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a 23-year-old with zero quant background ran a 14-year backtest on free government data last month sharpe of 1.8. most multi-strat funds averaged 1.1 last year signal he used? CFTC commitment of traders report - published every friday, free, updated weekly since 1986 nobody reads it - funds call...

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Livsun

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12,447 views • 17 days ago •via X (Twitter)

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THIS IS F*CKING DANGEROUS INFO AT THE END a 31-year-old actuary beat quant funds last year on a government file nobody reads anymore Marcus, minneapolis - no bloomberg, no fund, one free csv every friday at 3:30pm he didn't find a new signal. he found cftc's commitment of traders - public, weekly, free, and almost nobody reads past the headline he went to "leveraged funds" net long on ES futures, normalized to a rolling 2-year range late 2023 that column hit the 94th percentile historical 3-month returns at that extreme: ~1.2% average, baseline is ~2.9% january 2024 nearly ended it - crowding held extreme 6 weeks past any prior backtest, bleeding gains the whole stretch. week 5 he almost quit then it cleared. best run that quarter hit ~7%, most months edge runs 1-2% per cycle method: download ES futures COT history at cftc[.]gov/dea/futures look at "leveraged funds" net normalize to 2-year range: (current - min) / (max - min) above 0.85 or below 0.15 = crowding signal - market underperforms in crowd direction over next 4-6 weeks save this, check the COT once. 10 minutes data was never hidden. it just required reading past column 4
0:32

THIS IS F*CKING DANGEROUS INFO AT THE END a 31-year-old actuary beat quant funds last year on a government file nobody reads anymore Marcus, minneapolis - no bloomberg, no fund, one free csv every friday at 3:30pm he didn't find a new signal. he found cftc's commitment of traders - public, weekly, free, and almost nobody reads past the headline he went to "leveraged funds" net long on ES futures, normalized to a rolling 2-year range late 2023 that column hit the 94th percentile historical 3-month returns at that extreme: ~1.2% average, baseline is ~2.9% january 2024 nearly ended it - crowding held extreme 6 weeks past any prior backtest, bleeding gains the whole stretch. week 5 he almost quit then it cleared. best run that quarter hit ~7%, most months edge runs 1-2% per cycle method: download ES futures COT history at cftc[.]gov/dea/futures look at "leveraged funds" net normalize to 2-year range: (current - min) / (max - min) above 0.85 or below 0.15 = crowding signal - market underperforms in crowd direction over next 4-6 weeks save this, check the COT once. 10 minutes data was never hidden. it just required reading past column 4

Livsun

18,760 views • 1 month ago

a free government report tells you exactly what hedge funds, asset managers and leveraged traders are holding across every futures market on earth it's published every friday at 3:30pm funds have been running systematic strategies on it since 1993, and you've had exact same access the entire time it's the Commitment of Traders report - CFTC website, no login, free signal that runs on it: when leveraged funds flip net short after 4+ consecutive weeks net long, go long monday's open historical win rate on ES futures: 67%, tested back to 2006 not because report predicts direction. because positioning unwind creates mechanical buying pressure - 40,000 contracts covering short, someone absorbs that demand, and price follows average hold is 4 days, reward/risk 2.1 to 1 - Kelly says 15% position size 52 opportunities a year - drift is one-directional congress mandated this transparency in 1936. original intent: so retail could see what big money was doing Dm "Quant" for full quant course with all knowledge bookmark this before it buried retail never looked. quant desks built whole books around it data is free, backtest goes to 1993, implementation is a weekend of python they kept you staring at RSI and candle patterns while running probability tables on data congress was legally required to hand you for free
1:07

a free government report tells you exactly what hedge funds, asset managers and leveraged traders are holding across every futures market on earth it's published every friday at 3:30pm funds have been running systematic strategies on it since 1993, and you've had exact same access the entire time it's the Commitment of Traders report - CFTC website, no login, free signal that runs on it: when leveraged funds flip net short after 4+ consecutive weeks net long, go long monday's open historical win rate on ES futures: 67%, tested back to 2006 not because report predicts direction. because positioning unwind creates mechanical buying pressure - 40,000 contracts covering short, someone absorbs that demand, and price follows average hold is 4 days, reward/risk 2.1 to 1 - Kelly says 15% position size 52 opportunities a year - drift is one-directional congress mandated this transparency in 1936. original intent: so retail could see what big money was doing Dm "Quant" for full quant course with all knowledge bookmark this before it buried retail never looked. quant desks built whole books around it data is free, backtest goes to 1993, implementation is a weekend of python they kept you staring at RSI and candle patterns while running probability tables on data congress was legally required to hand you for free

Livsun

18,895 views • 1 month ago

a quant scraped free SEC filings for 3 years and outperformed 94% of mutual fund managers zero tools, zero credentials - just a government database that's existed free since 1994 every hedge fund over $100M is legally required to disclose exact holdings within 45 days of quarter-end it's called a 13F - and citadel, renaissance, two sigma all file one every quarter most retail traders have never heard of it he built one model: > rank stocks by institutional accumulation across rolling 2 quarters > weight by position-size growth, filter below $2B market cap > rebalance quarterly, nothing else backtest 2010-2024: 22.1% annualized. SPY returned 13.9% same window data is on sec. gov - free, updated quarterly, no API key python to implement: under 100 lines they didn't hide this - it's literally a government mandate you've been buying alerts, scanners, and newsletters meanwhile the edge was sitting in a free .gov filing the whole time save this not smarter - just reading the right website
0:32

a quant scraped free SEC filings for 3 years and outperformed 94% of mutual fund managers zero tools, zero credentials - just a government database that's existed free since 1994 every hedge fund over $100M is legally required to disclose exact holdings within 45 days of quarter-end it's called a 13F - and citadel, renaissance, two sigma all file one every quarter most retail traders have never heard of it he built one model: > rank stocks by institutional accumulation across rolling 2 quarters > weight by position-size growth, filter below $2B market cap > rebalance quarterly, nothing else backtest 2010-2024: 22.1% annualized. SPY returned 13.9% same window data is on sec. gov - free, updated quarterly, no API key python to implement: under 100 lines they didn't hide this - it's literally a government mandate you've been buying alerts, scanners, and newsletters meanwhile the edge was sitting in a free .gov filing the whole time save this not smarter - just reading the right website

Livsun

17,436 views • 1 month ago

hedge funds pay $50,000/year for data that's been free on SEC. gov since 2003 Form 4 filings every stock purchase a CEO makes, every share a CFO sells, filed within 48 hours and sitting there searchable for free nobody built a screener around it for two decades one guy did it in a Python script over a weekend. tracked every insider purchase above $500k in the 30 days before earnings signal held up: when a CEO buys his own stock right before earnings, it beats the market by an average of 11% over the next 60 days backtested across 7,400 trades since 2010, sharpe of 1.8, max drawdown under 15% he wasn't smarter than hedge funds. he just thought to look at a URL they were paying $50k to access behind a paywall Bookmark this before it get buried SEC made the disclosure public to protect retail investors it ended up being the only real edge retail investors ever had most people watch earnings calls. this guy just read filings same market, completely different game
0:47

hedge funds pay $50,000/year for data that's been free on SEC. gov since 2003 Form 4 filings every stock purchase a CEO makes, every share a CFO sells, filed within 48 hours and sitting there searchable for free nobody built a screener around it for two decades one guy did it in a Python script over a weekend. tracked every insider purchase above $500k in the 30 days before earnings signal held up: when a CEO buys his own stock right before earnings, it beats the market by an average of 11% over the next 60 days backtested across 7,400 trades since 2010, sharpe of 1.8, max drawdown under 15% he wasn't smarter than hedge funds. he just thought to look at a URL they were paying $50k to access behind a paywall Bookmark this before it get buried SEC made the disclosure public to protect retail investors it ended up being the only real edge retail investors ever had most people watch earnings calls. this guy just read filings same market, completely different game

Livsun

10,172 views • 2 months ago

Max Margenot, quant lecturer at Quantopian: "Jane Street pays $950,000 a year to quants who can explain how to apply stochastic processes and Markov chains in quantitative trading. " this free lecture from 2017 holds the entire "institutional stat-arb edge" the 2026 quant threads sell you. cointegration, mean reversion, the spread, the entry and exit thresholds, all of it, explained slowly, for zero dollars. 394,000 people watched it. almost none of them made a dollar. the math was never the moat. a whiteboard can't hand you the actual trade: data nobody else has, execution in microseconds, a server sitting next to the matching engine, and the one thing no formula on that board prices, how two venues actually settle when the window closes. learn the formula. just never confuse knowing it with holding the edge. the formula's been free since 2017. the edge never was.
54:18

Max Margenot, quant lecturer at Quantopian: "Jane Street pays $950,000 a year to quants who can explain how to apply stochastic processes and Markov chains in quantitative trading. " this free lecture from 2017 holds the entire "institutional stat-arb edge" the 2026 quant threads sell you. cointegration, mean reversion, the spread, the entry and exit thresholds, all of it, explained slowly, for zero dollars. 394,000 people watched it. almost none of them made a dollar. the math was never the moat. a whiteboard can't hand you the actual trade: data nobody else has, execution in microseconds, a server sitting next to the matching engine, and the one thing no formula on that board prices, how two venues actually settle when the window closes. learn the formula. just never confuse knowing it with holding the edge. the formula's been free since 2017. the edge never was.

Rossst.03

40,708 views • 2 months ago

a prop desk cleared $480M last year - four people, one strategy they run cointegration find two assets that historically move together, bet when they drift apart, exit when they close back math behind it has been in academic journals since 1987 - no secret edge, no proprietary data in practice: SPY and IVV track the same index. when their spread hits 1.8 standard deviations from its 18-month mean, it reverts 79% of the time average hold: 4 hours, no direction call - just a statistical relationship that hasn't broken in 14 years of backtesting data is free. cointegration is in every econometrics textbook, has been since the 80s reason retail never runs this: payoff per trade is 0.3%. too small to feel like an edge quant desks run it 3,000 times a year Bookmark this knowledge you're not missing information you're solving the wrong problem they kept you hunting for a 10% winner. 3,000 small ones is the actual game
0:56

a prop desk cleared $480M last year - four people, one strategy they run cointegration find two assets that historically move together, bet when they drift apart, exit when they close back math behind it has been in academic journals since 1987 - no secret edge, no proprietary data in practice: SPY and IVV track the same index. when their spread hits 1.8 standard deviations from its 18-month mean, it reverts 79% of the time average hold: 4 hours, no direction call - just a statistical relationship that hasn't broken in 14 years of backtesting data is free. cointegration is in every econometrics textbook, has been since the 80s reason retail never runs this: payoff per trade is 0.3%. too small to feel like an edge quant desks run it 3,000 times a year Bookmark this knowledge you're not missing information you're solving the wrong problem they kept you hunting for a 10% winner. 3,000 small ones is the actual game

Livsun

14,040 views • 2 months ago

A codebreaker made $31 billion. he returned 66% a year for thirty years. Buffett averaged 20%. Soros averaged 30%. nobody came close. he gave one lecture about it at MIT. Wall Street has spent forty years trying to reverse-engineer what he said. he didn't hire traders. not one MBA. not one analyst. he hired physicists, astronomers, and Cold War cryptographers. he ran the fund from a strip mall on Long Island. his name is Jim Simons. the Medallion Fund made more money than Goldman Sachs most years. he never explained how. the part nobody talks about: the same pattern recognition he used to crack Soviet codes for the NSA is what he used to crack financial markets. he said it in this lecture. nobody in finance picked it up. a quant at a multi-billion dollar fund told me they play this for every new hire on day one. not a textbook. not a model. a 45-minute talk from a man who beat Buffett, Soros, Dalio, and every hedge fund alive. $31 billion. one formula. zero finance people. Goldman, JPMorgan, Citadel, Bridgewater. he beat all of them. from a strip mall. the lecture is free. he died the following year. it is in the video.
44:52

A codebreaker made $31 billion. he returned 66% a year for thirty years. Buffett averaged 20%. Soros averaged 30%. nobody came close. he gave one lecture about it at MIT. Wall Street has spent forty years trying to reverse-engineer what he said. he didn't hire traders. not one MBA. not one analyst. he hired physicists, astronomers, and Cold War cryptographers. he ran the fund from a strip mall on Long Island. his name is Jim Simons. the Medallion Fund made more money than Goldman Sachs most years. he never explained how. the part nobody talks about: the same pattern recognition he used to crack Soviet codes for the NSA is what he used to crack financial markets. he said it in this lecture. nobody in finance picked it up. a quant at a multi-billion dollar fund told me they play this for every new hire on day one. not a textbook. not a model. a 45-minute talk from a man who beat Buffett, Soros, Dalio, and every hedge fund alive. $31 billion. one formula. zero finance people. Goldman, JPMorgan, Citadel, Bridgewater. he beat all of them. from a strip mall. the lecture is free. he died the following year. it is in the video.

Tigerflow

17,622 views • 23 days ago

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.
29:44

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 views • 1 month ago

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't. Don't want to spend a dollar for testing this? Kalshi just opened a perps exchange and gives US users $25 free to start ->
0:48

A finance professor manages $200M with AI agents, and he told everyone why: "Large language models are at the level of a fourth-year PhD student in every field" Alejandro Lopez-Lira's AI fund, Autopilot, returned 56% last year. The S&P did 16%. There are 52,000 people with money in it, and most of them just watch the machine work. What he automated is the same six-step loop every fund on earth runs: find an idea, code it, backtest it, deploy it, read the autopsy, learn from it. A quant at Two Sigma runs that loop once a month, and the salary time alone costs around $50,000 per hypothesis. All steps from this loop now fit in AI trading text box. Plain English in, executable strategy out, five-year backtest in 12 seconds, live on a broker 90 seconds after you typed the sentence. He runs $200M with AI. You can run same AI fund in two clicks, free to try: Step 6 on this loop is where everyone is stuck. Your agent has no memory. Every strategy it kills goes into a log nobody reads, and the next one starts from zero. Nobody keeps negative results. Not Citadel, not Man Group, not a single repo on GitHub. Fix that and the agent remembers every hypothesis it killed and the regime it died in. It stops burning cycles on your old mistakes. Jane Street pays 3,500 people to run this cycle and made $39.6 billion doing it. Five sixths of it is now free. Bookmark & read full map of this loop in the article below. Most people still think AI trading is out of reach for them - it isn't. Don't want to spend a dollar for testing this? Kalshi just opened a perps exchange and gives US users $25 free to start ->

cvxv666

82,592 views • 24 days ago

since 1993, hedge funds over $100M have been legally required to publish every position they hold 4 times a year, exact stocks and exact share counts, all of it free on the SEC website i spent 6 months asking one question with python: what happens when 4 or more separate funds all show up with new positions in the same small-cap stock in the same quarter - before the price has moved? backtested 2,400 signals from 2019 to 2025 67% win rate, 18.4% average gain per trade, 31 day average hold the reason the edge exists is the same reason the funds themselves can't collect it an $8B fund building a position in a $400M company moves the price against itself the second it starts buying so they file 45 days after the fact, the window opens, and nobody's standing in it running it live since february - 11 closed trades, 9 winners, +31% while the s&p returned 8% in the same period setup cost: a free API key from SEC EDGAR and one saturday morning this isn't an edge i found by being smart. it's an edge that only exists because the people publishing it are too large to use it themselves Bookmark before it get losted the filing requirement has been law since the clinton administration, sitting in a public federal database for 30 years most retail traders pay monthly subscriptions to signal services built by people who just learned to read a government XML file the data was never hidden. it just required knowing where to look
0:55

since 1993, hedge funds over $100M have been legally required to publish every position they hold 4 times a year, exact stocks and exact share counts, all of it free on the SEC website i spent 6 months asking one question with python: what happens when 4 or more separate funds all show up with new positions in the same small-cap stock in the same quarter - before the price has moved? backtested 2,400 signals from 2019 to 2025 67% win rate, 18.4% average gain per trade, 31 day average hold the reason the edge exists is the same reason the funds themselves can't collect it an $8B fund building a position in a $400M company moves the price against itself the second it starts buying so they file 45 days after the fact, the window opens, and nobody's standing in it running it live since february - 11 closed trades, 9 winners, +31% while the s&p returned 8% in the same period setup cost: a free API key from SEC EDGAR and one saturday morning this isn't an edge i found by being smart. it's an edge that only exists because the people publishing it are too large to use it themselves Bookmark before it get losted the filing requirement has been law since the clinton administration, sitting in a public federal database for 30 years most retail traders pay monthly subscriptions to signal services built by people who just learned to read a government XML file the data was never hidden. it just required knowing where to look

Livsun

32,072 views • 2 months ago

market opens at 9:30am his trade was already in at 4am neural net trained on 11 years of tick data called that setup 5 hours before candle even formed he's not smarter than the market. just built something that reads patterns human eyes can't process fast enough 4,200 data points per second, 847,000 labeled historical setups, running on a $40/mo server surfaces 3-4 trades a day. he takes top 2 last 90 days: 71% win rate, 2.3 avg risk/reward while retail traders watch news at open, this system already decided before sunrise you're not losing because your analysis is wrong you're losing because you're competing with something that doesn't sleep, panic or second-guess itself most people think this requires a PhD and a $2M quant desk he built his whole setup for under $500 using a free dataset and 3 weeks of evenings Bookmark this setup edge was never hidden behind a paywall or locked inside a fund it was sitting in a format nobody bothered to train on
0:32

market opens at 9:30am his trade was already in at 4am neural net trained on 11 years of tick data called that setup 5 hours before candle even formed he's not smarter than the market. just built something that reads patterns human eyes can't process fast enough 4,200 data points per second, 847,000 labeled historical setups, running on a $40/mo server surfaces 3-4 trades a day. he takes top 2 last 90 days: 71% win rate, 2.3 avg risk/reward while retail traders watch news at open, this system already decided before sunrise you're not losing because your analysis is wrong you're losing because you're competing with something that doesn't sleep, panic or second-guess itself most people think this requires a PhD and a $2M quant desk he built his whole setup for under $500 using a free dataset and 3 weeks of evenings Bookmark this setup edge was never hidden behind a paywall or locked inside a fund it was sitting in a format nobody bothered to train on

Livsun

70,370 views • 3 months ago

quant funds spend millions hiring people who know a formula you learned in 10th grade and never applied to a price chart y = mx + b. that's it linear regression - same math from high school most traders learned, ignored, and forgot existed what quants actually figured out: asset prices don't move randomly, they drift and revert with measurable slope regression separates signal from noise. slope tracks trend, residuals measure the deviation when deviation gets large enough, that's the trade - prices tend to snap back to the line quants call it "mean reversion." retail calls it "a dip" actual workflow: > pull 5 years of daily returns > run OLS, extract beta and residuals > z-score the residuals > entries at -2 standard deviations, exits at 0 retail draws trend lines by hand and calls it analysis Bookmark this ^ data is public, math is free, approach has been in papers since the 1980s 99% of traders have never built one signal this way it was never an information gap - always been a methodology gap, and that's the kind that compounds
1:01

quant funds spend millions hiring people who know a formula you learned in 10th grade and never applied to a price chart y = mx + b. that's it linear regression - same math from high school most traders learned, ignored, and forgot existed what quants actually figured out: asset prices don't move randomly, they drift and revert with measurable slope regression separates signal from noise. slope tracks trend, residuals measure the deviation when deviation gets large enough, that's the trade - prices tend to snap back to the line quants call it "mean reversion." retail calls it "a dip" actual workflow: > pull 5 years of daily returns > run OLS, extract beta and residuals > z-score the residuals > entries at -2 standard deviations, exits at 0 retail draws trend lines by hand and calls it analysis Bookmark this ^ data is public, math is free, approach has been in papers since the 1980s 99% of traders have never built one signal this way it was never an information gap - always been a methodology gap, and that's the kind that compounds

Livsun

28,936 views • 2 months ago

MIT defines an algorithm in one sentence that changes how you think about trading "a computational procedure that takes an input and produces an output through a well-defined sequence of steps" that's it. not AI. not machine learning. not a black box a set of rules that takes data in and spits a decision out every quant strategy ever built is just an algorithm Citadel's execution system that routes 40% of US equity volume is an algorithm Renaissance's Medallion Fund running millions of trades per year is an algorithm Jane Street's market making engine processing $26 trillion annually is an algorithm input: market data rules: mathematical conditions output: trade or no trade the difference between a quant desk and a retail trader is not the data it's that one side wrote down their rules precisely enough for a machine to execute them retail says "if RSI is low and the chart looks good, i'll probably buy" a quant desk says "if RSI 1.5, buy 0.3% of NAV" same logic. one is a feeling. the other is an algorithm the feeling can't be tested, can't be repeated, can't be measured the algorithm can be backtested across 10,000 trades and you know exactly when it works and when it doesn't > this lecture: MIT, free, 70 seconds > algorithmic trading volume: 60-75% of all US equity trades > Jane Street, Citadel, Two Sigma: every trade is algorithmically executed > tools to build your own: Python, free data, a laptop you don't need a faster computer or better data you need to write your strategy down precisely enough that a machine could run it without you that's the whole leap. from intuition to algorithm full breakdown in the video below
1:10

MIT defines an algorithm in one sentence that changes how you think about trading "a computational procedure that takes an input and produces an output through a well-defined sequence of steps" that's it. not AI. not machine learning. not a black box a set of rules that takes data in and spits a decision out every quant strategy ever built is just an algorithm Citadel's execution system that routes 40% of US equity volume is an algorithm Renaissance's Medallion Fund running millions of trades per year is an algorithm Jane Street's market making engine processing $26 trillion annually is an algorithm input: market data rules: mathematical conditions output: trade or no trade the difference between a quant desk and a retail trader is not the data it's that one side wrote down their rules precisely enough for a machine to execute them retail says "if RSI is low and the chart looks good, i'll probably buy" a quant desk says "if RSI 1.5, buy 0.3% of NAV" same logic. one is a feeling. the other is an algorithm the feeling can't be tested, can't be repeated, can't be measured the algorithm can be backtested across 10,000 trades and you know exactly when it works and when it doesn't > this lecture: MIT, free, 70 seconds > algorithmic trading volume: 60-75% of all US equity trades > Jane Street, Citadel, Two Sigma: every trade is algorithmically executed > tools to build your own: Python, free data, a laptop you don't need a faster computer or better data you need to write your strategy down precisely enough that a machine could run it without you that's the whole leap. from intuition to algorithm full breakdown in the video below

delost

23,905 views • 2 months ago

One man turned $20 million into $14 billion in thirteen years. he retired at 46. then he walked into the National Press Club and explained the entire method to a room of journalists. for free. the fund industry has spent thirty years pretending nobody recorded it. his name is Peter Lynch. he ran Fidelity's Magellan Fund from 1977 to 1990. 29% a year. every year. when he started, the fund had $20 million. when he left, it was the largest mutual fund on earth. over a million shareholders. then he quit, walked away from billions in fees, and never managed outside money again. the first thing he says is the one rule Wall Street will never teach you. if you cannot explain to a ten-year-old in two minutes why you own a stock, you should not own it. he says 80% of people who own stocks cannot do this. then he explains why the number has not changed in thirty years. he did not use algorithms. he did not use quant models. he found stocks at the mall. at the grocery store. in his own neighborhood. he made more money on Dunkin' Donuts than on any sophisticated trade. the most boring companies with the simplest products, bought by a man who actually used them. the part nobody repeats: he says individual investors have a structural advantage over every institution on Wall Street. the funds are forced to follow rules that you are not. when they panic-sell, you benefit. when they cannot hold a small position, you can. he said this to a room full of financial journalists. not one of them ran the story. your financial advisor charges 1% of everything you own every year to underperform a method a retired fund manager gave away in one hour. there are 5,000 mutual funds competing for your money. the man who beat all of them told you exactly how. thirty years ago. the lecture is 61 minutes. it has been free since 1994. the people charging you to invest are hoping you never find it.
1:00:51

One man turned $20 million into $14 billion in thirteen years. he retired at 46. then he walked into the National Press Club and explained the entire method to a room of journalists. for free. the fund industry has spent thirty years pretending nobody recorded it. his name is Peter Lynch. he ran Fidelity's Magellan Fund from 1977 to 1990. 29% a year. every year. when he started, the fund had $20 million. when he left, it was the largest mutual fund on earth. over a million shareholders. then he quit, walked away from billions in fees, and never managed outside money again. the first thing he says is the one rule Wall Street will never teach you. if you cannot explain to a ten-year-old in two minutes why you own a stock, you should not own it. he says 80% of people who own stocks cannot do this. then he explains why the number has not changed in thirty years. he did not use algorithms. he did not use quant models. he found stocks at the mall. at the grocery store. in his own neighborhood. he made more money on Dunkin' Donuts than on any sophisticated trade. the most boring companies with the simplest products, bought by a man who actually used them. the part nobody repeats: he says individual investors have a structural advantage over every institution on Wall Street. the funds are forced to follow rules that you are not. when they panic-sell, you benefit. when they cannot hold a small position, you can. he said this to a room full of financial journalists. not one of them ran the story. your financial advisor charges 1% of everything you own every year to underperform a method a retired fund manager gave away in one hour. there are 5,000 mutual funds competing for your money. the man who beat all of them told you exactly how. thirty years ago. the lecture is 61 minutes. it has been free since 1994. the people charging you to invest are hoping you never find it.

Tigerflow

258,968 views • 18 days ago

Claude Shannon ran his personal stock account at 28% a year for 30 years. He's also the man who mathematically proved the ceiling above every filter the thread above is selling. Both facts have been sitting in the same library since 1948. Shannon didn't beat the market with a smarter moving average. He didn't beat it with a swarm, a neural net, or the sharpest filter of his generation, and he could have built any of them in an afternoon. He beat it because he understood the one thing the industry has been quietly ignoring for 78 years: no filter, no matter how clever, can pull more signal from a channel than the channel actually holds. The market channel is almost pure noise by design. Every real edge gets arbitraged toward zero the moment enough people find it. A better filter doesn't create signal that wasn't there - it rounds noise into a shape that fools you into betting on it. Shannon compounded like that because he was ruthless about which channels still had signal left, and disciplined about how much to bet when they did. The filter came last. It always comes last. Build the filter. It's a fine tool. Just remember there's a ceiling above it no engineering can lift, and the part that finds signal before it decays - that part, you still have to bring yourself. Shannon wrote it down in 1948. It's still free. The lesson has been sitting there for 78 years.
29:44

Claude Shannon ran his personal stock account at 28% a year for 30 years. He's also the man who mathematically proved the ceiling above every filter the thread above is selling. Both facts have been sitting in the same library since 1948. Shannon didn't beat the market with a smarter moving average. He didn't beat it with a swarm, a neural net, or the sharpest filter of his generation, and he could have built any of them in an afternoon. He beat it because he understood the one thing the industry has been quietly ignoring for 78 years: no filter, no matter how clever, can pull more signal from a channel than the channel actually holds. The market channel is almost pure noise by design. Every real edge gets arbitraged toward zero the moment enough people find it. A better filter doesn't create signal that wasn't there - it rounds noise into a shape that fools you into betting on it. Shannon compounded like that because he was ruthless about which channels still had signal left, and disciplined about how much to bet when they did. The filter came last. It always comes last. Build the filter. It's a fine tool. Just remember there's a ceiling above it no engineering can lift, and the part that finds signal before it decays - that part, you still have to bring yourself. Shannon wrote it down in 1948. It's still free. The lesson has been sitting there for 78 years.

Veles

207,290 views • 1 month ago

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.
1:00:07

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

151,219 views • 1 month ago

A lot of people still don’t understand how ruthless systematic trading can be. This is exactly why I run a quant fund alongside everything else I do. The quant fund is built to measure momentum on the 4 hour timeframe. Nothing more. Nothing less. No opinions. No emotions. No discretion. It tracks 15 core stocks and follows the same rule set every single time. When the 4 hour signal line turns green and increases, it buys. When it rolls over and turns red, it exits. Period. This fund does not care what I think. It does not care what I want. It does not care about headlines, FOMC, earnings or narratives. It follows the signal to a T. That’s what makes it so powerful. This is completely separate from my main fund, which is longer term positioning based on monthly and weekly signal lines across sectors. It’s also completely separate from my options trades, which are built around a 2–3 month outlook and larger macro structure. Three different approaches. Three different time horizons. Three different objectives. The quant fund exists for one reason. To systematically capture short term momentum while removing every human weakness that causes traders to fail. The part most people can’t handle? They want to intervene. They want to override. They want to “feel” their way through it. Quant trading doesn’t allow that and that’s why it works. If you want discretion, opinions and emotion… this isn’t for you. If you want structure, probability and discipline… this is how accounts actually compound. That’s everything you need to know about my quant fund and the 4 hour signal line that drives it. THANK YOU FOR YOUR ATTENTION TO THIS MATTER! — TJ #SP500 #SPY #QQQ #TSLA #PLTR #NVDA #AAPL #Bitcoin #Crypto #StockMarket
16:50

A lot of people still don’t understand how ruthless systematic trading can be. This is exactly why I run a quant fund alongside everything else I do. The quant fund is built to measure momentum on the 4 hour timeframe. Nothing more. Nothing less. No opinions. No emotions. No discretion. It tracks 15 core stocks and follows the same rule set every single time. When the 4 hour signal line turns green and increases, it buys. When it rolls over and turns red, it exits. Period. This fund does not care what I think. It does not care what I want. It does not care about headlines, FOMC, earnings or narratives. It follows the signal to a T. That’s what makes it so powerful. This is completely separate from my main fund, which is longer term positioning based on monthly and weekly signal lines across sectors. It’s also completely separate from my options trades, which are built around a 2–3 month outlook and larger macro structure. Three different approaches. Three different time horizons. Three different objectives. The quant fund exists for one reason. To systematically capture short term momentum while removing every human weakness that causes traders to fail. The part most people can’t handle? They want to intervene. They want to override. They want to “feel” their way through it. Quant trading doesn’t allow that and that’s why it works. If you want discretion, opinions and emotion… this isn’t for you. If you want structure, probability and discipline… this is how accounts actually compound. That’s everything you need to know about my quant fund and the 4 hour signal line that drives it. THANK YOU FOR YOUR ATTENTION TO THIS MATTER! — TJ #SP500 #SPY #QQQ #TSLA #PLTR #NVDA #AAPL #Bitcoin #Crypto #StockMarket

TraderJonesy

43,814 views • 7 months ago

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.
1:00:58

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 views • 1 month ago

Stephen Boyd, Stanford professor: "Citadel will pay a 22 year old $400K to run this optimizer. The textbook that teaches it is free, and so was my course." this free stanford lecture holds the entire "optimal portfolio, perfect allocation" secret the trading gurus sell you. and the man teaching it didn't lock it inside a fund, he gave away the whole course and a textbook that costs $0. at the board it's simple: once you can write down your expected return, your risk, and your limits, convex optimization finds the single best portfolio, provably, not by trial and error. that's how a fund turns a messy pile of signals into one clean allocation. no guru required. it's not new either. boyd and vandenberghe's textbook has been free since 2004. same stack i mapped in the article above, old and free and sitting on a website the whole time. here's the honest part the course skips: the optimizer only allocates the edge you feed it. garbage in, garbage out. it can't invent an advantage that isn't already in your signals, it just sizes the real one without blowing you up. the solver is free. having an actual edge to optimize is the part nobody can sell you.
1:18:11

Stephen Boyd, Stanford professor: "Citadel will pay a 22 year old $400K to run this optimizer. The textbook that teaches it is free, and so was my course." this free stanford lecture holds the entire "optimal portfolio, perfect allocation" secret the trading gurus sell you. and the man teaching it didn't lock it inside a fund, he gave away the whole course and a textbook that costs $0. at the board it's simple: once you can write down your expected return, your risk, and your limits, convex optimization finds the single best portfolio, provably, not by trial and error. that's how a fund turns a messy pile of signals into one clean allocation. no guru required. it's not new either. boyd and vandenberghe's textbook has been free since 2004. same stack i mapped in the article above, old and free and sitting on a website the whole time. here's the honest part the course skips: the optimizer only allocates the edge you feed it. garbage in, garbage out. it can't invent an advantage that isn't already in your signals, it just sizes the real one without blowing you up. the solver is free. having an actual edge to optimize is the part nobody can sell you.

Rossst.03

72,607 views • 2 months ago

A basic VPS runs $20-40 a month at most providers. This GitHub README has been telling people how to get the same thing for $0 since 2015. > It's called free-for-dev. 132k stars, still maintained daily, 1600+ people adding new free tiers and killing dead ones every week. Not 14-day trials. The rule: if it's not free for at least a year, it doesn't make the list. Inside: → Oracle Cloud - 2 servers, 12GB RAM, free forever, no time limit → AWS Lambda - run code 1 million times a month before you pay a cent → Cloudflare - unlimited websites, DNS, SSL, and a global CDN, free → Google Cloud Run - 2 million requests a month on the house One rule they never break: if the security certificate isn't free too, it gets deleted from the list. Every side project starts with the same 20 minutes of Googling "is this actually free." This repo already did that search for you, and keeps redoing it every week. Bookmark it before your next project makes you do that search all over again.
1:44

A basic VPS runs $20-40 a month at most providers. This GitHub README has been telling people how to get the same thing for $0 since 2015. > It's called free-for-dev. 132k stars, still maintained daily, 1600+ people adding new free tiers and killing dead ones every week. Not 14-day trials. The rule: if it's not free for at least a year, it doesn't make the list. Inside: → Oracle Cloud - 2 servers, 12GB RAM, free forever, no time limit → AWS Lambda - run code 1 million times a month before you pay a cent → Cloudflare - unlimited websites, DNS, SSL, and a global CDN, free → Google Cloud Run - 2 million requests a month on the house One rule they never break: if the security certificate isn't free too, it gets deleted from the list. Every side project starts with the same 20 minutes of Googling "is this actually free." This repo already did that search for you, and keeps redoing it every week. Bookmark it before your next project makes you do that search all over again.

Atenov int.

176,102 views • 11 days ago