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a risk analyst at two sigma told me something over drinks i still think about "our models are right 54% of the time. retail models can be right 60% and still blow up" i asked him why "you trade every day. we don't" two sigma sits completely flat roughly...

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Livsun

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120,252 次观看 • 1 个月前 •via X (Twitter)

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a quant at Two Sigma told me something at a bar i can't stop thinking about "retail looks at price. we look at the autocorrelation of price changes - completely different signal" i asked him to explain it like i was 12 he drew on a napkin: if today's move predicts tomorrow's move - even slightly, 53% of the time - that's an edge that edge, sized with Kelly, compounds into something insane data is free - Bloomberg and the Fed publish all of it. math takes a weekend to learn reason retail loses isn't intelligence. it's that they're reading the wrong representation of the same data "a chart hides serial correlation. a time series shows it naked" went home, ran autocorrelation tests on 3 years of SPY data found 4 patterns - statistically significant, all exploitable on a 5-day window signals aren't perfect, right 58% of the time. Kelly says that's enough data was free the whole time, framework sitting in every stats textbook. nobody pointed retail toward it they kept you staring at candles
0:29

a quant at Two Sigma told me something at a bar i can't stop thinking about "retail looks at price. we look at the autocorrelation of price changes - completely different signal" i asked him to explain it like i was 12 he drew on a napkin: if today's move predicts tomorrow's move - even slightly, 53% of the time - that's an edge that edge, sized with Kelly, compounds into something insane data is free - Bloomberg and the Fed publish all of it. math takes a weekend to learn reason retail loses isn't intelligence. it's that they're reading the wrong representation of the same data "a chart hides serial correlation. a time series shows it naked" went home, ran autocorrelation tests on 3 years of SPY data found 4 patterns - statistically significant, all exploitable on a 5-day window signals aren't perfect, right 58% of the time. Kelly says that's enough data was free the whole time, framework sitting in every stats textbook. nobody pointed retail toward it they kept you staring at candles

Livsun

149,183 次观看 • 2 个月前

most powerful market regime tool on earth was invented to study nile river floods harold hurst published it in 1951. wall street found it decades later, buried it, never told retail the hurst exponent: one number between 0 and 1 below 0.5 means reversion, above 0.5 means market has memory and trends, at 0.5 you're flipping coins run it on SPY over a 90-day rolling window and you instantly know which playbook to use when it reads 0.38 you fade every breakout, when it reads 0.61 you buy every pullback i ran this on 4 years of daily closes - 40 lines of python, free data momentum in a trending regime: 64% win rate mean-reversion in a reverting regime: 71% when exponent sits between 0.45 and 0.55 - both strategies lose, that's the chop zone nobody tells you to sit on your hands there most retail traders aren't wrong about direction. they're wrong about regime bookmark this before your trading group figures it out edge isn't knowing where price is going - it's knowing what kind of market you're already in
0:30

most powerful market regime tool on earth was invented to study nile river floods harold hurst published it in 1951. wall street found it decades later, buried it, never told retail the hurst exponent: one number between 0 and 1 below 0.5 means reversion, above 0.5 means market has memory and trends, at 0.5 you're flipping coins run it on SPY over a 90-day rolling window and you instantly know which playbook to use when it reads 0.38 you fade every breakout, when it reads 0.61 you buy every pullback i ran this on 4 years of daily closes - 40 lines of python, free data momentum in a trending regime: 64% win rate mean-reversion in a reverting regime: 71% when exponent sits between 0.45 and 0.55 - both strategies lose, that's the chop zone nobody tells you to sit on your hands there most retail traders aren't wrong about direction. they're wrong about regime bookmark this before your trading group figures it out edge isn't knowing where price is going - it's knowing what kind of market you're already in

Livsun

15,785 次观看 • 13 天前

a researcher at a systematic fund showed me a 6x6 matrix on a whiteboard said: > this is our whole system. we don't forecast price. we classify which cell the market occupies and where that cell historically transitions i stared at it for days before it made sense. then everything changed never interpreted a chart the same way again the matrix is called a Markov Chain transition table. the theory dates back to 1913, it's in every introductory statistics textbook ever written and systematic funds rely on it because it poses a fundamentally different question than what retail traders ever think to ask retail: is this going higher or lower systematic: what regime is this market in, and where does this regime historically resolve every market sits in one of roughly 4-6 regimes at any point in time narrow consolidation, expanding volatility, trending with acceleration, post-reversal drift, pre-expansion squeeze not arbitrary categories - clusters you extract from real data using volatility, volume, and trend strength layered together once you define the regimes, you construct the table: P(regime 3 → regime 5) = 71% P(regime 1 → regime 3) = 64% P(regime 2 → regime 4) = 69% each cell is a historical frequency. now when the market sits in regime 3, you're not speculating you're trading on 71% historical resolution. you scale it with Kelly. you execute when the math confirms, not when it feels convincing i constructed this on ETH using 3 years of 1-hour data. isolated 6 regimes one i named "volatility squeeze below 15-day average for 8+ consecutive bars" transitioned to a directional breakout exceeding 2.2 ATR in 74% of cases average reward/risk on those setups: 4.8 that's not forecasting. that's reading a probability matrix the market populates for you every single session the part that should concern you: the data to construct this is free. the methodology is in any quantitative finance textbook python to build it is maybe 180 lines what Citadel has that you don't isn't classified data or secret algorithms it's this methodology applied to tick-level data with more granular regime definitions you're not lacking information you're framing the wrong question every single time you open a chart
0:26

a researcher at a systematic fund showed me a 6x6 matrix on a whiteboard said: > this is our whole system. we don't forecast price. we classify which cell the market occupies and where that cell historically transitions i stared at it for days before it made sense. then everything changed never interpreted a chart the same way again the matrix is called a Markov Chain transition table. the theory dates back to 1913, it's in every introductory statistics textbook ever written and systematic funds rely on it because it poses a fundamentally different question than what retail traders ever think to ask retail: is this going higher or lower systematic: what regime is this market in, and where does this regime historically resolve every market sits in one of roughly 4-6 regimes at any point in time narrow consolidation, expanding volatility, trending with acceleration, post-reversal drift, pre-expansion squeeze not arbitrary categories - clusters you extract from real data using volatility, volume, and trend strength layered together once you define the regimes, you construct the table: P(regime 3 → regime 5) = 71% P(regime 1 → regime 3) = 64% P(regime 2 → regime 4) = 69% each cell is a historical frequency. now when the market sits in regime 3, you're not speculating you're trading on 71% historical resolution. you scale it with Kelly. you execute when the math confirms, not when it feels convincing i constructed this on ETH using 3 years of 1-hour data. isolated 6 regimes one i named "volatility squeeze below 15-day average for 8+ consecutive bars" transitioned to a directional breakout exceeding 2.2 ATR in 74% of cases average reward/risk on those setups: 4.8 that's not forecasting. that's reading a probability matrix the market populates for you every single session the part that should concern you: the data to construct this is free. the methodology is in any quantitative finance textbook python to build it is maybe 180 lines what Citadel has that you don't isn't classified data or secret algorithms it's this methodology applied to tick-level data with more granular regime definitions you're not lacking information you're framing the wrong question every single time you open a chart

Hrundel75 🐷

12,088 次观看 • 27 天前

a quant at a prop firm showed me a 5x5 grid on a napkin said: > this is our entire edge. we don't predict price. we predict which box the market is in and where that box historically leads i didn't understand it for weeks. then it clicked never looked at a chart the same way since grid is called a Markov Chain transition matrix. the math is from 1906, it's in every probability textbook on earth and hedge funds use it because it asks a completely different question than retail traders ever ask retail: will this go up or down quant: what state is this market in, and where does this state typically go every market lives in one of maybe 5-6 states at any given moment tight range, volatility compression, trending with momentum, post-spike reversal, pre-breakout coil not random labels - clusters you identify from actual data using volatility, volume, and momentum readings stacked together once you have the states, you build the matrix: P(state 2 -> state 4) = 73% P(state 4 -> state 1) = 61% P(state 1 -> state 3) = 68% each cell is a historical probability. now when the market is in state 2, you're not guessing you're betting on 73% historical completion. you size it with Kelly. you take the trade when the math says to, not when it feels right i built this on BTC using 2 years of 4-hour data. identified 5 states one i labeled "volatility compression below 20-day mean for 6+ consecutive candles" transitioned to a directional move above 1.8 ATR in 71% of cases average reward/risk on those trades: 5.4 that's not prediction. that's reading a probability table the market keeps filling in for you every single day the part that should bother you: the data to build this is free. the framework is in any quant textbook python to implement it is maybe 200 lines what Renaissance Technologies has that you don't isn't secret data or proprietary signals it's this framework applied to higher-resolution data with more sophisticated state definitions you're not missing information you're asking the wrong question every single time you open a chart
0:26

a quant at a prop firm showed me a 5x5 grid on a napkin said: > this is our entire edge. we don't predict price. we predict which box the market is in and where that box historically leads i didn't understand it for weeks. then it clicked never looked at a chart the same way since grid is called a Markov Chain transition matrix. the math is from 1906, it's in every probability textbook on earth and hedge funds use it because it asks a completely different question than retail traders ever ask retail: will this go up or down quant: what state is this market in, and where does this state typically go every market lives in one of maybe 5-6 states at any given moment tight range, volatility compression, trending with momentum, post-spike reversal, pre-breakout coil not random labels - clusters you identify from actual data using volatility, volume, and momentum readings stacked together once you have the states, you build the matrix: P(state 2 -> state 4) = 73% P(state 4 -> state 1) = 61% P(state 1 -> state 3) = 68% each cell is a historical probability. now when the market is in state 2, you're not guessing you're betting on 73% historical completion. you size it with Kelly. you take the trade when the math says to, not when it feels right i built this on BTC using 2 years of 4-hour data. identified 5 states one i labeled "volatility compression below 20-day mean for 6+ consecutive candles" transitioned to a directional move above 1.8 ATR in 71% of cases average reward/risk on those trades: 5.4 that's not prediction. that's reading a probability table the market keeps filling in for you every single day the part that should bother you: the data to build this is free. the framework is in any quant textbook python to implement it is maybe 200 lines what Renaissance Technologies has that you don't isn't secret data or proprietary signals it's this framework applied to higher-resolution data with more sophisticated state definitions you're not missing information you're asking the wrong question every single time you open a chart

Livsun

188,258 次观看 • 2 个月前

citadel doesn't analyze 500 stocks they compress them to 5 hidden forces - then trade the forces most people saw the math behind this in a stats class and scrolled past it. nobody told them it was worth $30 billion a year technique is called PCA - principal component analysis Karl Pearson published it in 1901 in a free journal. it's in every stats textbook on earth here's what it does: you feed it 10 years of daily returns across 500 stocks it ignores earnings reports, management teams, every narrative retail obsesses over it finds underlying forces moving groups of stocks together without anyone naming them what comes out: > component 1 - broad market direction (~45% of all movement) > 2 - growth vs value tilt (~12%) > 3 - sector rotation (~8%) > 4 - volatility regime (~5%) > 5 - liquidity premium (~3%) five numbers explain 73% of everything moving in markets a quant desk doesn't ask "will NVDA go up tomorrow" it asks: which regime are we in, and where does this regime historically lead portfolio built around forces, not tickers if component 3 signals sector rotation at a historical inflection, they rotate without reading a single 10-K Two Sigma runs this across equities, bonds, commodities and currencies simultaneously Save this before someone turns it into a $2,000 data to build this is free - Ken French's factor library, CRSP, any linear algebra textbook 150 lines of python is the whole engine what Renaissance has isn't secret data or better intel
0:56

citadel doesn't analyze 500 stocks they compress them to 5 hidden forces - then trade the forces most people saw the math behind this in a stats class and scrolled past it. nobody told them it was worth $30 billion a year technique is called PCA - principal component analysis Karl Pearson published it in 1901 in a free journal. it's in every stats textbook on earth here's what it does: you feed it 10 years of daily returns across 500 stocks it ignores earnings reports, management teams, every narrative retail obsesses over it finds underlying forces moving groups of stocks together without anyone naming them what comes out: > component 1 - broad market direction (~45% of all movement) > 2 - growth vs value tilt (~12%) > 3 - sector rotation (~8%) > 4 - volatility regime (~5%) > 5 - liquidity premium (~3%) five numbers explain 73% of everything moving in markets a quant desk doesn't ask "will NVDA go up tomorrow" it asks: which regime are we in, and where does this regime historically lead portfolio built around forces, not tickers if component 3 signals sector rotation at a historical inflection, they rotate without reading a single 10-K Two Sigma runs this across equities, bonds, commodities and currencies simultaneously Save this before someone turns it into a $2,000 data to build this is free - Ken French's factor library, CRSP, any linear algebra textbook 150 lines of python is the whole engine what Renaissance has isn't secret data or better intel

Livsun

21,476 次观看 • 1 个月前

hedge funds spent $2M to build what you could replicate in a weekend they just knew it was possible first - that was their only advantage a researcher at d.e. shaw handed me a paper in 2023 two years of quant labor, internal "discovery" - original source was an MIT lecture from 1998, public, free, searchable mechanism is cointegration two assets drift independently, but their spread behaves like a rubber band - stationary, mean-reverting, measurable retail asks: will this go up quant asks: is this spread 2.3 standard deviations outside its 5-year mean - and what's historical reversion rate from here completely different question. second one has an answer run it on GLD/GDX, SPY/QQQ, XLE/XOM - data goes back 20 years, free on yahoo finance spread reverts within 8 trading days 71% of the time when it crosses 2 sigma size with Kelly on that 71%, take the trade when math clears, exit at mean paper they spent two years on is engle & granger, 1987 - won a nobel prize Bookmark before it deleted it's in every econometrics textbook on earth, chapter 4 they didn't hide the math from you they just never told you it existed
1:02

hedge funds spent $2M to build what you could replicate in a weekend they just knew it was possible first - that was their only advantage a researcher at d.e. shaw handed me a paper in 2023 two years of quant labor, internal "discovery" - original source was an MIT lecture from 1998, public, free, searchable mechanism is cointegration two assets drift independently, but their spread behaves like a rubber band - stationary, mean-reverting, measurable retail asks: will this go up quant asks: is this spread 2.3 standard deviations outside its 5-year mean - and what's historical reversion rate from here completely different question. second one has an answer run it on GLD/GDX, SPY/QQQ, XLE/XOM - data goes back 20 years, free on yahoo finance spread reverts within 8 trading days 71% of the time when it crosses 2 sigma size with Kelly on that 71%, take the trade when math clears, exit at mean paper they spent two years on is engle & granger, 1987 - won a nobel prize Bookmark before it deleted it's in every econometrics textbook on earth, chapter 4 they didn't hide the math from you they just never told you it existed

Livsun

26,816 次观看 • 2 个月前

100 billion dollars made without predicting a single price direction not a direction call, a macro bet, or a news trade in sight they asked a completely different question than every retail trader alive retail: "will this go up?" quant: "what state is the market in, and where does that state historically lead?" same data. completely different game markets aren't random - they cycle through states: trending, ranging, compressing, reversing each state has a fixed historical probability of transitioning to the next that's the whole edge. not a signal, not an indicator - just conditional probability you don't need to know what fed will do or what earnings will print you need to know which state you're in and what that state leads to 68% of the time framework has been public since 1906 Bookmark it before it gone data is free, implementation is 200 lines of python, paper costs nothing they built 100 billion off math sitting in statistics textbooks your whole life you were staring at candles while they ran probability tables
0:52

100 billion dollars made without predicting a single price direction not a direction call, a macro bet, or a news trade in sight they asked a completely different question than every retail trader alive retail: "will this go up?" quant: "what state is the market in, and where does that state historically lead?" same data. completely different game markets aren't random - they cycle through states: trending, ranging, compressing, reversing each state has a fixed historical probability of transitioning to the next that's the whole edge. not a signal, not an indicator - just conditional probability you don't need to know what fed will do or what earnings will print you need to know which state you're in and what that state leads to 68% of the time framework has been public since 1906 Bookmark it before it gone data is free, implementation is 200 lines of python, paper costs nothing they built 100 billion off math sitting in statistics textbooks your whole life you were staring at candles while they ran probability tables

Livsun

13,335 次观看 • 2 个月前

a hydrologist studying the Nile river in 1951 accidentally solved trading harold hurst wasn't looking for alpha - he was trying to predict flood cycles what he found: one number that tells you whether any time series will trend, random-walk, or mean-revert quants call it the hurst exponent above 0.7 - market trends, momentum works, follow it around 0.5 - coin flip, no edge exists below 0.3 - mean-reverts, fade every move one number, calculated from free price data, tells you which strategy to even bother running citadel doesn't build one model for all regimes they run hurst on every asset every week and deploy the right model for that regime retail builds one indicator setup and wonders why it stops working that's not bad luck - that's physics paper has been free since 1951. python to calculate it is 12 lines. data costs nothing they kept you switching indicators while they ran regime detection on everything bookmark this before someone in your group figures it out first
0:30

a hydrologist studying the Nile river in 1951 accidentally solved trading harold hurst wasn't looking for alpha - he was trying to predict flood cycles what he found: one number that tells you whether any time series will trend, random-walk, or mean-revert quants call it the hurst exponent above 0.7 - market trends, momentum works, follow it around 0.5 - coin flip, no edge exists below 0.3 - mean-reverts, fade every move one number, calculated from free price data, tells you which strategy to even bother running citadel doesn't build one model for all regimes they run hurst on every asset every week and deploy the right model for that regime retail builds one indicator setup and wonders why it stops working that's not bad luck - that's physics paper has been free since 1951. python to calculate it is 12 lines. data costs nothing they kept you switching indicators while they ran regime detection on everything bookmark this before someone in your group figures it out first

Livsun

10,807 次观看 • 8 天前

a citadel quant told me something that broke my entire trading framework "we don't predict markets. we model the state machine" he explained markov chains in 90 seconds the market is never random - it always exists in one of three states trending up, trending down, ranging - each has a fixed probability of shifting to another build the transition matrix from real price data: > trending up -> 68% stays trending, 21% flips to range, 11% reverses > ranging -> 54% stays range, 28% breaks up, 18% breaks down > trending down -> 61% stays falling, 24% flips to range, 15% reverses now you're not guessing, you're playing probability identify current state, enter with the 68% edge, size with kelly criterion based on that probability the formula is public - markov published it in 1906 hedge funds use it, the math costs nothing what costs you is asking the wrong question "where is price going?" is random "what state am I in right now?" has an answer transition matrix built from 10 years of data is your edge Bookmark it not a signal, not an indicator - just conditional probability that compounds every single trade
0:40

a citadel quant told me something that broke my entire trading framework "we don't predict markets. we model the state machine" he explained markov chains in 90 seconds the market is never random - it always exists in one of three states trending up, trending down, ranging - each has a fixed probability of shifting to another build the transition matrix from real price data: > trending up -> 68% stays trending, 21% flips to range, 11% reverses > ranging -> 54% stays range, 28% breaks up, 18% breaks down > trending down -> 61% stays falling, 24% flips to range, 15% reverses now you're not guessing, you're playing probability identify current state, enter with the 68% edge, size with kelly criterion based on that probability the formula is public - markov published it in 1906 hedge funds use it, the math costs nothing what costs you is asking the wrong question "where is price going?" is random "what state am I in right now?" has an answer transition matrix built from 10 years of data is your edge Bookmark it not a signal, not an indicator - just conditional probability that compounds every single trade

Livsun

268,026 次观看 • 2 个月前

A warning to Americans about living under Sharia Law from a woman who used to live in Iran - “In Iran, you can get arrested for walking a dog and then they can take your dog away because according to Islam, dogs are najis, which means unclean - In Iran, you will get arrested. Not can, will if you're a female solo singer, it is against the law - I Iran, not that you have to wear hijab, but if your hijab is not to the liking of the regime forces, they can push you forcefully into a van and take you to jail. And then things that happen in those jails, let's just say that they're not ethical - In Iran, you are not allowed to change your religion or choose your religion. If you do so, you will be executed - In Iran, they would line us up as children force hijab on us and force us to chant Death to America. I wouldn't call that school. I would call that a cult that is trying to brainwash children into a terrorist mindset. - In Iran, there are stations with regime forces and they can stop your car and see if the person next to you is a girlfriend, a boyfriend, or you're married to. If you're married to them, you can get arrested in 5 years. Imagine that a Big Mac went from $6 to $600. That's exactly what happened in Iran. Well, roughly. I think it's even more than that. And everything. I'm telling you, it's not even the worst thing that's happening in Iran. Every time people request a regime change and they start to protest, the regime shuts off the internet and starts shooting people with military grade weapons, children. Regime forces in the past two to three weeks have killed more than 50,000 people. So yeah, if you have opinions about how Iranians should feel, perhaps you should go to Iran, live with the regime and maybe raise a child or two, and then we can speak about it.”
1:58

A warning to Americans about living under Sharia Law from a woman who used to live in Iran - “In Iran, you can get arrested for walking a dog and then they can take your dog away because according to Islam, dogs are najis, which means unclean - In Iran, you will get arrested. Not can, will if you're a female solo singer, it is against the law - I Iran, not that you have to wear hijab, but if your hijab is not to the liking of the regime forces, they can push you forcefully into a van and take you to jail. And then things that happen in those jails, let's just say that they're not ethical - In Iran, you are not allowed to change your religion or choose your religion. If you do so, you will be executed - In Iran, they would line us up as children force hijab on us and force us to chant Death to America. I wouldn't call that school. I would call that a cult that is trying to brainwash children into a terrorist mindset. - In Iran, there are stations with regime forces and they can stop your car and see if the person next to you is a girlfriend, a boyfriend, or you're married to. If you're married to them, you can get arrested in 5 years. Imagine that a Big Mac went from $6 to $600. That's exactly what happened in Iran. Well, roughly. I think it's even more than that. And everything. I'm telling you, it's not even the worst thing that's happening in Iran. Every time people request a regime change and they start to protest, the regime shuts off the internet and starts shooting people with military grade weapons, children. Regime forces in the past two to three weeks have killed more than 50,000 people. So yeah, if you have opinions about how Iranians should feel, perhaps you should go to Iran, live with the regime and maybe raise a child or two, and then we can speak about it.”

Wall Street Apes

503,860 次观看 • 5 个月前

gurus sold you a shovel, but edge is free guy in delaware who writes code for a top-3 crypto exchange told me why you're still down after 4 years of "learning" "the course and signal industry is a gold rush. except you're digging, and they sell the shovels" he explained it in 2 minutes every "guru" with a +400% screenshot doesn't make money on trades he makes money on you, who bought access for $997 mechanic that actually works has been public since 1990s regime filter. gamma exposure. funding rate. markov transition matrix he gave me his numbers: > 73% of "signal services" shut down within 14 months - after milking newcomers > same 3 formulas in a $2000 course sit in a free university pdf > gap between "dream course" and reality is 150 lines of python and 8 months of grinding, not 8 minutes of video you're not "a bad trader". you're being fed shovels while someone else digs the gold cheapest thing you can do is stop buying access and open a notebook data is free. formulas are published. code is 200 lines before you buy the next "signal", ask: who's selling the shovel here, and who's actually digging they didn't hide strategy from you they made you shovel-buyer while someone else took the nugget
1:08

gurus sold you a shovel, but edge is free guy in delaware who writes code for a top-3 crypto exchange told me why you're still down after 4 years of "learning" "the course and signal industry is a gold rush. except you're digging, and they sell the shovels" he explained it in 2 minutes every "guru" with a +400% screenshot doesn't make money on trades he makes money on you, who bought access for $997 mechanic that actually works has been public since 1990s regime filter. gamma exposure. funding rate. markov transition matrix he gave me his numbers: > 73% of "signal services" shut down within 14 months - after milking newcomers > same 3 formulas in a $2000 course sit in a free university pdf > gap between "dream course" and reality is 150 lines of python and 8 months of grinding, not 8 minutes of video you're not "a bad trader". you're being fed shovels while someone else digs the gold cheapest thing you can do is stop buying access and open a notebook data is free. formulas are published. code is 200 lines before you buy the next "signal", ask: who's selling the shovel here, and who's actually digging they didn't hide strategy from you they made you shovel-buyer while someone else took the nugget

Livsun

21,075 次观看 • 25 天前

renaissance technologies hasn't had a losing year since 1988 not because they're smarter or have better data they're asking a completely different question than everyone else while retail asks "will it go up?" quant desks ask something else entirely which state is the market in right now, and with what probability does it transition to the next tool for that: markov chains markets cycle through states - trending, ranging, volatile, reversing each transition has a historical probability you can calculate trending -> stays trending: 48% trending -> ranging: 34% trending -> reversing: 18% you don't pick direction. you calculate expected value across every possible transition enter only when the math is positive that's it. that's the entire edge the framework is 119 years old - andrei markov published it in 1906 it's in every statistics textbook on earth Bookmark it or lose last chance to be quant nobody in your trading group ever mentioned it
2:02

renaissance technologies hasn't had a losing year since 1988 not because they're smarter or have better data they're asking a completely different question than everyone else while retail asks "will it go up?" quant desks ask something else entirely which state is the market in right now, and with what probability does it transition to the next tool for that: markov chains markets cycle through states - trending, ranging, volatile, reversing each transition has a historical probability you can calculate trending -> stays trending: 48% trending -> ranging: 34% trending -> reversing: 18% you don't pick direction. you calculate expected value across every possible transition enter only when the math is positive that's it. that's the entire edge the framework is 119 years old - andrei markov published it in 1906 it's in every statistics textbook on earth Bookmark it or lose last chance to be quant nobody in your trading group ever mentioned it

Livsun

51,500 次观看 • 2 个月前

Two Sigma runs 500 stocks through one formula and looks at 5 numbers math has been public since 1901 PCA - principal component analysis - run it on the S&P and entire market compresses 87% of all price movement. 5 hidden variables not sectors, not earnings - 5 eigenvectors. the hidden skeleton underneath price > market pressure - a tide moving every name in sync > growth vs value rotation > size divergence, mega cap vs small cap > momentum regime - trending or mean reverting > volatility clustering when eigenvector 4 flips, every momentum strategy on earth breaks at the same time same force rotating under all 500 names at once - not coincidence, that's structure retail reads 500 charts. quant desks read 5 transitions data: free. code: 300 lines of python. framework: 1901 been sitting in every linear algebra textbook for 120 years they just never pointed you at the right chapter
2:14

Two Sigma runs 500 stocks through one formula and looks at 5 numbers math has been public since 1901 PCA - principal component analysis - run it on the S&P and entire market compresses 87% of all price movement. 5 hidden variables not sectors, not earnings - 5 eigenvectors. the hidden skeleton underneath price > market pressure - a tide moving every name in sync > growth vs value rotation > size divergence, mega cap vs small cap > momentum regime - trending or mean reverting > volatility clustering when eigenvector 4 flips, every momentum strategy on earth breaks at the same time same force rotating under all 500 names at once - not coincidence, that's structure retail reads 500 charts. quant desks read 5 transitions data: free. code: 300 lines of python. framework: 1901 been sitting in every linear algebra textbook for 120 years they just never pointed you at the right chapter

Livsun

13,957 次观看 • 1 个月前

🚨JOHN BOLTON VS AFSHIN RATTANSI: REGIME CHANGE IN IRAN Bolton: ‘I don’t think the war is over because I don’t think we’ve done the necessary work to solve the problem in the way I think it has to be solved, which is through regime change…but it’s not clear to me at this point that Trump really knows what his objective is.’ Afshin Rattansi: ‘What do you mean, regime change? I mean, you’d back ground forces going in?’ Bolton: ‘I don’t think it’s necessary. I think if you look at Iran, with I think a sophisticated, well-educated population, this regime was in trouble long before the war started. For years its economy has been in desperate straits. That’s what the people were demonstrating about all over Iran in December and January.’ Afshin: ‘The economic situation isn’t necessarily demonstrating a demand for a complete change of regime.’ Bolton: ‘Not only is the economy bad, they’re running out of water. The irrigation policies of the government to develop what Ayatollah Khomeini wanted, which was complete agricultural autonomy, has devastated the groundwater. They’re even talking about having to move the capital out of Tehran. That’s how bad it is.’ Afshin: ‘Flint, Michigan had polluted water, that’s not a reason for changing the regime in the United States.’ —Watch the full interview with John Bolton, Donald Trump’s former National Security Adviser in the quoted post below👇 John Bolton
2:09

🚨JOHN BOLTON VS AFSHIN RATTANSI: REGIME CHANGE IN IRAN Bolton: ‘I don’t think the war is over because I don’t think we’ve done the necessary work to solve the problem in the way I think it has to be solved, which is through regime change…but it’s not clear to me at this point that Trump really knows what his objective is.’ Afshin Rattansi: ‘What do you mean, regime change? I mean, you’d back ground forces going in?’ Bolton: ‘I don’t think it’s necessary. I think if you look at Iran, with I think a sophisticated, well-educated population, this regime was in trouble long before the war started. For years its economy has been in desperate straits. That’s what the people were demonstrating about all over Iran in December and January.’ Afshin: ‘The economic situation isn’t necessarily demonstrating a demand for a complete change of regime.’ Bolton: ‘Not only is the economy bad, they’re running out of water. The irrigation policies of the government to develop what Ayatollah Khomeini wanted, which was complete agricultural autonomy, has devastated the groundwater. They’re even talking about having to move the capital out of Tehran. That’s how bad it is.’ Afshin: ‘Flint, Michigan had polluted water, that’s not a reason for changing the regime in the United States.’ —Watch the full interview with John Bolton, Donald Trump’s former National Security Adviser in the quoted post below👇 John Bolton

New Order with Afshin Rattansi

23,226 次观看 • 3 个月前

Your strategy isn't losing because it's bad. It's losing because the market changed and nobody told you. Markets have moods: trend, chop, panic. Every strategy only works inside one of them. And when the mood flips, no bell rings. Your equity curve is the bell - by the time it rings, you're already down 30%. Quant desks don't wait for the bell. They run 120-year-old math, a Hidden Markov Model, that reads the market's hidden state live and calls the flip days before the chart shows it. Horizon packed that whole desk setup into one typed sentence. Public launch July 15 - get on the waitlist now: Here's the proof, from a real pair of runs. A BTC breakout kept shorting into an uptrend and finished -50.68%, the short book alone bleeding $75,836. The exact same idea, with one added sentence about the regime: +41.15%. Same entries. Same logic. A 91-point swing from one sentence. You don't have to build any of this. Horizon fits the model, watches the regime every bar, and switches your strategy on its own - you just describe what you want. Half your losing trades were probably this exact thing: right idea, wrong market, no way to see it. All this time you've been blaming your discipline, your entries, your psychology. The real question was one you never asked: what state is the market in right now? Bookmark this and read the full framework below - it's the exact regime math desks run on live money, written so you can use it Monday.
0:48

Your strategy isn't losing because it's bad. It's losing because the market changed and nobody told you. Markets have moods: trend, chop, panic. Every strategy only works inside one of them. And when the mood flips, no bell rings. Your equity curve is the bell - by the time it rings, you're already down 30%. Quant desks don't wait for the bell. They run 120-year-old math, a Hidden Markov Model, that reads the market's hidden state live and calls the flip days before the chart shows it. Horizon packed that whole desk setup into one typed sentence. Public launch July 15 - get on the waitlist now: Here's the proof, from a real pair of runs. A BTC breakout kept shorting into an uptrend and finished -50.68%, the short book alone bleeding $75,836. The exact same idea, with one added sentence about the regime: +41.15%. Same entries. Same logic. A 91-point swing from one sentence. You don't have to build any of this. Horizon fits the model, watches the regime every bar, and switches your strategy on its own - you just describe what you want. Half your losing trades were probably this exact thing: right idea, wrong market, no way to see it. All this time you've been blaming your discipline, your entries, your psychology. The real question was one you never asked: what state is the market in right now? Bookmark this and read the full framework below - it's the exact regime math desks run on live money, written so you can use it Monday.

cvxv666

98,041 次观看 • 1 个月前

every vol desk on wall street watches one number retail has never heard of gamma exposure - GEX when institutions buy options, market makers take the other side and hedge continuously by trading the underlying aggregate GEX tells you which direction those hedges point positive GEX: makers buy every dip, sell every rip - vol collapses, price pins between strikes negative GEX: makers sell into every dip, amplify every move - vol explodes, price runs further than it "should" flip in GEX sign precedes volatility regime change by 1-3 sessions, historically consistent data is on cboe's website, free, updated daily - open interest by strike for every listed option formula: sum(gamma x open_interest x spot^2 x 0.01) across all strikes and expirations 100 lines of python, tested back to 2018 regime classification: correct 79% of sessions you don't need perfect accuracy - size correctly when math confirms the regime and compounding does the rest bookmark this retail was watching RSI while market makers mechanically amplified every move edge was never secret. nobody told you the question to ask
0:30

every vol desk on wall street watches one number retail has never heard of gamma exposure - GEX when institutions buy options, market makers take the other side and hedge continuously by trading the underlying aggregate GEX tells you which direction those hedges point positive GEX: makers buy every dip, sell every rip - vol collapses, price pins between strikes negative GEX: makers sell into every dip, amplify every move - vol explodes, price runs further than it "should" flip in GEX sign precedes volatility regime change by 1-3 sessions, historically consistent data is on cboe's website, free, updated daily - open interest by strike for every listed option formula: sum(gamma x open_interest x spot^2 x 0.01) across all strikes and expirations 100 lines of python, tested back to 2018 regime classification: correct 79% of sessions you don't need perfect accuracy - size correctly when math confirms the regime and compounding does the rest bookmark this retail was watching RSI while market makers mechanically amplified every move edge was never secret. nobody told you the question to ask

Livsun

14,993 次观看 • 8 天前

Your trading strategy didn't break. The market it was built for quietly stopped existing. Read that twice. It's most of why 89% of retail finished 2025 in the red. There's now an app that does the entire job of a $400,000 quant. You type a trading idea in plain English. It writes the code, backtests 5 years in 12 seconds, runs thousands of simulations, and tells you cold whether your edge is dead or the regime just changed. No code. No Python. No $25,000 terminal. 20,000 already inside. Waitlist stops at 25,000: That distinction is the whole game, and you never had a way to see it. Every strategy is a bet that one thing stays true. Momentum bets trends continue. Mean reversion bets ranges hold. When the regime flips, the assumption dies and your strategy bleeds with nothing wrong in the code. You stare at the logic for a month and never find the bug, because there isn't one. So you delete it, or refit it to the last drawdown and build something that would have survived the pain you already felt and nothing coming next. The desks never had that problem. 92% of institutional volume is automated. Only 45% of retail is. They test 100 strategies for every 1 you test by hand, and kill 97 of them on purpose, because they can tell a dead edge from a normal drawdown. Now that exact loop costs $0. One hypothesis used to cost a fund $87,500 to test. With Horizon you get unlimited, in seconds, and a winner deploys live in 90 seconds and runs without your hands on it.
0:40

Your trading strategy didn't break. The market it was built for quietly stopped existing. Read that twice. It's most of why 89% of retail finished 2025 in the red. There's now an app that does the entire job of a $400,000 quant. You type a trading idea in plain English. It writes the code, backtests 5 years in 12 seconds, runs thousands of simulations, and tells you cold whether your edge is dead or the regime just changed. No code. No Python. No $25,000 terminal. 20,000 already inside. Waitlist stops at 25,000: That distinction is the whole game, and you never had a way to see it. Every strategy is a bet that one thing stays true. Momentum bets trends continue. Mean reversion bets ranges hold. When the regime flips, the assumption dies and your strategy bleeds with nothing wrong in the code. You stare at the logic for a month and never find the bug, because there isn't one. So you delete it, or refit it to the last drawdown and build something that would have survived the pain you already felt and nothing coming next. The desks never had that problem. 92% of institutional volume is automated. Only 45% of retail is. They test 100 strategies for every 1 you test by hand, and kill 97 of them on purpose, because they can tell a dead edge from a normal drawdown. Now that exact loop costs $0. One hypothesis used to cost a fund $87,500 to test. With Horizon you get unlimited, in seconds, and a winner deploys live in 90 seconds and runs without your hands on it.

cvxv666

40,749 次观看 • 1 个月前

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

269,381 次观看 • 1 个月前

quant at aqr sat next to me at a conference and said something that rewired how i think about markets "we don't analyze 500 stocks. we run 5 factors that explain all 500 at once" i asked him to draw it out take your entire stock universe - 500 names, 3 years of daily returns - and run PCA the 500 collapse into 5 factor 1: broad market momentum - explains 58% of all price movement by itself factor 2: sector rotation - where institutional money is actually flowing factor 3: rate sensitivity - duration risk bleeding across the equity curve factor 4: momentum tilt - which names are accelerating vs mean-reverting factor 5: credit spread stress - signal hiding inside equity vol if you know these 5 numbers, you know what 500 stocks are about to do retail watches 500 charts and sees noise. quant desks watch 5 eigenvalues and see structure math is called Principal Component Analysis, in every intro stats course on earth data to run it is free. python implementation is ~120 lines renaissance, two sigma, aqr - running this since before most retail traders could name a stock reason nobody told you isn't that it's proprietary it's that telling you costs them their edge Bookmark this market was never 500 moving parts it was always 5 - hiding inside 500
0:49

quant at aqr sat next to me at a conference and said something that rewired how i think about markets "we don't analyze 500 stocks. we run 5 factors that explain all 500 at once" i asked him to draw it out take your entire stock universe - 500 names, 3 years of daily returns - and run PCA the 500 collapse into 5 factor 1: broad market momentum - explains 58% of all price movement by itself factor 2: sector rotation - where institutional money is actually flowing factor 3: rate sensitivity - duration risk bleeding across the equity curve factor 4: momentum tilt - which names are accelerating vs mean-reverting factor 5: credit spread stress - signal hiding inside equity vol if you know these 5 numbers, you know what 500 stocks are about to do retail watches 500 charts and sees noise. quant desks watch 5 eigenvalues and see structure math is called Principal Component Analysis, in every intro stats course on earth data to run it is free. python implementation is ~120 lines renaissance, two sigma, aqr - running this since before most retail traders could name a stock reason nobody told you isn't that it's proprietary it's that telling you costs them their edge Bookmark this market was never 500 moving parts it was always 5 - hiding inside 500

Livsun

22,073 次观看 • 1 个月前