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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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120,924 просмотров • 2 месяцев назад •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

150,025 просмотров • 4 месяцев назад

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

16,029 просмотров • 1 месяц назад

a flood scientist accidentally solved stock market prediction in 1951 he wasn't studying markets. he was modeling nile river overflow patterns for the egyptian government harold hurst discovered something that broke the assumptions behind modern finance: natural systems have "memory" - the recent past predicts the near future at a statistically measurable level quants found his paper buried in hydrology journals 40 years later, built regime-detection desks around it, kept it off retail radar the number is called the Hurst Exponent. single value, 0 to 1: above 0.5 = market has momentum, recent moves predict continuation below 0.5 = market is mean-reverting, extremes snap back to the average at 0.5 = pure random walk, no edge exists SPY's 3-year hurst on daily closes: 0.61 not random. statistically confirmed to trend. a flood hydrologist proved it before most traders alive were born when H > 0.58: trend-following has positive expected value - bet with momentum, hold longer when H < 0.42: mean reversion has the edge - fade the extremes, take fast profits you're not predicting direction. you're detecting the regime first, then picking the right strategy for it this is the actual reason 90% of traders lose - not bad entries, not bad exits, not bad indicators - just using a trend strategy in a mean-reverting market and a mean-reversion strategy in a trending one wrong tool. wrong regime. every time formula is in any time series textbook. raw data is free on yahoo finance. implementation is 40 lines of python Bookmark this before you forget they built billion-dollar regime-detection desks on a nile river scientist's math while you were drawing support lines on the wrong type of market entirely
0:30

a flood scientist accidentally solved stock market prediction in 1951 he wasn't studying markets. he was modeling nile river overflow patterns for the egyptian government harold hurst discovered something that broke the assumptions behind modern finance: natural systems have "memory" - the recent past predicts the near future at a statistically measurable level quants found his paper buried in hydrology journals 40 years later, built regime-detection desks around it, kept it off retail radar the number is called the Hurst Exponent. single value, 0 to 1: above 0.5 = market has momentum, recent moves predict continuation below 0.5 = market is mean-reverting, extremes snap back to the average at 0.5 = pure random walk, no edge exists SPY's 3-year hurst on daily closes: 0.61 not random. statistically confirmed to trend. a flood hydrologist proved it before most traders alive were born when H > 0.58: trend-following has positive expected value - bet with momentum, hold longer when H < 0.42: mean reversion has the edge - fade the extremes, take fast profits you're not predicting direction. you're detecting the regime first, then picking the right strategy for it this is the actual reason 90% of traders lose - not bad entries, not bad exits, not bad indicators - just using a trend strategy in a mean-reverting market and a mean-reversion strategy in a trending one wrong tool. wrong regime. every time formula is in any time series textbook. raw data is free on yahoo finance. implementation is 40 lines of python Bookmark this before you forget they built billion-dollar regime-detection desks on a nile river scientist's math while you were drawing support lines on the wrong type of market entirely

Livsun

15,492 просмотров • 23 дней назад

robert engle won the nobel prize in economics for proving something hedge funds already knew they never bothered to mention it to retail price direction is mostly noise. but volatility? predictable. mathematically, provably, across every liquid market ever studied it clusters - that's not a pattern someone found, it's a structural law. high vol today predicts high vol tomorrow with 70%+ historical accuracy the model is called GARCH. published in every econometrics textbook on earth, chapter 4, about 60 lines of python to run quant desks at citadel and D.E. Shaw don't ask "will it go up?" - they ask "will the next move be large or small?" because sizing correctly inside a vol regime is worth more than being right on direction a trader right 48% of the time who sizes with vol awareness beats someone right 62% of the time sizing blindly - every time, over any long enough sample run it on 10 years of SPY data: > low vol state -> 74% chance next session stays low vol > vol spike -> 81% chance next session is also elevated now you're not predicting markets. you're reading a state machine the market keeps filling in for you every single session with real data the predictable part of markets was never price direction it was the distribution of price. the size of the moves. which regime you're currently inside math is free, data is free, implementation is free you were just told to stare at candlesticks instead Bookmark this before the feed buries it
0:30

robert engle won the nobel prize in economics for proving something hedge funds already knew they never bothered to mention it to retail price direction is mostly noise. but volatility? predictable. mathematically, provably, across every liquid market ever studied it clusters - that's not a pattern someone found, it's a structural law. high vol today predicts high vol tomorrow with 70%+ historical accuracy the model is called GARCH. published in every econometrics textbook on earth, chapter 4, about 60 lines of python to run quant desks at citadel and D.E. Shaw don't ask "will it go up?" - they ask "will the next move be large or small?" because sizing correctly inside a vol regime is worth more than being right on direction a trader right 48% of the time who sizes with vol awareness beats someone right 62% of the time sizing blindly - every time, over any long enough sample run it on 10 years of SPY data: > low vol state -> 74% chance next session stays low vol > vol spike -> 81% chance next session is also elevated now you're not predicting markets. you're reading a state machine the market keeps filling in for you every single session with real data the predictable part of markets was never price direction it was the distribution of price. the size of the moves. which regime you're currently inside math is free, data is free, implementation is free you were just told to stare at candlesticks instead Bookmark this before the feed buries it

Hrundel75 🐷

814,505 просмотров • 1 месяц назад

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

189,343 просмотров • 4 месяцев назад

the fed publishes data every single week that D.E. Shaw and Two Sigma actively trade on retail has no idea it exists. it's free. has been for decades it's called the H.4.1 - the federal reserve's own balance sheet release, every thursday at 4:30pm when bank reserves expand above their 12-week rolling mean, equity volatility compresses in a statistically predictable window 71% historical consistency since 2009 quants call this liquidity regime detection. the framework is in any macro textbook, chapter 4 not a chart pattern. not an indicator. a state the market is already in before you open a single candle high reserves -> collateral abundance -> risk appetite expands -> vol falls -> entry window opens you identify the state from free weekly data, enter when the math says the state historically sustains, exit when reserve growth rate rolls below the 8-week threshold avg hold: 6 to 11 days win rate: 71% kelly sizing turns that into compounding edge, not luck the data source: fred.stlouisfed. org, free API, zero subscription the framework: standard monetary transmission mechanics, any macro textbook the implementation: 150 lines of python Bookmark this before you scroll past it they told you to stare at RSI while they were reading the fed balance sheet every thursday at 4:30
0:30

the fed publishes data every single week that D.E. Shaw and Two Sigma actively trade on retail has no idea it exists. it's free. has been for decades it's called the H.4.1 - the federal reserve's own balance sheet release, every thursday at 4:30pm when bank reserves expand above their 12-week rolling mean, equity volatility compresses in a statistically predictable window 71% historical consistency since 2009 quants call this liquidity regime detection. the framework is in any macro textbook, chapter 4 not a chart pattern. not an indicator. a state the market is already in before you open a single candle high reserves -> collateral abundance -> risk appetite expands -> vol falls -> entry window opens you identify the state from free weekly data, enter when the math says the state historically sustains, exit when reserve growth rate rolls below the 8-week threshold avg hold: 6 to 11 days win rate: 71% kelly sizing turns that into compounding edge, not luck the data source: fred.stlouisfed. org, free API, zero subscription the framework: standard monetary transmission mechanics, any macro textbook the implementation: 150 lines of python Bookmark this before you scroll past it they told you to stare at RSI while they were reading the fed balance sheet every thursday at 4:30

Livsun

31,696 просмотров • 24 дней назад

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 просмотров • 2 месяцев назад

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 просмотров • 3 месяцев назад

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 просмотров • 3 месяцев назад

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 просмотров • 1 месяц назад

a quant at citadel told me something that broke my entire trading framework "we don't predict markets. we model the state machine" he explained markov cains 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 - andrei markov published it in 1906 hedge funds use it every day, 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 and use in your own strategy 37 years without a losing year, 66% annual returns paper is free, data is free, implementation is 200 lines of python they kept you staring at candles while they ran probability tables
0:30

a quant at citadel told me something that broke my entire trading framework "we don't predict markets. we model the state machine" he explained markov cains 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 - andrei markov published it in 1906 hedge funds use it every day, 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 and use in your own strategy 37 years without a losing year, 66% annual returns paper is free, data is free, implementation is 200 lines of python they kept you staring at candles while they ran probability tables

Livsun

19,808 просмотров • 1 месяц назад

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

269,433 просмотров • 4 месяцев назад

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

504,308 просмотров • 6 месяцев назад

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 просмотров • 2 месяцев назад

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 просмотров • 4 месяцев назад

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 просмотров • 2 месяцев назад

🚨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 просмотров • 4 месяцев назад

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 просмотров • 2 месяцев назад

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

15,272 просмотров • 1 месяц назад