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this model doesn't predict where the S&P 500 will go it predicts when the market's own velocity is about to collapse Z(x,y) = F(β, α, τ, ∇τ; x, y, t) one equation. four parameters. a 3D surface that maps how price momentum evolves across time and space β is... drift velocity: μ/σ, the ratio of expected return to volatility when β is high the market is moving with conviction when β decays toward zero the trend is losing energy before the chart shows any sign of it α measures how fast that velocity is changing τ is the time structure of the regime ∇τ is the gradient, the rate at which the regime itself is shifting the 3D surface on screen is not decoration the red peaks are where momentum is concentrated and unstable the blue basin is where the system is calm and mean-reverting the yellow marker is where the S&P sat at the moment of the snapshot the model's output: position sizing optimization not buy or sell. how much exposure to hold given the current position on that surface the bottom chart shows it: blue line is the model, white line is buy & hold same asset, same period, different sizing at every point based on where the dynamics equation said the market was > time dynamics models: rooted in physics, applied to finance since the 1990s > drift-to-volatility ratio: standard risk metric at Two Sigma, AQR, Man Group > this exact framework: free, public, 60 seconds in this video > what retail uses instead: lagging indicators that measure the past, not the velocity of the present retail asks "is the market going up or down?" this model asks "how fast is the market's own energy decaying and where on the surface are we right now?" completely different question. completely different result full breakdown in the video belowshow more

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String Theory Lecture 1 A String Does Not Move Like a Point A point particle traces a line through spacetime. A string traces a surface. This is the first geometric shift in String Theory. Particle mechanics asks where one object is at time t, so its history is a curve. String Theory asks where every point of an extended object is at worldsheet time τ, so we need another coordinate telling us where we are along the string. For a point particle x(t) So, for one input of time we get a position in Spacetime. For a string Xᵘ(τ,σ) Here τ plays the role of time on the worldsheet, while σ labels position along the string. Freeze τ and vary σ, and you see the string at one instant. Let τ move, and that curve sweeps out a two-dimensional surface... the worldsheet. The same comparison appears in the action. For a relativistic point particle, the geometric action measures worldline length S = −m ∫ ds If we parameterize the path by t, the action has one integral, one parameter, and one tangent vector dxᵘ/dt For a string, the same idea grows by one dimension. The action measures area, not length. In Nambu-Goto form, S = −T ∫ dτ dσ √[−det hₐᵦ] Here T is the string tension. It plays a role similar to mass, but for an extended object. It weights the area of a surface rather than the length of a line. The particle action has ∫ dt because the history is one-dimensional. The string action has ∫ dτ dσ because the history is two-dimensional. We are no longer summing along a path, we are summing over a surface. The geometry changes for the same reason. For the particle, one derivative is enough dxᵘ/dt For the string, the geometry is built from two derivatives: ∂τXᵘ and ∂σXᵘ The first tells you how the string changes as worldsheet time flows. The second tells you how the embedding changes as you move along the string. Together they define the induced worldsheet metric hₐᵦ = ∂ₐXᵘ ∂ᵦXᵤ In plain terms, hₐᵦ measures tangent lengths and tangent angles on the worldsheet. From it, the area element is dA = dτ dσ √[−det hₐᵦ] This, the Nambu-Goto action is the direct analogue of the point-particle length action. The point particle extremizes length and the string extremizes area. For calculations, people usually switch to the Polyakov action: S = −(T/2) ∫ dτ dσ √[−γ] γᵃᵇ ∂ₐXᵘ ∂ᵦXᵤ This describes the same classical string dynamics, but the algebra is cleaner. After choosing conformal gauge, varying with respect to Xᵘ gives (∂²/∂τ² − ∂²/∂σ²) Xᵘ = 0 This is the first real dynamical payoff... a two-dimensional wave equation on the worldsheet. For a point particle, the equation of motion tells you how one position evolves along one path. For a string, it tells you how an entire curve evolves, with waves traveling along it. The term ∂²Xᵘ/∂τ² measures acceleration in worldsheet time, while ∂²Xᵘ/∂σ² measures curvature along the string. The time evolution is balanced by how the string bends along its own length. This is why strings have oscillation modes. A point particle has one trajectory. A string has many possible vibration patterns, each one a normal mode of the worldsheet wave equation. For a closed string, σ wraps around the loop Xᵘ(τ, σ + 2π) = Xᵘ(τ, σ) For an open string, one standard free-end condition is ∂σXᵘ = 0 at the endpoints. Solving the wave equation gives waves moving in opposite directions along the string Xᵘ(τ,σ) = Fᵘ(τ + σ) + Gᵘ(τ − σ) A function of τ + σ moves one way. A function of τ − σ moves the other. Therefore, a particle has a worldline, its action measures length, and its geometry uses one tangent. The string has a worldsheet, its action measures area, and its geometry uses two tangent directions. #StringTheory #TheoreticalPhysics #MathematicalPhysics #Physics #Spacetime

String Theory Lecture 1 A String Does Not Move Like a Point A point particle traces a line through spacetime. A string traces a surface. This is the first geometric shift in String Theory. Particle mechanics asks where one object is at time t, so its history is a curve. String Theory asks where every point of an extended object is at worldsheet time τ, so we need another coordinate telling us where we are along the string. For a point particle x(t) So, for one input of time we get a position in Spacetime. For a string Xᵘ(τ,σ) Here τ plays the role of time on the worldsheet, while σ labels position along the string. Freeze τ and vary σ, and you see the string at one instant. Let τ move, and that curve sweeps out a two-dimensional surface... the worldsheet. The same comparison appears in the action. For a relativistic point particle, the geometric action measures worldline length S = −m ∫ ds If we parameterize the path by t, the action has one integral, one parameter, and one tangent vector dxᵘ/dt For a string, the same idea grows by one dimension. The action measures area, not length. In Nambu-Goto form, S = −T ∫ dτ dσ √[−det hₐᵦ] Here T is the string tension. It plays a role similar to mass, but for an extended object. It weights the area of a surface rather than the length of a line. The particle action has ∫ dt because the history is one-dimensional. The string action has ∫ dτ dσ because the history is two-dimensional. We are no longer summing along a path, we are summing over a surface. The geometry changes for the same reason. For the particle, one derivative is enough dxᵘ/dt For the string, the geometry is built from two derivatives: ∂τXᵘ and ∂σXᵘ The first tells you how the string changes as worldsheet time flows. The second tells you how the embedding changes as you move along the string. Together they define the induced worldsheet metric hₐᵦ = ∂ₐXᵘ ∂ᵦXᵤ In plain terms, hₐᵦ measures tangent lengths and tangent angles on the worldsheet. From it, the area element is dA = dτ dσ √[−det hₐᵦ] This, the Nambu-Goto action is the direct analogue of the point-particle length action. The point particle extremizes length and the string extremizes area. For calculations, people usually switch to the Polyakov action: S = −(T/2) ∫ dτ dσ √[−γ] γᵃᵇ ∂ₐXᵘ ∂ᵦXᵤ This describes the same classical string dynamics, but the algebra is cleaner. After choosing conformal gauge, varying with respect to Xᵘ gives (∂²/∂τ² − ∂²/∂σ²) Xᵘ = 0 This is the first real dynamical payoff... a two-dimensional wave equation on the worldsheet. For a point particle, the equation of motion tells you how one position evolves along one path. For a string, it tells you how an entire curve evolves, with waves traveling along it. The term ∂²Xᵘ/∂τ² measures acceleration in worldsheet time, while ∂²Xᵘ/∂σ² measures curvature along the string. The time evolution is balanced by how the string bends along its own length. This is why strings have oscillation modes. A point particle has one trajectory. A string has many possible vibration patterns, each one a normal mode of the worldsheet wave equation. For a closed string, σ wraps around the loop Xᵘ(τ, σ + 2π) = Xᵘ(τ, σ) For an open string, one standard free-end condition is ∂σXᵘ = 0 at the endpoints. Solving the wave equation gives waves moving in opposite directions along the string Xᵘ(τ,σ) = Fᵘ(τ + σ) + Gᵘ(τ − σ) A function of τ + σ moves one way. A function of τ − σ moves the other. Therefore, a particle has a worldline, its action measures length, and its geometry uses one tangent. The string has a worldsheet, its action measures area, and its geometry uses two tangent directions. #StringTheory #TheoreticalPhysics #MathematicalPhysics #Physics #Spacetime

Mathelirium

31,560 Aufrufe • vor 2 Monaten

String Theory Lecture 2 In Conformal Gauge, the String Becomes a Wave Equation Episode 1 showed the geometric jump point particle -> worldline string -> worldsheet Episode 2 is the dynamical jump. The Nambu-Goto action measures the area of the worldsheet, S = −T ∫ dτ dσ √[−det hₐᵦ] but the square-root determinant is awkward to work with. So we usually rewrite the same classical theory in Polyakov form, S = −(T/2) ∫ dτ dσ √[−γ] γᵃᵇ ∂ₐXᵘ ∂ᵦXᵤ Here Xᵘ(τ,σ) tells us where each point of the string’s worldsheet sits in spacetime, and γₐᵦ is the metric we put on the worldsheet. The power of this form is that we can choose a convenient gauge. In conformal gauge, the equations of motion simplify to (∂²/∂τ² − ∂²/∂σ²) Xᵘ = 0 So the string’s spacetime coordinates behave like waves living on the worldsheet. The τ-derivative measures how the string changes in worldsheet time. The σ-derivative measures how it bends along its own length. For a closed string, σ is periodic Xᵘ(τ, σ + 2π) = Xᵘ(τ,σ) and the wave equation splits into two traveling pieces, Xᵘ(τ,σ) = Fᵘ(τ + σ) + Gᵘ(τ − σ) One family moves one way around the string and the other moves the opposite way. These are the left-moving and right-moving modes. In the render, the bright loop is the string at the present moment. The glowing cylinder behind it is the worldsheet it has swept out. The cyan curves trace one traveling family, and the gold curves trace the other. They are the visual version of τ + σ and τ − σ. Therefore, the theory has an internal wave equation, and its normal modes are the raw material for the string spectrum. #StringTheory #TheoreticalPhysics #ConformalGauge #Worldsheet #WaveEquation #Physics #Mathematics #MathematicalPhysics #QuantumGravity #ScienceVisuals

String Theory Lecture 2 In Conformal Gauge, the String Becomes a Wave Equation Episode 1 showed the geometric jump point particle -> worldline string -> worldsheet Episode 2 is the dynamical jump. The Nambu-Goto action measures the area of the worldsheet, S = −T ∫ dτ dσ √[−det hₐᵦ] but the square-root determinant is awkward to work with. So we usually rewrite the same classical theory in Polyakov form, S = −(T/2) ∫ dτ dσ √[−γ] γᵃᵇ ∂ₐXᵘ ∂ᵦXᵤ Here Xᵘ(τ,σ) tells us where each point of the string’s worldsheet sits in spacetime, and γₐᵦ is the metric we put on the worldsheet. The power of this form is that we can choose a convenient gauge. In conformal gauge, the equations of motion simplify to (∂²/∂τ² − ∂²/∂σ²) Xᵘ = 0 So the string’s spacetime coordinates behave like waves living on the worldsheet. The τ-derivative measures how the string changes in worldsheet time. The σ-derivative measures how it bends along its own length. For a closed string, σ is periodic Xᵘ(τ, σ + 2π) = Xᵘ(τ,σ) and the wave equation splits into two traveling pieces, Xᵘ(τ,σ) = Fᵘ(τ + σ) + Gᵘ(τ − σ) One family moves one way around the string and the other moves the opposite way. These are the left-moving and right-moving modes. In the render, the bright loop is the string at the present moment. The glowing cylinder behind it is the worldsheet it has swept out. The cyan curves trace one traveling family, and the gold curves trace the other. They are the visual version of τ + σ and τ − σ. Therefore, the theory has an internal wave equation, and its normal modes are the raw material for the string spectrum. #StringTheory #TheoreticalPhysics #ConformalGauge #Worldsheet #WaveEquation #Physics #Mathematics #MathematicalPhysics #QuantumGravity #ScienceVisuals

Mathelirium

15,295 Aufrufe • vor 2 Monaten

Phase Space Is the Real Stage of Dynamics. So, Stop Watching the Object and Watch the State. Ordinary Space tells you where something is. Phase Space tells you what state it is in. Position alone is not enough because you also need the variable that tells you where the system is trying to go. In the animation, the left panel shows the particle moving in Ordinary Space, while the right panel shows the same system as a moving point in Phase Space. For one degree of freedom, the state is (x, p) and as time evolves, that state traces a trajectory t ↦ (x(t), p(t)) Instead of thinking of a differential equation as just a formula, Phase Space lets you see it as a flow on the space of states. For this lecture we use ẋ = p ṗ = x − x³ with Hamiltonian H(x,p) = 0.5 p² + 0.25 x⁴ − 0.5 x² #PhaseSpace #DynamicalSystems #NonlinearDynamics #HamiltonianMechanics #Mathematics

Phase Space Is the Real Stage of Dynamics. So, Stop Watching the Object and Watch the State. Ordinary Space tells you where something is. Phase Space tells you what state it is in. Position alone is not enough because you also need the variable that tells you where the system is trying to go. In the animation, the left panel shows the particle moving in Ordinary Space, while the right panel shows the same system as a moving point in Phase Space. For one degree of freedom, the state is (x, p) and as time evolves, that state traces a trajectory t ↦ (x(t), p(t)) Instead of thinking of a differential equation as just a formula, Phase Space lets you see it as a flow on the space of states. For this lecture we use ẋ = p ṗ = x − x³ with Hamiltonian H(x,p) = 0.5 p² + 0.25 x⁴ − 0.5 x² #PhaseSpace #DynamicalSystems #NonlinearDynamics #HamiltonianMechanics #Mathematics

Mathelirium

30,340 Aufrufe • vor 3 Monaten

This is what it means to be on the charts for 20 years. For a trader, experience is not a detail, it is the real key to success. We are not talking about indicators, magic setups or current trends, but about eye, market memory and the ability to recognise the same dynamics that repeat themselves in different forms. This video found online explains it perfectly: it makes you understand how, over time, you stop reacting to candlesticks and start reading the market's intentions. You know when there is noise, when there is distribution, when they are just looking for liquidity... and above all, you know when to do nothing. That's where the real advantage lies. The rest is just haste, ego and overtrading. Experience does not accelerate the market. It accelerates you.

This is what it means to be on the charts for 20 years. For a trader, experience is not a detail, it is the real key to success. We are not talking about indicators, magic setups or current trends, but about eye, market memory and the ability to recognise the same dynamics that repeat themselves in different forms. This video found online explains it perfectly: it makes you understand how, over time, you stop reacting to candlesticks and start reading the market's intentions. You know when there is noise, when there is distribution, when they are just looking for liquidity... and above all, you know when to do nothing. That's where the real advantage lies. The rest is just haste, ego and overtrading. Experience does not accelerate the market. It accelerates you.

EliZ

61,654 Aufrufe • vor 6 Monaten

🚨 S&P 500 IS WALKING STRAIGHT INTO A WYCKOFF TRAP This is one of the oldest market structure models in history. And right now the S&P 500 is playing it out perfectly Preliminary Supply. Buying Climax. Upthrust. Post-Distribution Every phase has printed exactly where the model predicted We are now entering the Weakness phase - and if the structure holds, the target sits at 4,180 The market just hit new all-time highs while oil is above $120 and geopolitical risk is at decade highs That's not strength. That's the last trap before the drop NOTIFS ON!

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NoName

135,802 Aufrufe • vor 2 Monaten

🚨 READ THIS CAREFULLY The S&P 500 is entering the most dangerous part of the pattern. We are currently at point 6. The final all-time high zone. This is the phase where everyone thinks the worst is over. It isn’t. This is where the market turns back. This is a 7 point structure. And so far, it has followed the script perfectly. 1 → First support touch. 2 → First rejection from upper resistance. 3 → Second support touch. 4 → Second rejection. 5 → Panic flush into lower support. 6 → Final all-time high and reversal zone. Now comes 7. That is not the start of the dip. That is already the target zone after the reversal. And this is where the real damage starts. If this structure keeps playing out, the S&P 500 is heading toward 5,200 to 5,300. That is where this pattern completes. We are not there yet. Narratives will break there. Bulls will give up there. And most people will only realize it when the dump is already deep. This is exactly why I keep saying the market is much weaker than it looks. The rally is not strength. It is the final squeeze before the next leg down. I’ve studied macro for 10 years and I called almost every major market top, including the October BTC ATH. Follow and turn notifications on. I’ll post the warning BEFORE it hits the headlines.

🚨 READ THIS CAREFULLY The S&P 500 is entering the most dangerous part of the pattern. We are currently at point 6. The final all-time high zone. This is the phase where everyone thinks the worst is over. It isn’t. This is where the market turns back. This is a 7 point structure. And so far, it has followed the script perfectly. 1 → First support touch. 2 → First rejection from upper resistance. 3 → Second support touch. 4 → Second rejection. 5 → Panic flush into lower support. 6 → Final all-time high and reversal zone. Now comes 7. That is not the start of the dip. That is already the target zone after the reversal. And this is where the real damage starts. If this structure keeps playing out, the S&P 500 is heading toward 5,200 to 5,300. That is where this pattern completes. We are not there yet. Narratives will break there. Bulls will give up there. And most people will only realize it when the dump is already deep. This is exactly why I keep saying the market is much weaker than it looks. The rally is not strength. It is the final squeeze before the next leg down. I’ve studied macro for 10 years and I called almost every major market top, including the October BTC ATH. Follow and turn notifications on. I’ll post the warning BEFORE it hits the headlines.

Wimar.X

57,924 Aufrufe • vor 1 Monat

What String Theory Does That Classical Physics Doesn’t Classical Physics begins with a point particle. Its position is described by one function of time x = x(t) As time passes, that point traces a curve through Spacetime called a worldline. String theory changes the starting object. A string has length, so time alone is not enough. We also need a coordinate along the string Xᵘ = Xᵘ(τ, σ) Here τ is worldsheet time, and σ labels position along the string. As the string moves, it sweeps out a surface called a worldsheet. The action measures the area of that surface S = -T ∫ dτ dσ √[-det hₐᵦ] This is where string theory begins. #StringTheory #ClassicalMechanics #TheoreticalPhysics #Worldsheet #QuantumGravity #MathematicalPhysics #Spacetime #PhysicsVisualization #ScienceEducation

What String Theory Does That Classical Physics Doesn’t Classical Physics begins with a point particle. Its position is described by one function of time x = x(t) As time passes, that point traces a curve through Spacetime called a worldline. String theory changes the starting object. A string has length, so time alone is not enough. We also need a coordinate along the string Xᵘ = Xᵘ(τ, σ) Here τ is worldsheet time, and σ labels position along the string. As the string moves, it sweeps out a surface called a worldsheet. The action measures the area of that surface S = -T ∫ dτ dσ √[-det hₐᵦ] This is where string theory begins. #StringTheory #ClassicalMechanics #TheoreticalPhysics #Worldsheet #QuantumGravity #MathematicalPhysics #Spacetime #PhysicsVisualization #ScienceEducation

Mathelirium

18,446 Aufrufe • vor 14 Tagen

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

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

Livsun

13,176 Aufrufe • vor 1 Monat

Bannon: Pam Bondi where are the prosecutions of the people that did the invasion that set up the invasion of the southern border? FBI Director Kash Patel where are the arrests? Are we going to get serious about this or are we not? Todd Bensman is on here all the time. He said it was intricately set up to mass invade the country. Where are those politicians? Where is Mayorkas? Where is the grand jury? Where are the investigations? It is one thing to provide a platform to hear that heart wrenching story. But how are you going to stop it in the future? It is take action now. The reason for the frustration of this audience after all the work and effort to get here is let’s do something. Do not think you are going to be here forever. You cannot plan on that. Action. Action. Action.

Bannon: Pam Bondi where are the prosecutions of the people that did the invasion that set up the invasion of the southern border? FBI Director Kash Patel where are the arrests? Are we going to get serious about this or are we not? Todd Bensman is on here all the time. He said it was intricately set up to mass invade the country. Where are those politicians? Where is Mayorkas? Where is the grand jury? Where are the investigations? It is one thing to provide a platform to hear that heart wrenching story. But how are you going to stop it in the future? It is take action now. The reason for the frustration of this audience after all the work and effort to get here is let’s do something. Do not think you are going to be here forever. You cannot plan on that. Action. Action. Action.

Grace Chong, MBI

187,421 Aufrufe • vor 1 Jahr

every time you hit buy, the market maker on the other side already solved for two numbers not on the asset - on you specifically the first: their internal fair value. not the midpoint you see on screen their number is adjusted for the last 30 seconds of order flow, their current inventory imbalance and which volatility regime the model thinks the market is in it's different from the displayed price, and they never show it to you the second: your adverse selection probability. a live estimate of whether you're informed or just emotional if the model flags you as a potential informed trader, the spread widens before your fill - automatically, invisibly, before you notice anything changed that bad fill you blamed on "low liquidity"? sometimes it's a market maker's algorithm deciding you look too dangerous to fill at the quoted price this is Glosten-Milgrom - published 1985, sits in every market microstructure textbook on earth, runs inside every serious market making operation that's ever quoted you a price Bookmark this feature before it lost when you click buy, you're answering a question you didn't know was being asked retail spends all its time thinking about where price is going the desk filling your order is spending that same time thinking about you

every time you hit buy, the market maker on the other side already solved for two numbers not on the asset - on you specifically the first: their internal fair value. not the midpoint you see on screen their number is adjusted for the last 30 seconds of order flow, their current inventory imbalance and which volatility regime the model thinks the market is in it's different from the displayed price, and they never show it to you the second: your adverse selection probability. a live estimate of whether you're informed or just emotional if the model flags you as a potential informed trader, the spread widens before your fill - automatically, invisibly, before you notice anything changed that bad fill you blamed on "low liquidity"? sometimes it's a market maker's algorithm deciding you look too dangerous to fill at the quoted price this is Glosten-Milgrom - published 1985, sits in every market microstructure textbook on earth, runs inside every serious market making operation that's ever quoted you a price Bookmark this feature before it lost when you click buy, you're answering a question you didn't know was being asked retail spends all its time thinking about where price is going the desk filling your order is spending that same time thinking about you

Livsun

18,906 Aufrufe • vor 18 Tagen

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

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

Livsun

188,258 Aufrufe • vor 1 Monat

🚨 EVERY TIME INFLATION SPIKED, THE S&P 500 DUMPED... This is not a theory. This is simple pattern. Decades of data point in one direction: 2001: Inflation surged -> The S&P 500 collapsed 2008: Same story -> Different decade 2022: CPI spiked to 9% -> The S&P 500 dropped 25% Now look at where we are right now. CPI is rising again. PPI is already running hot. The market is pricing in a "NORMAL CORRECTION". But the data is screaming "HUGE COLLAPSE". Do NOT say I didn't warn you later...

🚨 EVERY TIME INFLATION SPIKED, THE S&P 500 DUMPED... This is not a theory. This is simple pattern. Decades of data point in one direction: 2001: Inflation surged -> The S&P 500 collapsed 2008: Same story -> Different decade 2022: CPI spiked to 9% -> The S&P 500 dropped 25% Now look at where we are right now. CPI is rising again. PPI is already running hot. The market is pricing in a "NORMAL CORRECTION". But the data is screaming "HUGE COLLAPSE". Do NOT say I didn't warn you later...

ᴛʀᴀᴄᴇʀ

67,526 Aufrufe • vor 1 Monat

Do you actually know what convex optimization is in the geometric, guarantee-theoretic sense or have you only met it through solvers and loss curves? Convexity is rare comfort in optimization...there are no spurious local minima, no surprise traps, and inequalities you can use like tools instead of prayers. So, what is this convexity? Let x = (x₁, x₂) and let f(x) be convex. Plot the surface z = f(x). Pick a contact point x₀. The local slope is the gradient p = ∇f(x₀). That p is exactly the data that defines the supporting plane: z = f(x₀) + p · (x − x₀). Thus, f is said to be convex because for every x, f(x) ≥ f(x₀) + p · (x − x₀). So the plane at x₀ can slide under the surface, but it never slices through it. Not near the point...everywhere. Now for here is the interesting part: The slope becomes a coordinate system! Rewrite the same plane as z = p · x − b, where b is the offset. Because the plane passes through (x₀, f(x₀)), the offset is forced to be b = p · x₀ − f(x₀). And that number isn’t just geometry trivia. It’s the convex conjugate: f*(p) = sup over x ( p · x − f(x) ). At a differentiable contact point, the supporting plane touches f tightly enough that the supremum is achieved at x₀, giving the identity f*(p) = p · x₀ − f(x₀) when p = ∇f(x₀). So one moving contact point gives two linked readouts: primal position x₀ dual position (slope) p = ∇f(x₀) dual offset f*(p) One surface. Two worlds. #ConvexOptimization #Optimization #MachineLearning #SignalProcessing #AppliedMath #Engineering

Do you actually know what convex optimization is in the geometric, guarantee-theoretic sense or have you only met it through solvers and loss curves? Convexity is rare comfort in optimization...there are no spurious local minima, no surprise traps, and inequalities you can use like tools instead of prayers. So, what is this convexity? Let x = (x₁, x₂) and let f(x) be convex. Plot the surface z = f(x). Pick a contact point x₀. The local slope is the gradient p = ∇f(x₀). That p is exactly the data that defines the supporting plane: z = f(x₀) + p · (x − x₀). Thus, f is said to be convex because for every x, f(x) ≥ f(x₀) + p · (x − x₀). So the plane at x₀ can slide under the surface, but it never slices through it. Not near the point...everywhere. Now for here is the interesting part: The slope becomes a coordinate system! Rewrite the same plane as z = p · x − b, where b is the offset. Because the plane passes through (x₀, f(x₀)), the offset is forced to be b = p · x₀ − f(x₀). And that number isn’t just geometry trivia. It’s the convex conjugate: f(p) = sup over x ( p · x − f(x) ). At a differentiable contact point, the supporting plane touches f tightly enough that the supremum is achieved at x₀, giving the identity f(p) = p · x₀ − f(x₀) when p = ∇f(x₀). So one moving contact point gives two linked readouts: primal position x₀ dual position (slope) p = ∇f(x₀) dual offset f*(p) One surface. Two worlds. #ConvexOptimization #Optimization #MachineLearning #SignalProcessing #AppliedMath #Engineering

Mathelirium

38,506 Aufrufe • vor 6 Monaten

"The Iranian regime is not a hierarchical system where decapitation is even “on the table”. So, even if you were to kill the Supreme Leader — or even the line of succession — which is, I think, what the Israelis are trying at the moment by taking out operational and strategic commanders across the IRGC, theocratic leaders, and political leaders, it doesn’t mean the regime is just going to collapse. The fact is, what we’ve seen since January is a complete decentralisation of the chain of command and command-and-control. So, despite this heavy attack this morning, there is no paralysis in Iran. Iran is sustaining it. They were very quick to strike back across the Gulf — escalating — and the operational tempo is still there. That shows command-and-control has been delegated down to the local level. We also see, for example, that the Basij — the major component of the IRGC that controls the public on the ground — has been on alert for quite some time and has organised itself at the local level without having to rely constantly on the main chain of command in Tehran"

"The Iranian regime is not a hierarchical system where decapitation is even “on the table”. So, even if you were to kill the Supreme Leader — or even the line of succession — which is, I think, what the Israelis are trying at the moment by taking out operational and strategic commanders across the IRGC, theocratic leaders, and political leaders, it doesn’t mean the regime is just going to collapse. The fact is, what we’ve seen since January is a complete decentralisation of the chain of command and command-and-control. So, despite this heavy attack this morning, there is no paralysis in Iran. Iran is sustaining it. They were very quick to strike back across the Gulf — escalating — and the operational tempo is still there. That shows command-and-control has been delegated down to the local level. We also see, for example, that the Basij — the major component of the IRGC that controls the public on the ground — has been on alert for quite some time and has organised itself at the local level without having to rely constantly on the main chain of command in Tehran"

Dr Andreas Krieg

224,057 Aufrufe • vor 4 Monaten

🔥🔥HUGH FIRES EVERYWHERE🔥 DERIVATIVES OVER LEVERAGE RISK🔥🔥💣💣🔥🔥 The system is at capacity IMO. When you see numbers in the high Trillions and Quadrillions and add huge amounts of leverage the system is not in good shape. Gold and Silver are not going up the system is failing. The system is backed by trust only. TRUST IS BROKEN. Suppressing the price of Precious Metals is an illusion it's not based on supply and demand it's based on how much paper can we throw at the Metals to hold them down. This is a pressure cooker MARKET MANIPULATION IN EVERY MARKET

🔥🔥HUGH FIRES EVERYWHERE🔥 DERIVATIVES OVER LEVERAGE RISK🔥🔥💣💣🔥🔥 The system is at capacity IMO. When you see numbers in the high Trillions and Quadrillions and add huge amounts of leverage the system is not in good shape. Gold and Silver are not going up the system is failing. The system is backed by trust only. TRUST IS BROKEN. Suppressing the price of Precious Metals is an illusion it's not based on supply and demand it's based on how much paper can we throw at the Metals to hold them down. This is a pressure cooker MARKET MANIPULATION IN EVERY MARKET

Stephanie 🇬🇧🇺🇸🦍

22,369 Aufrufe • vor 8 Monaten

Everyone is talking about inflation. The Fed is hawking. The ECB is hawking. Financial media is on repeat. But there is a market specifically designed to price inflation expectations, and it is saying something completely different. TIPS breakeven rates, the market's real-time gauge of inflation protection demand, have been falling. Not rising. Falling. Five-year breakevens slid to around 248 basis points last week, back near where they were before the energy shock began, even as oil stayed elevated and central bankers turned more aggressive. In 2022, when inflation was genuinely broad-based, breakevens pushed toward 325 to 350 basis points. This time, the ceiling was 270, and the market has been retreating from it ever since. The bond market is not pricing sustained, widespread inflation. It is pricing a narrow energy impulse, one the market believes will either resolve quickly or destroy enough demand to contain itself. That is 100% against the Fed's hiking thesis.

Everyone is talking about inflation. The Fed is hawking. The ECB is hawking. Financial media is on repeat. But there is a market specifically designed to price inflation expectations, and it is saying something completely different. TIPS breakeven rates, the market's real-time gauge of inflation protection demand, have been falling. Not rising. Falling. Five-year breakevens slid to around 248 basis points last week, back near where they were before the energy shock began, even as oil stayed elevated and central bankers turned more aggressive. In 2022, when inflation was genuinely broad-based, breakevens pushed toward 325 to 350 basis points. This time, the ceiling was 270, and the market has been retreating from it ever since. The bond market is not pricing sustained, widespread inflation. It is pricing a narrow energy impulse, one the market believes will either resolve quickly or destroy enough demand to contain itself. That is 100% against the Fed's hiking thesis.

Jeffrey P. Snider

18,154 Aufrufe • vor 13 Tagen

Warmup to Statistical Mechanics What Exactly is a Hamiltonian A System? In ordinary Mechanics, you might begin with position and velocity. Hamiltonian Mechanics rewrites the same motion in a different language. Instead of position and velocity, it uses position and momentum. We write the position variables as q and the momentum variables as p. Then the full state of the system at one instant is (q, p) That pair is one point in phase space. Why do we do this? Because in these variables, the equations of motion take a remarkably clean form. Everything is generated by one single function, the Hamiltonian H(q, p) and in the simplest cases this Hamiltonian is just the total energy written in terms of position and momentum. So if you know H, you know the dynamics. You might wonder, but how can one function generate motion? The rule is dqᵢ/dt = ∂H/∂pᵢ dpᵢ/dt = −∂H/∂qᵢ These are Hamilton’s equations. Now read them slowly 😄 The rate of change of position comes from differentiating H with respect to momentum. The rate of change of momentum comes from differentiating H with respect to position, with a minus sign. This constitutes the whole engine. A simple example makes this less abstract: Take one particle of mass m moving in a potential V(q). Then the Hamiltonian is H(q, p) = p²/(2m) + V(q) The first term is kinetic energy. The second term is potential energy. Now apply Hamilton’s equations. First, dq/dt = ∂H/∂p = p/m So momentum tells you how position changes. Second, dp/dt = −∂H/∂q = −dV/dq Thus, momentum changes because of force. If you now combine these two equations, you recover ordinary Newtonian mechanics. Since p = m dq/dt, we get m d²q/dt² = −dV/dq So, Hamiltonian mechanics is not a different theory. It is the same mechanics, written in a form that exposes its geometric structure much more clearly. The animation The full 3D surface is the Hamiltonian itself, the energy landscape H(q, p). The floor underneath is phase space, marked by energy contours and the local flow field. The bright moving point is one actual state (q(t), p(t)) evolving under Hamilton’s equations. Its trail shows that the motion is not arbitrary. It is guided everywhere by the geometry of the same single function H. The render is doing more than illustrating a particle moving, it is showing how one function organizes the whole phase-space motion. The math breakdown: Start with one degree of freedom. The state is described by position q and momentum p. So the system lives in a two-dimensional phase space with coordinates (q, p) Now choose a Hamiltonian H(q, p) Think of H as the energy function. In many standard systems, H(q, p) = kinetic energy + potential energy For a particle of mass m in a potential V(q), this becomes H(q, p) = p²/(2m) + V(q) Hamilton’s equations say dq/dt = ∂H/∂p dp/dt = −∂H/∂q Now substitute this specific H. First compute the p derivative: ∂H/∂p = ∂/∂p (p²/(2m) + V(q)) = p/m So dq/dt = p/m Now compute the q derivative: ∂H/∂q = ∂/∂q (p²/(2m) + V(q)) = dV/dq So dp/dt = −dV/dq These two first-order equations completely determine the motion. Now, connect this back to Newton’s law. From dq/dt = p/m we get p = m dq/dt Differentiate both sides with respect to time: dp/dt = m d²q/dt² But Hamilton’s second equation gives dp/dt = −dV/dq So , together they imply m d²q/dt² = −dV/dq This is exactly Newton’s second law for motion in the potential V(q). Thus, Hamilton’s equations do not replace mechanic, they reorganize it. #HamiltonianMechanics #PhaseSpace #ClassicalMechanics #MathematicalPhysics #DifferentialEquations #Mathematics #Physics

Warmup to Statistical Mechanics What Exactly is a Hamiltonian A System? In ordinary Mechanics, you might begin with position and velocity. Hamiltonian Mechanics rewrites the same motion in a different language. Instead of position and velocity, it uses position and momentum. We write the position variables as q and the momentum variables as p. Then the full state of the system at one instant is (q, p) That pair is one point in phase space. Why do we do this? Because in these variables, the equations of motion take a remarkably clean form. Everything is generated by one single function, the Hamiltonian H(q, p) and in the simplest cases this Hamiltonian is just the total energy written in terms of position and momentum. So if you know H, you know the dynamics. You might wonder, but how can one function generate motion? The rule is dqᵢ/dt = ∂H/∂pᵢ dpᵢ/dt = −∂H/∂qᵢ These are Hamilton’s equations. Now read them slowly 😄 The rate of change of position comes from differentiating H with respect to momentum. The rate of change of momentum comes from differentiating H with respect to position, with a minus sign. This constitutes the whole engine. A simple example makes this less abstract: Take one particle of mass m moving in a potential V(q). Then the Hamiltonian is H(q, p) = p²/(2m) + V(q) The first term is kinetic energy. The second term is potential energy. Now apply Hamilton’s equations. First, dq/dt = ∂H/∂p = p/m So momentum tells you how position changes. Second, dp/dt = −∂H/∂q = −dV/dq Thus, momentum changes because of force. If you now combine these two equations, you recover ordinary Newtonian mechanics. Since p = m dq/dt, we get m d²q/dt² = −dV/dq So, Hamiltonian mechanics is not a different theory. It is the same mechanics, written in a form that exposes its geometric structure much more clearly. The animation The full 3D surface is the Hamiltonian itself, the energy landscape H(q, p). The floor underneath is phase space, marked by energy contours and the local flow field. The bright moving point is one actual state (q(t), p(t)) evolving under Hamilton’s equations. Its trail shows that the motion is not arbitrary. It is guided everywhere by the geometry of the same single function H. The render is doing more than illustrating a particle moving, it is showing how one function organizes the whole phase-space motion. The math breakdown: Start with one degree of freedom. The state is described by position q and momentum p. So the system lives in a two-dimensional phase space with coordinates (q, p) Now choose a Hamiltonian H(q, p) Think of H as the energy function. In many standard systems, H(q, p) = kinetic energy + potential energy For a particle of mass m in a potential V(q), this becomes H(q, p) = p²/(2m) + V(q) Hamilton’s equations say dq/dt = ∂H/∂p dp/dt = −∂H/∂q Now substitute this specific H. First compute the p derivative: ∂H/∂p = ∂/∂p (p²/(2m) + V(q)) = p/m So dq/dt = p/m Now compute the q derivative: ∂H/∂q = ∂/∂q (p²/(2m) + V(q)) = dV/dq So dp/dt = −dV/dq These two first-order equations completely determine the motion. Now, connect this back to Newton’s law. From dq/dt = p/m we get p = m dq/dt Differentiate both sides with respect to time: dp/dt = m d²q/dt² But Hamilton’s second equation gives dp/dt = −dV/dq So , together they imply m d²q/dt² = −dV/dq This is exactly Newton’s second law for motion in the potential V(q). Thus, Hamilton’s equations do not replace mechanic, they reorganize it. #HamiltonianMechanics #PhaseSpace #ClassicalMechanics #MathematicalPhysics #DifferentialEquations #Mathematics #Physics

Mathelirium

50,478 Aufrufe • vor 2 Monaten

🚨 THIS IS NOT NORMAL The stock market is about to repeat history. US MARKET HAS NEVER BEEN THIS OVERBOUGHT IN HISTORY. The setup is IDENTICAL. Every single time the MACD turns, the S&P-500 has a massive crash. I spent 14 hours researching this, and you MUST know what comes next: Back in 2000, markets looked unstoppable. Momentum was strong. Confidence was high. And then everything broke. Billions were erased. Portfolios were crushed. And the dump was brutal. Right now, the chart is lining up almost point for point. Same breakout. Same overextension. Same false sense of security. And the warning signs are flashing. Valuations are stretched. Liquidity is tightening. Volatility is waking up. And risk is building underneath the surface. Most investors still don’t see it. Because at the top, everything feels normal. That’s how every major correction starts. Optimism peaks. Positioning gets crowded. And complacency takes over. Then the reversal begins. Fast. And once momentum flips, there is no gradual exit. There is only repricing. The market does not wait. It resets. And when it does, it moves violently. Right now, there are three paths ahead: 1⃣ SOFT RESET The market cools off. Valuations compress. Momentum stabilizes. 2⃣ DEEP CORRECTION Selling accelerates. Fear returns. Risk assets dump lower. 3⃣ FULL DOT-COM STYLE COLLAPSE Support breaks. Panic spreads. Liquidity disappears. Forced selling takes over. That is where real damage happens. Because when leverage unwinds, everything gets hit. Stocks. Crypto. Speculative assets. EVERYTHING. The chart is there. The setup is there. And history is staring investors in the face. Watch price action. Watch liquidity. Watch volatility. Because if this pattern completes, the next move will be impossible to ignore. And by the time everyone sees it - the market will already be lower. I’ve spent 10 years studying markets, and I’ve called most major tops and bottoms along the way. And I’ll call it again in 2026. Follow me and turn notifications on before it’s too late. Don’t become the exit liquidity.

🚨 THIS IS NOT NORMAL The stock market is about to repeat history. US MARKET HAS NEVER BEEN THIS OVERBOUGHT IN HISTORY. The setup is IDENTICAL. Every single time the MACD turns, the S&P-500 has a massive crash. I spent 14 hours researching this, and you MUST know what comes next: Back in 2000, markets looked unstoppable. Momentum was strong. Confidence was high. And then everything broke. Billions were erased. Portfolios were crushed. And the dump was brutal. Right now, the chart is lining up almost point for point. Same breakout. Same overextension. Same false sense of security. And the warning signs are flashing. Valuations are stretched. Liquidity is tightening. Volatility is waking up. And risk is building underneath the surface. Most investors still don’t see it. Because at the top, everything feels normal. That’s how every major correction starts. Optimism peaks. Positioning gets crowded. And complacency takes over. Then the reversal begins. Fast. And once momentum flips, there is no gradual exit. There is only repricing. The market does not wait. It resets. And when it does, it moves violently. Right now, there are three paths ahead: 1⃣ SOFT RESET The market cools off. Valuations compress. Momentum stabilizes. 2⃣ DEEP CORRECTION Selling accelerates. Fear returns. Risk assets dump lower. 3⃣ FULL DOT-COM STYLE COLLAPSE Support breaks. Panic spreads. Liquidity disappears. Forced selling takes over. That is where real damage happens. Because when leverage unwinds, everything gets hit. Stocks. Crypto. Speculative assets. EVERYTHING. The chart is there. The setup is there. And history is staring investors in the face. Watch price action. Watch liquidity. Watch volatility. Because if this pattern completes, the next move will be impossible to ignore. And by the time everyone sees it - the market will already be lower. I’ve spent 10 years studying markets, and I’ve called most major tops and bottoms along the way. And I’ll call it again in 2026. Follow me and turn notifications on before it’s too late. Don’t become the exit liquidity.

DANNY

142,432 Aufrufe • vor 1 Monat

Ever Heard of a Metric in Differential Geometry? How About a Geodesic? These two ideas are central to how Mathematics and Physics describe Spacetime. A metric is how a surface measures distance and angle. A geodesic is the path that counts as "straight" after that measuring rule is chosen. Once the metric changes from point to point, straightness is no longer something you judge by eye. On a curved surface, the shortest paths are geodesics. They are chosen by the metric. Take a surface written as r(x,y) = (x, y, f(x,y)) Its metric is gᵢⱼ = ∂ᵢr · ∂ⱼr A geodesic q(t) = (x(t), y(t)) obeys q̈ᵏ + Γᵏᵢⱼ q̇ᶦq̇ʲ = 0 where Γᵏᵢⱼ are the Christoffel symbols of the surface metric. Launch many almost-parallel paths. At the start, they look like a clean beam until curvature takes over. Some paths focus, others separate and some slide around ridges. The surface is essentially the rulebook for motion. The shortest path is local. The geometry remembers everything. #DifferentialGeometry #Geodesics #RiemannianGeometry #MathematicalPhysics #Curvature #TensorCalculus #AppliedMathematics #Geometry #ScienceAnimation

Ever Heard of a Metric in Differential Geometry? How About a Geodesic? These two ideas are central to how Mathematics and Physics describe Spacetime. A metric is how a surface measures distance and angle. A geodesic is the path that counts as "straight" after that measuring rule is chosen. Once the metric changes from point to point, straightness is no longer something you judge by eye. On a curved surface, the shortest paths are geodesics. They are chosen by the metric. Take a surface written as r(x,y) = (x, y, f(x,y)) Its metric is gᵢⱼ = ∂ᵢr · ∂ⱼr A geodesic q(t) = (x(t), y(t)) obeys q̈ᵏ + Γᵏᵢⱼ q̇ᶦq̇ʲ = 0 where Γᵏᵢⱼ are the Christoffel symbols of the surface metric. Launch many almost-parallel paths. At the start, they look like a clean beam until curvature takes over. Some paths focus, others separate and some slide around ridges. The surface is essentially the rulebook for motion. The shortest path is local. The geometry remembers everything. #DifferentialGeometry #Geodesics #RiemannianGeometry #MathematicalPhysics #Curvature #TensorCalculus #AppliedMathematics #Geometry #ScienceAnimation

Mathelirium

22,170 Aufrufe • vor 19 Tagen

Bridgewater doesn't have 500 positions they have 5 exposures that explain 78% of everything those 500 positions do this video shows what that looks like in 3D PCA Risk-Mode Trajectory. three axes: PC1, PC2, PC3 each one is a principal component extracted from the return matrix of the entire market PC1 is broad market direction. it alone explains roughly 40% of all stock movement PC2 separates growth from value. another 15% PC3 captures rate sensitivity. another 10% three invisible forces. 65% of the variance in every stock you've ever traded the dot moving through that 3D space is where the market is right now when the dot drifts toward a corner, the market is concentrating into one regime when it sits in the center, forces are balanced and directional trades are noise quant desks don't watch that dot for fun. they use its position to size every trade in the book if PC1 is dominating, stock picking is pointless because everything moves together if PC2 is leading, the value vs growth rotation is the only trade that matters if PC3 spikes, interest rate sensitivity is driving everything and your "stock pick" is really a rate bet you didn't know you made > PCA: Karl Pearson, 1901 > used at Bridgewater, AQR, Two Sigma for factor decomposition since the 1990s > this visualization: free, public, 29 seconds > scipy builds PCA in 3 lines of Python retail analyzes 500 tickers and thinks they're making 500 decisions quant desks decompose the same 500 into 5 forces and make 5 decisions one is complexity. the other is the math that simplifies it full breakdown in the video below

Bridgewater doesn't have 500 positions they have 5 exposures that explain 78% of everything those 500 positions do this video shows what that looks like in 3D PCA Risk-Mode Trajectory. three axes: PC1, PC2, PC3 each one is a principal component extracted from the return matrix of the entire market PC1 is broad market direction. it alone explains roughly 40% of all stock movement PC2 separates growth from value. another 15% PC3 captures rate sensitivity. another 10% three invisible forces. 65% of the variance in every stock you've ever traded the dot moving through that 3D space is where the market is right now when the dot drifts toward a corner, the market is concentrating into one regime when it sits in the center, forces are balanced and directional trades are noise quant desks don't watch that dot for fun. they use its position to size every trade in the book if PC1 is dominating, stock picking is pointless because everything moves together if PC2 is leading, the value vs growth rotation is the only trade that matters if PC3 spikes, interest rate sensitivity is driving everything and your "stock pick" is really a rate bet you didn't know you made > PCA: Karl Pearson, 1901 > used at Bridgewater, AQR, Two Sigma for factor decomposition since the 1990s > this visualization: free, public, 29 seconds > scipy builds PCA in 3 lines of Python retail analyzes 500 tickers and thinks they're making 500 decisions quant desks decompose the same 500 into 5 forces and make 5 decisions one is complexity. the other is the math that simplifies it full breakdown in the video below

delost

48,015 Aufrufe • vor 14 Tagen