip enough coins and the path they trace is not shapeless. it has a precise geometry, and a number, the Loewner energy, that measures how far a curve sits from pure chance. a circle scores zero. it is the most natural thing randomness can draw. almost every shape you see on a chart scores near zero too. it is noise wearing a costume. this is the entire quant problem in one idea. the market draws millions of random curves, and only a vanishing few carry real structure. the edge is a rigorous way to tell the costume from the signal. Citadel pay $500,000 a year for people who can measure that difference instead of feeling it. the trader who falls in love with a pattern is admiring a curve that randomness would have drawn anyway. the shape was never the edge. the odds that randomness did not draw it were.
Rossst.0358,891 просмотров • 9 дней назад
Long Jin, Tsinghua mathematician who trained under the same master as Semyon Dyatlov and then proved a theorem beside him: "my school spent years proving that chaos hides your signal. I proved the limit on that. watch a small enough slice of a chaotic system and it cannot hide the whole from you. a quant fund pays $500,000 a year for that exact estimate." it is called control of eigenfunctions, and it answers one question: how much of a wild system can you reconstruct from a tiny observation window. his theorem puts a number on it. even at maximum chaos, a signal cannot vanish everywhere. it has to leave a trace, and the size of that trace is fixed, not up for debate. this is the entire quant game restated. you never see the whole market. you see a slice. the only question is how much the rest is forced to reveal, and there is a hard mathematical answer. Dyatlov proved how well chaos hides. his classmate Long Jin proved how much it cannot. the second theorem is the one you can trade.
Rossst.0340,626 просмотров • 7 дней назад
Mrityunjoy Chakraborty, IIT Kharagpur professor: "every hedge fund, every trading bot, every bet you have ever made obeys three rules. Citadel pays $500,000 to people who truly understand them. this professor writes all three on a blackboard for free" these are the axioms of probability, the ground rules sitting under all of it. three simple statements. a probability is never negative. something is certain to happen. separate outcomes add up. that is the entire foundation. get comfortable with these three and every model in finance becomes readable. skip them and you are just guessing with extra steps. Chakraborty proves them from zero, slowly, in notation anyone can follow. Wall Street rents you these rules for half a million a year. an IIT professor hands you the deed for nothing.
Rossst.03112,379 просмотров • 20 дней назад
An Indian physicist put the entire secret behind Renaissance's $100 billion on one chalkboard: a coin that barely beats 50/50. he is V. Balakrishnan, and his lecture went viral years after he recorded it. it has been free the whole time. almost nobody who trades has watched it. lecture one is the humblest thing in all of finance. a coin that lands your way a little more than half the time. that is the entire edge. that is all Renaissance ever had. the post above is the one equation for what to do with that coin. not what to bet. how much. bet too little and you die of old age. bet too much and one flip ends you. that same coin is every trade, every hand, every prediction market. a tiny edge, flipped a million times. the whole machine fits on his board, and he charged nothing for it. no slides. no notes. one coin and a stick of chalk. a quant I know says this old Indian lecture taught him probability better than his entire degree. the coin is free. the equation is free. the discipline to size it is the only thing left to earn.
Rossst.03159,548 просмотров • 1 месяц назад
Terence Tao, UCLA professor and the most decorated mathematician alive: "Funds pay $750K to combine weak signals into one real edge. I proved the thing that makes it work and makes it dangerous: in any long enough sequence, hidden structure is unavoidable. it always accumulates. the whole job is telling the real structure from the noise that only looks like it." this free lecture is the most decorated mathematician alive on the exact problem sitting underneath every factor model, and it costs nothing. at the board it's simple. Tao's lifelong theme is the line between structure and randomness. The Erdős discrepancy problem asks a deceptively simple thing: can you write an endless string of plus-ones and minus-ones that stays perfectly balanced forever? Tao proved you cannot. No matter how cleverly you try, imbalance, hidden structure, is forced to accumulate as the sequence grows. There is no such thing as a long stream of pure, structureless noise. That's the whole idea, minus the jargon. Which is exactly why a multi-factor model can work, and exactly why it can kill you. Stack enough weak signals and real structure will appear, because at scale structure is unavoidable. But so will fake structure, patterns that exist only because the data is long enough to force them. Same point as the post above: finding structure is guaranteed. Knowing which structure is an edge is the rare and expensive part. the mathematics is free and public. what nobody can sell you is the judgment to tell the structure the market will pay you for from the structure that exists only because you looked hard enough. That judgment is the alpha, and it takes years to build.
Rossst.03213,931 просмотров • 1 месяц назад
Alan Oppenheim, MIT professor: "Jump Trading pays quants $650K to pull one real signal out of market noise. I wrote the textbook on that exact math and taught it for free." this free MIT lecture is the math the whole "quant edge" is built on, and almost nobody selling you a course will name it. the man teaching it wrote the signal-processing textbook every engineer on earth learned from, and he put the lectures online for nothing. here is the idea. a price chart is a signal buried in noise. most of what you see is random static, and hidden inside is a faint, repeating pattern with real mathematics for pulling it out. that is not a metaphor. jim simons was a codebreaker who did exactly this to enemy transmissions, then pointed the same math at the market and made a hundred billion dollars. none of it is new. oppenheim taught this in 1987, the math is older, and every lecture is free. same story i told in the article above. the edge was never a secret formula. it was knowing a market is a noisy signal, and having the tools to read it. here is what the gurus skip. the math to separate signal from noise is free and everyone has it. the edge is cleaner data than the next desk, and the discipline to trust a faint signal across thousands of trades instead of chasing the static. the filter is free. the patience to use it is not.
Rossst.03281,905 просмотров • 2 месяцев назад
Sukhendu Das, IIT Madras professor: "Jump Trading pays a 23 year old $500,000 a year for one skill: given the odds, pick the one move that makes the most money on average. that rule is the first thing this professor proves on a free chalkboard, and it costs nothing" this free lecture is the decision rule sitting under every trading bot and every hedge fund model on the planet. strip away the AI and the neural nets and one question is left. given everything you know right now, what is the single best bet. there is a mathematically correct answer. it is called the Bayes decision rule, and it turns a probability into the one action that maximizes your payoff. every profitable bot is just this rule running fast. Das builds it from zero, on a blackboard, in notation a beginner can follow. the odds go in, the optimal bet comes out. Wall Street rents this out as a $500,000 edge. an IIT professor hands you the rule itself for nothing.
Rossst.0369,755 просмотров • 17 дней назад
Daniel Kahneman, Nobel laureate and author of "Thinking, Fast and Slow": "You have two minds. one is fast, confident and usually wrong about money. the other is slow, lazy, and the only one that can do the math. I won a Nobel showing the casino lives off the first one, because it shows up before the second one wakes up." this free lecture holds the entire "trust your instincts" the gurus sell, from the Nobel laureate who proved your instincts are the trap. at the board it's simple. Kahneman split the mind in two. System 1 is fast, automatic and sure of itself. System 2 is slow, effortful, and the only part that actually computes the odds. the catch is that System 1 answers first and System 2 is lazy, so you act on a feeling and build the reasons afterward. the casino and the market are timed to catch you in that first second. that's the whole "instinct edge", minus the marketing. Kahneman worked this out over fifty years and put it in one book in 2011. it has been public ever since. same point as my casino piece above: the house wins because your fast mind calls luck skill before your slow mind can check the math. the science is free and half the world has read the book. what nobody can sell you is the discipline to wake the slow mind up before you click buy. that one pause is the whole edge, and no lecture can force you to take it.
Rossst.03197,883 просмотров • 1 месяц назад
Persi Diaconis, Stanford mathematician and former professional magician: "I spent fifty years proving one thing: almost nothing is as random as it looks. The 50.75% that built Renaissance wasn't luck. It was a tiny crack in the randomness, found and repeated a million times." this free lecture holds the exact idea the thread above is built on. and the man giving it isn't a trader. he's a stanford professor and former professional magician who spent his career on one question: where does real randomness end, and where does a hidden edge begin. here is his life's finding. a coin, a shuffle, a market, all look random, yet each hides a faint, measurable bias. on its own that bias is nothing, indistinguishable from luck. repeat it enough times and it stops being luck and becomes a law. that faint crack, found and repeated, is the whole distance between a 50.75% win rate and a hundred billion dollars. none of this is new or hidden. diaconis has taught it for decades, the math runs back to 1713, and the lecture is free. i mapped the full system in my article, expected value, kelly, and this. same point the thread makes: the edge was sitting in plain sight. here is the part the gurus skip. a faint edge only pays if you survive long enough to reach it, and that takes correct sizing and the patience to trust it through thousands of losing-looking trades. most quit while it still looks like randomness. the math is free. the nerve to hold it is the edge.
Rossst.03231,067 просмотров • 2 месяцев назад
Persi Diaconis, Stanford mathematician and former professional magician: "I've spent my life on two tricks: making a rigged deck look random, and making a random one look rigged. The market is the first trick, and almost nobody catches it." this free lecture asks one question, does anything happen at random, and the answer is: far less than you think. and the man asking isn't a trader. he's a stanford professor and former professional magician who spent his life proving how badly humans read randomness. the market is his first trick in the wild. it looks like pure chance, yet buried inside is a faint rig, a 50.75% tilt no eye can see. your gut reads a losing week as a broken system and a hot streak as skill, and it's wrong both times. the tilt is invisible to human intuition, which is exactly why funds hand the decision to the math. none of it is hidden. diaconis has taught it for decades, the probability goes back to 1713, and the lecture is free. same point the thread makes: the 50.75% is real, but it lives inside noise your gut will always misread. here is the trap. you feel every win and every loss, but you cannot feel the average, and the average is the only thing that pays. it takes thousands of trades for a 51% edge to separate from luck, and almost everyone quits long before then. the math is free. the patience to trust it past your own eyes is the edge.
Rossst.03216,635 просмотров • 2 месяцев назад
Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath. that is all it is, and it is the bluntest one there is. the same math gives you filters that lag less and cut more noise, and that gap is a real edge. this is the second half of what Simons was doing. first you accept the market is a signal buried in noise. then you build the filter that reads it, and the moving average on your chart is the crudest possible version. Oppenheim builds the real ones at the board in this lecture. here is the catch. a filter only helps if there is a real signal under the noise. smooth pure randomness and you will see a beautiful trend that means nothing. the filter is free. knowing there is a real signal worth filtering is the edge.
Rossst.03214,907 просмотров • 2 месяцев назад
Prabha Sharma, one of the sharpest women mathematicians India has produced: "Optiver puts every applicant through a probability gauntlet, then pays the ones who pass $500,000 a year for one skill: counting the ways an outcome can happen before anyone else does. that is exactly where this professor opens her course, and it is free" this free lecture is the foundation under every prediction market and every price you have ever seen. strip away the models and the AI and one question is left. in how many ways can this happen, and how many of them pay you. get that count right and the probability falls out on its own. get it wrong and every model built on top is wrong with it. Sharma builds it from zero, on a blackboard, in notation a schoolkid can follow. permutations, combinations, the n choose r sitting under every set of odds. Wall Street rents this out as a $500,000 edge. an IIT professor hands you the whole foundation for free.
Rossst.0361,127 просмотров • 18 дней назад
Raphael Townshend, Stanford AI PhD and founder of Atomic AI (Forbes 30 Under 30): ""Wall Street will pay you $500K a year to build these models. I'd rather teach them to you for free." this free stanford lecture holds the entire "77% win rate, pure math" random forest the 2026 quant threads sell you. and the guy teaching it didn't take the wall street money either, townshend went on to found an ai drug-discovery company and land forbes 30 under 30. at the board he builds it from scratch: one decision tree overfits, so you grow hundreds on random subsets of the data and features and average them. the errors cancel, the signal survives. that's the whole "100 ai agents auditing the market" idea, minus the marketing. the √N feature rule, the out-of-bag error, the probability output, all of it is standard ensemble learning, taught free by stanford for years. random forests came out of leo breiman's public paper in 2001. the thread didn't discover it. it renamed it. and here's the honest part the win rate hides. a model that scored 77% on past data is describing the past, not promising the future. ensembles cut variance, they don't turn a weak edge into a real one, and markets shift under the model in ways the training set never warned about. the lecture is free. knowing whether your 77% survives out of sample and on live capital is exactly the part the post skips."
Rossst.03203,272 просмотров • 2 месяцев назад
Marvin Minsky, MIT professor and father of artificial intelligence: "Anthropic pays engineers $900K to build multi-agent AI systems. The blueprint is 40 years old, from an MIT professor who proved intelligence is just a swarm of dumb specialists." the thread above shows you how to turn one AI into a team of specialized agents, each with its own job and memory, all managed by a boss. brilliant. it is also marvin minsky's 1986 theory of how your own mind works. minsky's whole idea was that intelligence is not one smart thing. it is a society of tiny, mindless agents, each doing a single dumb job, none of them intelligent alone. put enough of them together under a few managers and intelligence emerges. that is not a metaphor for the claude trick. it is the claude trick. so when you spin up specialized sub-agents and delegate, you are not inventing a new hack. you are rebuilding the architecture minsky described forty years ago, the same one your brain has run your entire life. he co-founded the field, taught it at MIT, and left it all in this free lecture. same story i keep telling: the "new" AI trick is usually an old idea in a new wrapper. here is the part the thread skips, and minsky knew it. a society of agents is only as good as how you organize it. one dumb specialist is useless. a thousand, badly managed, is chaos. the edge was never spawning the agents. it is the orchestration, knowing which specialist to call, when, and how to combine their answers. the tool is free. the judgment is the whole game.
Rossst.03148,991 просмотров • 1 месяц назад
An MIT professor finds the prize behind a thousand doors by opening ten. no faster running. he just skips every door it cannot be behind. the lecture is called algorithmic thinking. 6 million people have watched it, and it has been free the whole time. brute force checks every door, one by one. a real algorithm throws away half of them with every step. same answer, a thousand times fewer moves, zero new hardware. now read the post above. that is Wall Street paying $300 million for the opposite. they drilled a cable through a mountain to open the same thousand doors 3 milliseconds faster. Devadas just stopped opening most of them. that same move is every search engine, every trading model, every small AI that beats a bigger one. the edge was never the speed of the machine. it was the shape of the idea. no cable. no mountain. one better idea. a quant I know says one algorithm rewrite beat a full year of latency upgrades on his desk. they spent $300 million to run the long way faster. the shortcut has been free for over a decade.
Rossst.0381,024 просмотров • 1 месяц назад
Ben Polak, Yale economics professor: "Jane Street made $20.5 billion in a year without guessing where the market goes. this free Yale lecture is the exact trap they spend all day avoiding: the winner's curse." the post above is one machine with two seats. Polak runs a live auction in class and proves a brutal rule. the person who wins the bid is usually the person who was most wrong. win, and you probably overpaid. that is adverse selection. a market maker's whole job is to not be that person. quote both sides, pocket the spread, and duck the trades that only fill because someone knows more than you do. Bill Hwang took the other seat. he kept winning the bid with $36 billion until the market handed him the curse in full. two days, gone, 18 years. the math is a free Yale lecture. the discipline to want the boring side of every trade is the part no one teaches you.
Rossst.0365,660 просмотров • 1 месяц назад
Nassim Taleb, options trader and author of "The Black Swan": "Wall Street pays $500K for a five-year track record. I traded options for two decades and watched records like that vanish in a single afternoon." the article above is about telling a real edge from luck. taleb built his whole career and his books on one warning: a track record is the weakest evidence there is. a trader can win every single day for years and still be sitting on a hidden risk. the five good years don't prove skill, they just haven't met the one bad day yet. that is the entire "fooled by randomness" trap, dressed up as a resume. and you only ever see the survivors. for every rich trader with a spotless record, thousands ran the same reckless bet and quietly blew up. the graveyard is silent, so the lucky fool looks like a genius. none of this is new, taleb has said it for 25 years and the talk is free. same point as my article: a winning streak is not evidence. here is the edge, and it isn't a hot record. it's surviving. sizing so your one bad day can't erase you, and staying skeptical of your own success while everyone else worships theirs.
Rossst.0377,954 просмотров • 2 месяцев назад
Srinivasan Chandrasekaran, IIT Madras professor: "Bridgewater pays a risk manager $650,000 a year to answer one question: what is the exact probability this blows up. that is the same question this professor answers to keep billion dollar oil rigs from collapsing in a storm, and he teaches the math for free" this free lecture is the risk model under every fund that has survived more than one crash. strip away the upside talk and one number decides everything. not how much you can make, but the odds the whole thing fails. an oil rig and a trading account die the same way: one rare load bigger than anything you planned for. reliability is the math that sizes your safety margin so that day does not end you. Chandrasekaran builds it from zero, on a blackboard, in notation a beginner can follow. failure modes, safety factors, and the probability of ruin. Wall Street rents this out as a $650,000 skill. an IIT professor hands you the math of not blowing up for free.
Rossst.0321,051 просмотров • 15 дней назад
My friend sent 300 applications to quant and AI firms in two years. No MIT. No PhD. Last month Jane Street offered him $700,000. I asked him how he finally broke in from nothing. He sent me the exact lecture that flipped it for him. a free 2014 topology course, taught with paper and a rubber band. Tadashi Tokieda, a Stanford mathematician, shows you the one idea every AI model and every quant signal is secretly built on: the shape hiding inside data. I watched it last night. Halfway through I understood why the people who actually get hired talk about the geometry of data while everyone else grinds leetcode. Bookmark this and watch the lecture below. - 0:00 - what topology actually is, and why shape beats numbers - 6:20 - rubber sheet thinking: bend and stretch, never tear - 13:20 - the Mobius strip and one sided surfaces - 20:20 - why your data lives on a folded surface, the manifold every model learns
Rossst.0318,465 просмотров • 13 дней назад