Livsun
@L1vsun • 4,021 subscribers
US Entrepreneur × Quant Trading × Finance Tech For collab & business - tg: @l1vsun
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retail has 10,000 indicators and still loses 80% of the time quants have one number they pull every morning before touching anything else it's called options skew - the gap between how much downside protection costs versus upside exposure on any liquid name CBOE publishes it free, every 15 minutes, on every major ticker since 2004 when put vol runs 8+ points above call vol on SPY, institutional desks are paying premium to hedge hard - that's not noise, that's where money thinks risk actually is backtested 2009 to 2024: when skew spikes 1.5 sigma above its 90-day baseline, SPY underperforms next 15 sessions 68% of the time not predicting direction - reading where billion-dollar desks are quietly paying to protect themselves size with kelly at 68% edge, enter short, exit in three weeks retail spent years memorizing moving average crossovers quants spent the same years reading a free number nobody told them existed same market. completely different question bookmark this data was public the whole time, you just didn't know to look for it
Livsun77,040 次观看 • 4 天前
the finance kids everyone envied in college made $120k at goldman the quiet math kids nobody noticed made $650k at firms most people can't name jane street. citadel. two sigma. d.e. shaw they don't recruit from linkedin. they recruit from math olympiads and competitive programming leaderboards the filter is 4 things: probability, coding, mental math, game theory same problems recycled every year, same structure every round the prep path is documented, free, and takes 8 months a kid from a state school who grinds this for 8 months has beaten ivy leaguers who showed up unprepared - credential matters less than the pattern recognition most people spend 3 years trying to break into banking for $120k the people who looked one level up spent 8 months and landed 5x the salary the information to do this has existed for years Bookmark this and upgrade your brain the gap isn't talent it's that nobody told you where to look
Livsun1,284,195 次观看 • 2 个月前
a hotel front desk clerk in nashville figured out why markets move exactly when they do not direction, not news - the actual mechanism of why a move happens at all he works overnight shift, 11pm to 7am. lobby goes quiet after midnight, nothing but a monitor and a wifi connection question that started it: why does volatility cluster he'd read it in passing - options dealers cause price moves they didn't intend spent 6 hours across two nights searching, wrote everything into a google doc called "options thing" here's what he found when you buy a call option from a dealer, dealer has a new problem. they sold you the right to buy shares at a certain price if stock moves up, your option gains value and dealer owes you money. to protect themselves they have to buy shares immediately - no discretion, no delay amount they have to buy at every price level is published every second for free - it's open interest on the options chain. every brokerage shows it he built a spreadsheet every morning at 9:29am, one minute before open, he pulled SPY's options chain and calculated where dealers were most exposed marked strikes with heaviest call open interest. watched what happened in first 30 minutes of trading day 12 he stopped breathing for a second price moved to the strike with heaviest dealer exposure 73% of the time in the first 45 minutes not because of a chart pattern, not because of any signal because 400 dealers ran the same hedge calculation at open, and all of them had to buy the same shares at the same time he started calling it gravity price pulls toward certain strikes when dealer positioning is heavy enough - not prediction, mechanics math has a name: gamma exposure, or GEX SpotGamma built a whole company surfacing it. Squeeze Metrics published an academic paper on mechanics in 2018 python implementation is around 400 lines, nothing but the options chain you already have he built it in google colab over 3 weekends, free, working only on nights the lobby was empty tracked it against 60 days of live SPY data on negative GEX days - dealers short gamma, forced to amplify moves - average daily range expanded 2.8x on positive GEX days, 63% of sessions closed within half a percent of open this is not a signal. it's a regime classifier negative GEX: something moves big today, whichever direction gets started. buy straddles, size up, let dealers carry it positive GEX: nothing moves today. dealers kill every attempt before it gets 2 points sell premium, collect theta, sleep at month 4 he went live. $4,200 account, pure options, no directional bet six months later: $4,200 became $19,800 he still works overnight shift. told me about it in the lobby at 3am when i asked what he was typing google doc still says "options thing" - he never renamed it i asked why he never shared this. he looked at the lobby doors and said "who would believe a hotel clerk" data is free, formula is public, wall street has run this since 2017 they assumed retail would never think to read options flow as a mechanical map of where price has to go they were right about retail. they weren't right about him bookmark this and go build it market tells you exactly where it's going. you just have to stop reading the wrong layer Write your thought below
Livsun200,378 次观看 • 1 个月前
a russian mathematician solved trading in 1906 wall street found the paper 70 years later, built billion-dollar funds around it, never mentioned it to retail andrei markov proved markets aren't random - they're state machines trending, ranging, reversing - each state has a fixed historical probability of shifting to the next build a transition matrix from real data: trending -> stays trending: 68% trending -> flips to range: 21% trending -> reverses: 11% now you're not predicting direction. you're entering on 68% historical completion identify your state, size with kelly, take the trade when math says yes that's the edge. the whole edge renaissance has run this since 1988. 37 years of 66% annual returns paper is free, data is free, implementation is 200 lines of python Bookmark and use in your own strategy they kept you staring at candles while they ran probability tables
Livsun376,556 次观看 • 2 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
Livsun14,528 次观看 • 3 天前
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 40% of the year - not because signals are missing, because regime filter says math doesn't work in that environment trending regime eats mean reversion alive - ranging regime eats momentum most retail accounts blow up not from bad signals but from running the right signal in the wrong regime framework is called regime detection - published academic work, in every quant textbook since the 1990s 3 inputs to identify it: realized vol vs 30-day mean, autocorrelation of daily returns, volume profile vs 20-day average vol elevated + autocorrelation negative = mean-reversion regime - momentum will destroy you here autocorrelation positive + vol compressing = trending regime - reversion will destroy you here wrong regime turns a 60% signal into a 40% signal - you're paying the house right regime turns a 54% signal into a 65% edge - kelly compounds it into something insane bookmark this before you open another chart Dm me "Quant" for full quant course data is free, formula is public, 150 lines of python to run the whole thing they didn't hide the signals from you they hid the question you were supposed to ask first
Livsun120,252 次观看 • 1 个月前
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
Livsun268,026 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
Livsun10,807 次观看 • 3 天前
THIS REPO IS F*CKING GOLD i genuinely wasn't planning to share this last night i stumbled onto a github repo that feels like someone accidentally left a quant firm's bookshelf unlocked hundreds of resources, papers people usually find years later market microstructure, stat arb, execution models, order flow books, datasets, lectures, research, code... all in one place what pissed me off wasn't even repo itself it was realizing how many people are still grinding through recycled twitter threads and $500 courses while this stuff has been sitting in public for years that's how this game works most people don't lose because they're lazy they lose because they never even see same information people at top quietly build on by time everyone starts talking about something, edge is already gone meanwhile somebody downloads one repo, spends 3 months reading instead of doomscrolling, and ends up seeing market completely differently hardest part isn't learning Bookmark before it losted forever it's finding what actually matters before everyone else does
Livsun26,709 次观看 • 10 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
Livsun188,258 次观看 • 2 个月前
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
Livsun149,183 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
Livsun15,785 次观看 • 8 天前
whoever leak this have titanium balls at 4am, while you sleep, a quant fund has re-weighted 300 signals, identified names to fade at open, and priced in exactly what you're about to do next number buried in here: they model retail order flow 40 minutes before the bell with 73% directional accuracy - not from secret data, from public futures positioning that's not prediction. that's your loss, booked before you wake up here's what the article unpacks about how the 4am pipeline actually runs - and where your money goes: - factor signals get re-ranked nightly on vol-adjusted returns from the prior session and overnight futures - by 9:30 every quant desk has a fresh edge score while you're reading yesterday's close - "gap up, buy the open" isn't alpha: it's one of most modeled retail behaviors in existence, and quant desk has been long since 2am and is selling into your confidence at 9:31 - they don't read same earnings release you do at 8am - automated parsers ran it 5 hours earlier, positions were set, name is already priced before it hits your news feed - order flow imbalance from asian markets predicts US open direction - quant desks weight it explicitly, most retail traders have never heard of it, and both groups see same public exchange data - vol regime they set at 4am changes position sizing by 3x - high-volatility environment means they hold a third the size and harvest from tighter edges; you're just guessing at size - news sentiment parsers score every overnight headline on a factor model trained on how similar stories moved same names in the past - by the time CNBC covers it, they've already positioned - they don't ask "which way?" at open. they ask "which way will retail push this, and where does it exhaust?" - that question alone is worth more than any indicator you run catch: not one input above is proprietary - futures prices are free, exchange data is public, and the academic papers on retail order flow sat on government websites since 2003 they read it, built on top of it, and you were never told where to look every time you log in at 9:29 feeling sharp, that session started 5 hours ago without you read what 4am actually looks like ↓
Livsun12,857 次观看 • 6 天前
every day before market open, the CBOE publishes exactly where market makers are forced to buy and sell not a theory, not a pattern - a number that actually moves price it's called dealer gamma exposure - GEX - and it creates real price magnets quants have traded against for years here's why it works when you buy a call option, a market maker sells it to you and has to hedge that hedge shifts as price moves - they buy when it rises, sell when it falls negative GEX zones are where they sell into every rally, cap every breakout, crush every momentum move strikes with highest open interest aren't random - they're gravitational markets don't break through those levels cleanly because a billion-dollar dealer is actively hedging against it quants call them gamma walls data is free, published every morning on the CBOE site - no API, no Bloomberg terminal retail calls those same levels "resistance" and chalks it up to vibes bookmark this before it lost it's not vibes. it's math someone is paid $400k/year to understand while you do it by eyeball the whole time you thought technical analysis was detecting patterns you were just watching the shadow of dealer hedging and calling it insight
Livsun69,577 次观看 • 1 个月前
Wall Street pays you to be calm. Then kills you for it a vol trader in chicago told me quietest money on street and the most brutal "retail buys insurance. we sell it. every single day. and we get paid to" i asked why that isn't suicide "because market is calm 80% of the time. calm is default. fear is exception" here's the part that should make you uncomfortable VIX futures curve is normally in contango near-term vol is cheap, far-term is expensive every day curve rolls down toward spot and whoever is short that curve collects roll. automatically it's: > called volatility risk premium > been paying out for decades > market's fee for letting you sleep but here's twist they don't put on retail: curve rolling down isn't luck, it's structural when front-month VIX is below the 2nd month by more than ~1 point, shorting the roll earns ~1-2% a month, nearly risk-free catch is the 20% of the time it's not calm: that's when one week wipes out two years free data. VIX futures term structure is published by CBOE every morning save this post before next vol spike they kept you buying the dip. the desk was selling the calm
Livsun26,734 次观看 • 17 天前
a prop trader from chicago made $847k in 180 days just by asking one question every single morning that 99% of traders never ask he didn't build a new model didn't touch machine learning just opened excel and spent 8 minutes on one calculationthe question: what state is the market in right now, and where does it statistically go next most traders ask "will this go up or down". that's 50/50 he started asking "is the market trending, ranging, or reversing" and then looked at the historical probability of each transitionturns out markets don't flip randomly they cycle through states. each state has a fixed probability of shifting to the next onehe built a 5x5 grid on a napkin: 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% to range, 15% reverses he didn't predict direction he just calculated which state had the highest expected value and sized the position with kelly criterion that's the entire edgethe framework is from 1906 - andrei markov. free in every probability textbook on earthrenaissance technologies has been running this since 1988 37 years of 66% annual returnsdata costs nothing - yahoo finance, federal reserve, any broker implementation is 200 lines of python what separates him from the retail traders losing money isn't intelligence or capital or luck it's that he was willing to think differently about the same data everyone else sees every single day they kept you staring at candles while the people who got it were reading transition matrices bookmark this - you're either asking the wrong question or you're not asking it at all
Livsun41,634 次观看 • 1 个月前
jane street, two sigma, man group put their actual code on github 22 repos from firms running $200 billion combined - all public, all free nobody's talking about this because nobody thought to check what's in those repos isn't just tooling - it's their mental model these firms don't ask "will price go up?" they model markets as adversarial games - every participant simultaneously optimizing against every other that's why their signals hold - retail's don't two sigma's repo covers how they structure and clean data at scale man group's work spans signal generation, portfolio construction, factor models jane street's tools teach probability and microstructure exactly how their quants think this is game theory applied to markets - nash equilibria, auction dynamics, opponent modeling not chart patterns or indicator crossovers code is free, frameworks in public repos, math in every probability textbook Bookmark before it gets buried retail paid for courses on same stuff these firms gave away information gap was never intelligence, just knowing where to look
Livsun61,062 次观看 • 1 个月前
market opens at 9:30am his trade was already in at 4am neural net trained on 11 years of tick data called that setup 5 hours before candle even formed he's not smarter than the market. just built something that reads patterns human eyes can't process fast enough 4,200 data points per second, 847,000 labeled historical setups, running on a $40/mo server surfaces 3-4 trades a day. he takes top 2 last 90 days: 71% win rate, 2.3 avg risk/reward while retail traders watch news at open, this system already decided before sunrise you're not losing because your analysis is wrong you're losing because you're competing with something that doesn't sleep, panic or second-guess itself most people think this requires a PhD and a $2M quant desk he built his whole setup for under $500 using a free dataset and 3 weeks of evenings Bookmark this setup edge was never hidden behind a paywall or locked inside a fund it was sitting in a format nobody bothered to train on
Livsun70,370 次观看 • 2 个月前
YOU ARE FREAKING KIDDING ME... most reliable trade of the year happens while you are drunk and offline biggest, most predictable money move of year lands in December and January while you're hammered, offline, and not watching and it's been free for 40 years every November a whole class of stocks gets hammered for no reason. not fraud or bad earnings forced selling. on a clock fund managers dump losers before year-end to bank losses and clean their books mechanical. mandatory. nothing to do with company then January hits, pressure's gone and those same beaten stocks rip harder than winners retail waits for "new year rally" to start in January desk already loaded truck in the last two weeks of December you're buying what they accumulated while you were doing holiday shopping here's edge they don't put in beginner courses: you don't predict a winner. you find the forced sellers screen for stocks down 20%+ year-to-date in the last ten trading days of November, with real fundamentals those are the tax-loss dumping grounds. buy the basket the week before Christmas historically they outrun the index by 3 to 6% in the first three weeks of January as the forced selling reverses free screen. any broker's "losers YTD" filter. no indicator, no signal service save this post and set reminder now: November 20 while everyone else is shopping, you're shopping dump
Livsun19,740 次观看 • 16 天前
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
Livsun21,075 次观看 • 20 天前