Livsun
@L1vsun • 2,121 subscribers
US Entrepreneur × Quant Trading × Finance Tech For collab & business - https://t.co/xMWDJHA6co
Videos
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
Livsun1,280,972 views • 1 month ago
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
Livsun65,622 views • 3 days ago
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
Livsun374,208 views • 25 days ago
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
Livsun264,881 views • 1 month ago
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
Livsun59,615 views • 9 days ago
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
Livsun187,776 views • 1 month ago
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 views • 29 days ago
market opens at 9:30am his trade was already in at 4am neural net trained on 11 years of tick data called that setup 5 hours before candle even formed he's not smarter than the market. just built something that reads patterns human eyes can't process fast enough 4,200 data points per second, 847,000 labeled historical setups, running on a $40/mo server surfaces 3-4 trades a day. he takes top 2 last 90 days: 71% win rate, 2.3 avg risk/reward while retail traders watch news at open, this system already decided before sunrise you're not losing because your analysis is wrong you're losing because you're competing with something that doesn't sleep, panic or second-guess itself most people think this requires a PhD and a $2M quant desk he built his whole setup for under $500 using a free dataset and 3 weeks of evenings Bookmark this setup edge was never hidden behind a paywall or locked inside a fund it was sitting in a format nobody bothered to train on
Livsun70,268 views • 19 days ago
your backtest showed profit. so did mine then I ran 10,000 Monte Carlo simulations on that same strategy and found out we'd both read exactly one path out of 10,000 possible ones same 112 trades. reshuffled 10,000 times > worst outcome: -31% drawdown, 14 months underwater > 5th percentile: -18% max drawdown > median: +19% annual return > 95th percentile: +28% return strategy has a real edge but 1 in 20 traders running it hits a path that looks like failure for over a year most quit before month 14. blame the strategy, market, signals wasn't any of that here's a number that actually ends accounts: probability of ruin at 2% risk per trade: 0.3% bump to 3%: 4.1% 13x more likely to blow up from changing one input - not worse entries, not worse signals, just 1% more size most "failed" systems weren't failing. they were good systems at wrong size on a bad sequence the trader never knew existed one Monte Carlo run would've told them: this drawdown is normal, keep trading Bookmark this info most traders will never run it. they'll read the backtest once, start live, hit month 4, and wonder why their "proven" system broke it didn't break. they just never knew what they were holding
Livsun28,470 views • 7 days ago
quant funds spend millions hiring people who know a formula you learned in 10th grade and never applied to a price chart y = mx + b. that's it linear regression - same math from high school most traders learned, ignored, and forgot existed what quants actually figured out: asset prices don't move randomly, they drift and revert with measurable slope regression separates signal from noise. slope tracks trend, residuals measure the deviation when deviation gets large enough, that's the trade - prices tend to snap back to the line quants call it "mean reversion." retail calls it "a dip" actual workflow: > pull 5 years of daily returns > run OLS, extract beta and residuals > z-score the residuals > entries at -2 standard deviations, exits at 0 retail draws trend lines by hand and calls it analysis Bookmark this ^ data is public, math is free, approach has been in papers since the 1980s 99% of traders have never built one signal this way it was never an information gap - always been a methodology gap, and that's the kind that compounds
Livsun28,357 views • 8 days ago
options market makers calculate a number every day that tells them whether to pin price or let it run retail has no idea it exists it's called net dealer gamma exposure. when they're long gamma, they hedge by selling rallies and buying dips - price gets pinned when short gamma, they hedge the opposite way - moves accelerate, break out, trend this isn't hidden data or a proprietary signal it's calculable from public cboe options chains, free, updated every morning crossover - where gamma flips zero - is your volatility regime indicator above it: suppression, below it: acceleration python + cboe feed + 200 lines of code to build it framework in academic papers since 2017, sitting in textbooks the whole time retail has been reading candles while market makers were reading their own hedging book Bookmark and reasearch it yourself same market. completely different game
Livsun59,146 views • 27 days ago
73% win rate, $340k in 11 months no indicators, just a 6x6 probability matrix it's called a markov chain - math from 1906 wall street quants used it for decades, retail never heard of it markets cycle between states: trending, ranging, volatile, choppy probability of which state comes next is measurable, stable across decades if market is in "ranging" today: 62% -> trending, 23% -> stays ranging, 15% -> volatile you stop predicting price direction you start predicting market structure one is a coin flip dressed in candlesticks the other is a math problem with an answer Bookmark and add this indicator in your tools RSI: 1978. markov chains: 1906 72 years older and it's eating technical analysis alive
Livsun44,797 views • 20 days ago
nobody making $380k at a quant desk has any reason to write you a roadmap that's not cynicism - that's incentive structure wall street banks have PR teams pushing the "break into finance" pipeline. quant firms don't recruit that way, don't advertise, don't need to the filter has nothing to do with finance knowledge - it's 6 categories: probability, statistics, mental math, game theory, coding, market microstructure zero of those show up in a finance degree interview structure has been roughly the same for over a decade problems are documented, prep path is public, nobody stitched it into a guide for you most applicants wash out in round 1 and assume they weren't the right kind of smart a state school CS grad who grinds the right 6 categories for 6 months outearns a target-school banking analyst within 2 years $140k on the banking path vs $430k on the quant path same city, completely different question set Bookmark this information to close that gap has existed for years you just had to know you were supposed to be looking
Livsun20,519 views • 10 days ago
hedge funds have been running this math for 30 years. retail just discovered fibonacci retracements andrei markov was a russian linguist studying letter sequences in 1906 - had nothing to do with markets renaissance found his paper 70 years later, built medallion around it, told nobody markets don't move randomly - they move in states trending, ranging, reversing - each state has a fixed historical probability of shifting to the next you don't predict direction. you identify which state you're in, then let probability do the rest build a transition matrix from 10 years of price data: trending -> stays trending 68% of the time, flips to range 21%, reverses 11% ranging -> holds 54%, breaks up 28%, breaks down 18% now you're not guessing - you're entering on 68% historical completion size with kelly criterion based on that probability. take the trade when math says yes "where is price going?" -> random "what state am i in right now?" -> has an answer paper is free, data is free, python to build this: 200 lines 37 years, zero losing years - that's what medallion looks like when you ask the right question they kept you drawing fibonacci lines while they ran probability tables Bookmark this and run the matrix yourself
Livsun29,985 views • 16 days ago
a citadel options trader told me the one concept they test first in every quant interview and it's been sitting on a free website for years not a hedge fund textbook, not a $3,000 prep program. a free course syllabus - options greeks, volatility, quizzes - publicly available, almost nobody applying has ever opened it concept is expected value across a probability distribution retail looks at a chart and asks which direction. quant looks at expected payout across every possible outcome and asks if that number beats the cost of the trade - completely different question options pricing is just EV made rigorous fair value of any position = sum of (each outcome's probability x its payoff), discounted back. that formula is in every intro stats course and every free options curriculum these firms post publicly citadel's first round isn't a stock pitch or a DCF it's a market-making problem: "set me a bid and ask on a coin flip" if you can solve that fast and size it correctly, you can price any derivative on earth prep is documented in 6 categories: probability, greeks, volatility, mental math, coding, microstructure firms don't want you pattern-matching to old trades. they want raw EV instinct - and that's in free courses that have been online for years entry-level quant traders at these firms start at $300k. senior traders clear $650k+ most people never make it past round 1. not because they weren't smart - because nobody told them what the test was actually measuring Bookmark this they kept you reading charts while they were drilling expected value at 2am
Livsun25,684 views • 14 days ago
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
Livsun51,395 views • 1 month ago
jane street made $4 billion last year they employ almost no traders just physicists building AI while retail draws support lines, their models are running: > 2 million signals per second from order flow > news sentiment scored in 0.3ms before your feed updates > regime detection that flags state shifts before price confirms by the time you see a candle, trade is closed and profit is locked and here's what should actually bother you: every paper behind this stack is public datasets are free. arxiv has the math tick data runs $50/month they didn't find secret knowledge Boomark it and create your own pipeline they built a better system before you knew a different game existed
Livsun33,432 views • 25 days ago
jane street paid a 23yo $250k last year didn't come from a target school didn't have a finance degree knew exactly what the interview was going to test while his classmates were grinding campus recruiting, he was drilling probability problems at 2am that's what nobody tells you about quant finance - the interview has nothing to do with traditional finance citadel wants to know how fast your brain handles expected value under pressure. they don't care about your DCF model 6 categories: >probability, >mental math, >statistics, >logic puzzles, >coding, >market microstructure zero to interview-ready in under a year if you actually know what to study most people apply without knowing any of this. screened out in round 1, assume they weren't smart enough the firms aren't looking for the smartest Bookmark it or will lose all potential they're looking for the most prepared
Livsun39,010 views • 1 month ago
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
Livsun13,335 views • 9 days ago
quants don't predict markets. they stopped trying years ago retail is still asking "where is price going?" - quants switched to a different question entirely "given the current state, what's the probability distribution of outcomes" that's not a semantics game. it changes the math entirely stochastic processes model how a system evolves probabilistically - not picking a direction, mapping where each path leads and how likely it is ornstein-uhlenbeck does this for mean reversion: drift rate back to equilibrium, variance around that path same price data everybody has. different equation math is a century old, free in every applied probability textbook Bookmark and learn this before it gone you've been drawing trend lines while they ran probability distributions on same numbers it was never about data it was the question you were taught to ask
Livsun13,176 views • 11 days ago