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D.E. Shaw pays a machine learning PhD $600,000 a year for one skill: teaching a computer to tell a real pattern from random noise. a professor in Chennai taught that exact skill on a free chalkboard over a decade ago. his point: a market is mostly noise with a... faint pattern buried inside. every trading bot, every AI model, is one machine trying to draw the line between the two. get the line right and you print. get it wrong and you are trading on ghosts. no GPU cluster, no hedge fund. a professor at a green board in Chennai, showing how a machine learns to recognize what matters and ignore the rest. skip to the board in the first ten minutes. he takes a pile of examples and shows how a machine draws a boundary between one class and another, in notation a beginner can follow. that boundary is your buy and your sell. I put what I learned in this lecture into practice and developed a strategy that generates income, the results surprised me. 26 days. $100 → $24,300. 75% win rate. Sharpe 2.46. I'm giving away the full configuration of my bot for free. 24 hours only. Here's how: >Comment "BOT" >Like and Follow me I'll send the complete setup in your DMs.show more

Voltex

3,397 subscribers

14,206 просмотров • 17 дней назад •via X (Twitter)

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Комментарии: 29

Фото профиля T.Oberoi

T.Oberoi16 дней назад

BOT

Фото профиля Voltex

Voltex16 дней назад

Check out DM 📤

Фото профиля Leo

Leo17 дней назад

nice write!

Фото профиля Rossst.03

Rossst.0317 дней назад

Wow, why is this info free...

Фото профиля Shevaxgod

Shevaxgod17 дней назад

wow so smart

Фото профиля Badrinarayanan S

Badrinarayanan S16 дней назад

BOT

Фото профиля Voltex

Voltex16 дней назад

Follow me, and then I'll be able to send you a message)

Фото профиля Badrinarayanan S

Badrinarayanan S13 дней назад

I followed you

Фото профиля Voltex

Voltex13 дней назад

Check out DM 📤

Фото профиля JaganVaman

JaganVaman17 дней назад

Bot

Фото профиля Voltex

Voltex17 дней назад

Check out DM 📤

Фото профиля FindMyFutureApp.AI (Claude❤️❤️)

FindMyFutureApp.AI (Claude❤️❤️)17 дней назад

Bot

Фото профиля Voltex

Voltex16 дней назад

Follow me, and then I'll be able to send you a message)

Фото профиля నామధారక 🚩

నామధారక 🚩17 дней назад

BOT

Фото профиля Voltex

Voltex16 дней назад

Check out DM 📤

Фото профиля Robin

Robin17 дней назад

Bot

Фото профиля DreamHacker.Base.Eth 🀄

DreamHacker.Base.Eth 🀄17 дней назад

Bot

Фото профиля Voltex

Voltex17 дней назад

@ShadowCrusherX Check out DM 📤

Фото профиля Lima

Lima17 дней назад

26 days is the exact sample size where you can't tell the pattern from the noise, which is what the lecture was about

Фото профиля SpectraView

SpectraView17 дней назад

They are so cheerful.

Фото профиля Jayashankar Dhandapa

Jayashankar Dhandapa17 дней назад

Bot

Фото профиля Voltex

Voltex17 дней назад

Check out DM 📤

Фото профиля Twilight

Twilight17 дней назад

BOT

Фото профиля Voltex

Voltex17 дней назад

Follow me, and then I'll be able to send you a message)

Фото профиля Twilight

Twilight16 дней назад

done.

Фото профиля rajeev singh

rajeev singh17 дней назад

BOT

Фото профиля Voltex

Voltex17 дней назад

Follow me, and then I'll be able to send you a message)

Фото профиля Sethu

Sethu17 дней назад

BOT

Фото профиля Voltex

Voltex17 дней назад

Check out DM 📤

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Over a decade ago, a math professor in Chennai opened his first lecture with the simplest idea in all of math, and it is the exact thing every prediction market runs on today. NPTEL filmed it. it has been free ever since. 759,000 people have watched it, almost none of them trade. his point: before probability, before any odds, there are just sets. a bag of everything that can happen, and the slice you are betting on. every trader pricing a market is doing set theory without knowing the name for it. no Wall Street badge, no trading desk. just a professor at a green board building the whole machine from nothing. skip to the board in the first ten minutes. he takes union, intersection, and the outcomes you throw away, and turns them into the rules every payoff has to obey, in notation a schoolkid can follow. no slides. no app. one green board and a piece of chalk. a quant i know rewatched this exact lecture before rebuilding his risk model. said he had been skipping the part that actually matters. I put the practical aspects of this lecture into practice and developed a strategy that generates income, the results surprised me. 27 days. $200 → $25,400. 74% win rate. Sharpe 2.47. I'm giving away the full configuration of my bot for free. 24 hours only. Here's how: >Comment "SEND" >Like and Follow me I'll send the complete setup in your DMs.

Over a decade ago, a math professor in Chennai opened his first lecture with the simplest idea in all of math, and it is the exact thing every prediction market runs on today. NPTEL filmed it. it has been free ever since. 759,000 people have watched it, almost none of them trade. his point: before probability, before any odds, there are just sets. a bag of everything that can happen, and the slice you are betting on. every trader pricing a market is doing set theory without knowing the name for it. no Wall Street badge, no trading desk. just a professor at a green board building the whole machine from nothing. skip to the board in the first ten minutes. he takes union, intersection, and the outcomes you throw away, and turns them into the rules every payoff has to obey, in notation a schoolkid can follow. no slides. no app. one green board and a piece of chalk. a quant i know rewatched this exact lecture before rebuilding his risk model. said he had been skipping the part that actually matters. I put the practical aspects of this lecture into practice and developed a strategy that generates income, the results surprised me. 27 days. $200 → $25,400. 74% win rate. Sharpe 2.47. I'm giving away the full configuration of my bot for free. 24 hours only. Here's how: >Comment "SEND" >Like and Follow me I'll send the complete setup in your DMs.

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Rossst.03

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Loran

47,557 просмотров • 1 месяц назад

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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.03

281,905 просмотров • 2 месяцев назад

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Marvin Minsky, MIT professor and father of AI: "The best trader on Wall Street is no longer human. I spent fifty years proving the mind is just a machine built from smaller machines, and once that's true, nothing stops a machine from being the house. it already is." this free lecture holds the entire "AI edge" the funds and the gurus sell, and the man teaching it founded the field itself and put his whole MIT course online for free. at the board it's simple. Minsky's idea is that there is no magic in thinking. a mind is a huge pile of small, mindless parts, each doing something simple, and intelligence is just what happens when enough of them work together. a trading machine is the same trick: thousands of simple rules stacked until an edge appears. that's the whole "AI", minus the mystery. Minsky taught this at MIT and published "The Society of Mind" in 1986. the course has been free ever since. same point as my casino piece above: the house wins with many small mindless advantages stacked, not with one born genius. the ideas are free and every AI lab and every fund already has them. what they cannot sell you is the data and the compute to actually build the machine. that is the real moat now, and no lecture can hand it to you.

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27,976 просмотров • 1 месяц 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.

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.03

21,051 просмотров • 15 дней назад

David MacKay, Cambridge professor: "Citadel and Jane Street pay $900K for people who get one idea I taught free at Cambridge: information is measurable, and whoever measures it best wins. the casino knew it first. the machines know it now." this free lecture holds the entire "secret alpha" the funds and the AI gurus sell, and the man teaching it put his whole course and his whole book online for free and never locked a single page. at the board it's simple. information is just how much a signal cuts your uncertainty, and you can measure it in exact bits. the more an edge shrinks what you don't know, the more it is worth, and Shannon proved there is a hard ceiling on how fast you can compound it into money. that is the whole "edge", and the whole "AI magic", minus the marketing. MacKay taught it at Cambridge and gave the book away free in 2003. it has been free ever since. same point as the casino piece above: the house wins with a small, measurable edge, repeated and sized right, not with a secret. the theory is free and every fund and every model already runs on it. what they cannot sell you is the data to feed the machine and the discipline to size the bet. that is the part that actually compounds, and no course can put it in a formula.

David MacKay, Cambridge professor: "Citadel and Jane Street pay $900K for people who get one idea I taught free at Cambridge: information is measurable, and whoever measures it best wins. the casino knew it first. the machines know it now." this free lecture holds the entire "secret alpha" the funds and the AI gurus sell, and the man teaching it put his whole course and his whole book online for free and never locked a single page. at the board it's simple. information is just how much a signal cuts your uncertainty, and you can measure it in exact bits. the more an edge shrinks what you don't know, the more it is worth, and Shannon proved there is a hard ceiling on how fast you can compound it into money. that is the whole "edge", and the whole "AI magic", minus the marketing. MacKay taught it at Cambridge and gave the book away free in 2003. it has been free ever since. same point as the casino piece above: the house wins with a small, measurable edge, repeated and sized right, not with a secret. the theory is free and every fund and every model already runs on it. what they cannot sell you is the data to feed the machine and the discipline to size the bet. that is the part that actually compounds, and no course can put it in a formula.

Rossst.03

24,939 просмотров • 1 месяц назад

A DEVELOPER PROVED THE REGEX YOU'VE WRITTEN A THOUSAND TIMES IS SECRETLY A COMPILER AND THAT ALMOST NO ONE WHO USES THEM HAS ANY IDEA WHAT ACTUALLY RUNS 36 minutes from Paul Wankadia, the engineer behind a regex engine that compiles your pattern straight down to raw machine code -- walking through what really happens between the slashes. -> The moment it clicks, regex stops being magic punctuation you paste from Stack Overflow and becomes what it actually is: a tiny machine. Your pattern gets turned into a state machine, and that machine is what runs against every character of your text. That one idea explains everything you never understood. Why one regex returns instantly and a nearly identical one hangs your whole server. Why some patterns are safe and others are a denial-of-service waiting to happen. It was never random -- it's whether the machine underneath is built well or badly. Writing a regex was never the skill -> reading one is. And now that an AI agent hands you dense, clever patterns you'd never write yourself, the person who can see the machine underneath is the one who catches the one that takes down production at 3am. Everyone copies regex and prays. This is the talk that ends the praying. Save it. The next time a pattern "Just works," you'll actually know why ↓

A DEVELOPER PROVED THE REGEX YOU'VE WRITTEN A THOUSAND TIMES IS SECRETLY A COMPILER AND THAT ALMOST NO ONE WHO USES THEM HAS ANY IDEA WHAT ACTUALLY RUNS 36 minutes from Paul Wankadia, the engineer behind a regex engine that compiles your pattern straight down to raw machine code -- walking through what really happens between the slashes. -> The moment it clicks, regex stops being magic punctuation you paste from Stack Overflow and becomes what it actually is: a tiny machine. Your pattern gets turned into a state machine, and that machine is what runs against every character of your text. That one idea explains everything you never understood. Why one regex returns instantly and a nearly identical one hangs your whole server. Why some patterns are safe and others are a denial-of-service waiting to happen. It was never random -- it's whether the machine underneath is built well or badly. Writing a regex was never the skill -> reading one is. And now that an AI agent hands you dense, clever patterns you'd never write yourself, the person who can see the machine underneath is the one who catches the one that takes down production at 3am. Everyone copies regex and prays. This is the talk that ends the praying. Save it. The next time a pattern "Just works," you'll actually know why ↓

slash1s

193,107 просмотров • 3 месяцев назад

🚨 THIS IS ABSOLUTELY INSANE a developer just released a free tool that builds a vertical video with a talking presenter. out of one script and one photo. it's called lanshu-create-ai-presenter-video. it landed on GitHub two days ago. 267 stars. MIT. here's how it works: 1. You give it a script and a presenter photo you have the rights to. 2. The AI writes and voices the narration, generates the presenter, and locks the lips to the audio. 3. The skill edits, burns in subtitles and a cover, checks the sync, and hands back a master with a QA report. 9:16, 1080x1920, 30fps, 45-75 seconds. all of it happens in one run, on your own machine. save this before you sit down to cut your next video. i left the link in the next comment 👇

🚨 THIS IS ABSOLUTELY INSANE a developer just released a free tool that builds a vertical video with a talking presenter. out of one script and one photo. it's called lanshu-create-ai-presenter-video. it landed on GitHub two days ago. 267 stars. MIT. here's how it works: 1. You give it a script and a presenter photo you have the rights to. 2. The AI writes and voices the narration, generates the presenter, and locks the lips to the audio. 3. The skill edits, burns in subtitles and a cover, checks the sync, and hands back a master with a QA report. 9:16, 1080x1920, 30fps, 45-75 seconds. all of it happens in one run, on your own machine. save this before you sit down to cut your next video. i left the link in the next comment 👇

Granite

162,249 просмотров • 21 дней 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.

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.03

61,127 просмотров • 18 дней назад

In 2013 a Wall Street risk boss walked up to an MIT chalkboard and gave away the exact math desks charge $400,000 a year to run. MIT filmed it. it has been free for 13 years. 7.9 million people pressed play and almost none of them changed a thing. his point: the Wall Street edge was never a secret. it is a first lecture. options, risk, how a payout is actually built. every prediction-market trader hunting an edge in 2026 is chasing what Jake Xia put on a board in hour one of a free class. he ran risk for a living, not a channel. the video outdrew most blockbusters and still moved almost no one, because watching is not doing. skip to where he prices risk. he takes the thing quant threads sell for $500 and builds it from zero, slow enough for a beginner to follow. no paywall. no NDA. one board and a marker. a quant I know sends this link to every junior who whines the math is too hard. you are 13 years late. it is still free.

In 2013 a Wall Street risk boss walked up to an MIT chalkboard and gave away the exact math desks charge $400,000 a year to run. MIT filmed it. it has been free for 13 years. 7.9 million people pressed play and almost none of them changed a thing. his point: the Wall Street edge was never a secret. it is a first lecture. options, risk, how a payout is actually built. every prediction-market trader hunting an edge in 2026 is chasing what Jake Xia put on a board in hour one of a free class. he ran risk for a living, not a channel. the video outdrew most blockbusters and still moved almost no one, because watching is not doing. skip to where he prices risk. he takes the thing quant threads sell for $500 and builds it from zero, slow enough for a beginner to follow. no paywall. no NDA. one board and a marker. a quant I know sends this link to every junior who whines the math is too hard. you are 13 years late. it is still free.

Loran

152,813 просмотров • 1 месяц назад

Nobody can track 10^23 particles. A professor in Chennai spends an hour explaining why that stopped being a problem 150 years ago. This is Classical Physics, lecture 20, from V. Balakrishnan's course at IIT Madras, on the founding postulates of equilibrium statistical mechanics. The move is a surrender that pays. Stop following trajectories. Count how many microscopic arrangements produce the same macroscopic state, and temperature, pressure, and entropy fall out as consequences. Every sampling method in machine learning is a descendant. Diffusion models, MCMC, Boltzmann distributions in softmax. All of it is state counting wearing different notation. Watch how he handles the postulates themselves. He states what is assumed rather than derived, then refuses to pretend the assumption is a proof. A machine learning engineer I know rewatched the first 25 minutes and said sampling stopped looking like a trick. Free on YouTube, low resolution, green chalkboard. The particles were never the point. The counting was.

Nobody can track 10^23 particles. A professor in Chennai spends an hour explaining why that stopped being a problem 150 years ago. This is Classical Physics, lecture 20, from V. Balakrishnan's course at IIT Madras, on the founding postulates of equilibrium statistical mechanics. The move is a surrender that pays. Stop following trajectories. Count how many microscopic arrangements produce the same macroscopic state, and temperature, pressure, and entropy fall out as consequences. Every sampling method in machine learning is a descendant. Diffusion models, MCMC, Boltzmann distributions in softmax. All of it is state counting wearing different notation. Watch how he handles the postulates themselves. He states what is assumed rather than derived, then refuses to pretend the assumption is a proof. A machine learning engineer I know rewatched the first 25 minutes and said sampling stopped looking like a trick. Free on YouTube, low resolution, green chalkboard. The particles were never the point. The counting was.

Merlow

24,534 просмотров • 1 месяц назад

$In 2008 a Stanford professor stood at a podium and proved, for free, that information and money grow by the exact same equation. it was filmed. it has been free for 18 years. 7,000 people watched it. Thomas Cover died four years later and took the fame with him. his life's work: Shannon's information theory and Kelly's betting formula are one thing. how much to bet is just how much you know. every quant sizing a trade in 2026 is standing on Cover, whether they know the name or not. he wrote the book every information theorist trains on. the lecture that ties it all to money sits on YouTube with fewer views than a cat clip. skip to where he turns a horse race into a stock market. same math. a bit of information, a fraction of your bankroll, one growth rate. no fund. no signal. one professor and one equation. a quant I know says this hour is the missing chapter behind every book on position sizing he owns. you are 18 years late. it is still free.$

In 2008 a Stanford professor stood at a podium and proved, for free, that information and money grow by the exact same equation. it was filmed. it has been free for 18 years. 7,000 people watched it. Thomas Cover died four years later and took the fame with him. his life's work: Shannon's information theory and Kelly's betting formula are one thing. how much to bet is just how much you know. every quant sizing a trade in 2026 is standing on Cover, whether they know the name or not. he wrote the book every information theorist trains on. the lecture that ties it all to money sits on YouTube with fewer views than a cat clip. skip to where he turns a horse race into a stock market. same math. a bit of information, a fraction of your bankroll, one growth rate. no fund. no signal. one professor and one equation. a quant I know says this hour is the missing chapter behind every book on position sizing he owns. you are 18 years late. it is still free.

Loran

33,982 просмотров • 1 месяц назад

GROK BOT MADE ME $7,600 IN THE LAST 24 HOURS AND COSTS $1.90 A DAY TO RUN the bot is built straight from their own official docs, I didn't write a line of code - just one file, three lines root → scanner → analysis → filter → trade → back to root it reads every market and every headline at once and filters 400 signals a day out of those 400 exactly 1 makes it to a trade, the rest get killed before I wake up the priciest model on the stack gets called once a day, everything else runs on a $0.10 batch X Search eats 53% of the whole bill, because that is where the news shows up before the chart does 12 minutes of checking against a month of building - that is the whole gap between $7,600 and zero the check is 3,600× shorter than what most people do instead of it a 3-line ROOT.md gets read 30 mornings in a row and the bot never asks what to do next write those three lines badly and the machine automates the wrong business perfectly, 30 times save this and paste it into Grok - let it write your ROOT.md ↓

GROK BOT MADE ME $7,600 IN THE LAST 24 HOURS AND COSTS $1.90 A DAY TO RUN the bot is built straight from their own official docs, I didn't write a line of code - just one file, three lines root → scanner → analysis → filter → trade → back to root it reads every market and every headline at once and filters 400 signals a day out of those 400 exactly 1 makes it to a trade, the rest get killed before I wake up the priciest model on the stack gets called once a day, everything else runs on a $0.10 batch X Search eats 53% of the whole bill, because that is where the news shows up before the chart does 12 minutes of checking against a month of building - that is the whole gap between $7,600 and zero the check is 3,600× shorter than what most people do instead of it a 3-line ROOT.md gets read 30 mornings in a row and the bot never asks what to do next write those three lines badly and the machine automates the wrong business perfectly, 30 times save this and paste it into Grok - let it write your ROOT.md ↓

Sprytix

27,231 просмотров • 12 дней назад

A Stanford mathematician who spent 10 years as a professional magician just described the market in one sentence: "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." That's Persi Diaconis. He has a free lecture that asks one question: does anything actually happen at random? The answer is: far less than you think. The market is his first trick in the wild. It looks like pure chance. 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. 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. The lecture is free. Here's 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.

A Stanford mathematician who spent 10 years as a professional magician just described the market in one sentence: "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." That's Persi Diaconis. He has a free lecture that asks one question: does anything actually happen at random? The answer is: far less than you think. The market is his first trick in the wild. It looks like pure chance. 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. 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. The lecture is free. Here's 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.

Veles

2,188,032 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.

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.03

214,907 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.

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.03

216,635 просмотров • 2 месяцев назад