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A Nobel Prize-winning volatility model was turned into a trading filter with a reported 72% hit rate. The original framework came from economist Robert Engle. The new version answers one question before a trader risks any money: “Will tomorrow have enough price movement to trade?” On the example shown,...

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A+ NQ setup has exactly three parts. 1. Statistical bias: Probability Map shows 75%+ to one side. Not an opinion. Backtested across 10 years of NQ session data. That number narrows the playing field before price moves an inch. 2. The sweep: Liquidity is resting in the opposite direction. When price grabs it, that is not a fake-out. That is the fuel for the real move. You were expecting it. You were watching for it. 3. The entry model: After the sweep, the structure confirms. iFVG / CISD. A defined ICT concept with clear invalidation. Not a hope, not a gut feel. A model with a precise entry and a reason to be there. Probability tells you where. The sweep tells you when. The entry model tells you how. Remove any one of the three and you do not have an edge. You have a trade. How many of these boxes do you tick before you pull the trigger?
1:01

A+ NQ setup has exactly three parts. 1. Statistical bias: Probability Map shows 75%+ to one side. Not an opinion. Backtested across 10 years of NQ session data. That number narrows the playing field before price moves an inch. 2. The sweep: Liquidity is resting in the opposite direction. When price grabs it, that is not a fake-out. That is the fuel for the real move. You were expecting it. You were watching for it. 3. The entry model: After the sweep, the structure confirms. iFVG / CISD. A defined ICT concept with clear invalidation. Not a hope, not a gut feel. A model with a precise entry and a reason to be there. Probability tells you where. The sweep tells you when. The entry model tells you how. Remove any one of the three and you do not have an edge. You have a trade. How many of these boxes do you tick before you pull the trigger?

Herman Trading

20,079 Aufrufe • vor 2 Monaten

"The worst trade is a trade that you make money on. Because then you convince yourself bad trades will make you money, and you lose a lot going forward" Tillman Holloway on why you can't let the market drive you into emotional decisions "The intention is to not let the conditions of the market drive you into an emotional state that then leads you into a decision. Those decisions most of the time are bad ones" "There's an old adage my dad and my granddad used to tell me. The worst trade is a trade that you make money on. That's a bad trade because then you convince yourself that bad trades will make you money" "You gotta have a strategy, and you gotta deploy it without emotion"
0:35

"The worst trade is a trade that you make money on. Because then you convince yourself bad trades will make you money, and you lose a lot going forward" Tillman Holloway on why you can't let the market drive you into emotional decisions "The intention is to not let the conditions of the market drive you into an emotional state that then leads you into a decision. Those decisions most of the time are bad ones" "There's an old adage my dad and my granddad used to tell me. The worst trade is a trade that you make money on. That's a bad trade because then you convince yourself that bad trades will make you money" "You gotta have a strategy, and you gotta deploy it without emotion"

The Wolf Of All Streets

15,907 Aufrufe • vor 2 Monaten

THIS GUY CONNECTED CLAUDE TO TRADINGVIEW AND CUT 200+ HOURS OF MANUAL CHART WORK 40 trades a week used to mean the same loop: open the chart, check RSI, compare EMA, write notes and wait for the next setup now Claude reads TradingView 24/7, tracks volume, indicators and price conditions while he is not even at the desk this is not a $20k trading terminal and not a quant fund setup, just one laptop, one chart and one strategy written in plain English the crazy part is not that Claude predicts the market, it is that a regular trader can remove the boring human loop from every setup ↓
0:26

THIS GUY CONNECTED CLAUDE TO TRADINGVIEW AND CUT 200+ HOURS OF MANUAL CHART WORK 40 trades a week used to mean the same loop: open the chart, check RSI, compare EMA, write notes and wait for the next setup now Claude reads TradingView 24/7, tracks volume, indicators and price conditions while he is not even at the desk this is not a $20k trading terminal and not a quant fund setup, just one laptop, one chart and one strategy written in plain English the crazy part is not that Claude predicts the market, it is that a regular trader can remove the boring human loop from every setup ↓

Gipp 🦅

55,610 Aufrufe • vor 2 Monaten

Qullamaggie on Feeling Like a Genius, It's The Market Not You “A melt-up market is when everything is going straight up. And it becomes too easy to make money. You start feeling like a genius — that’s a melt-up market. Trust me, you are not a genius. None of you. It’s the market, not you. No, it’s true. It’s true. Most of my money has come from periods when the market is really good. You just have to line your trading with a period where the market is really good. You know, you gotta be aggressive when the market is really good. Your job is to identify good setups in a good market — and then let the market take care of the rest. Too many people think they are the shit just because they’re making a lot of money. But that’s not really true. It’s the market, not you.”
0:56

Qullamaggie on Feeling Like a Genius, It's The Market Not You “A melt-up market is when everything is going straight up. And it becomes too easy to make money. You start feeling like a genius — that’s a melt-up market. Trust me, you are not a genius. None of you. It’s the market, not you. No, it’s true. It’s true. Most of my money has come from periods when the market is really good. You just have to line your trading with a period where the market is really good. You know, you gotta be aggressive when the market is really good. Your job is to identify good setups in a good market — and then let the market take care of the rest. Too many people think they are the shit just because they’re making a lot of money. But that’s not really true. It’s the market, not you.”

Lone

14,021 Aufrufe • vor 2 Monaten

Why does price reverse the second you enter? Because you're reacting to micro structure shifts while institutions are still executing the macro trend. Every market operates in 2 ranges simultaneously: 1) External range (macro structure) 2) Internal range (micro structure) Every market is always operating within BOTH ranges simultaneously. 1) External Ranges How do you identify it? Look at the SIZE of the pullbacks. If one pullback is twice the size of the others—that's your external break of structure. What does it tell you? Your overall bias. If the external range is bearish, you should be looking for sells. If it's bullish, you should be looking for buys. The external range doesn't tell you when NOT to trade—it tells you WHAT DIRECTION to trade. 2) Internal Ranges How do you identify it? Look for small breaks of structure that happen WITHIN your external range. These are the tiny pullbacks that barely move price compared to the major swings. What does it tell you? Short-term trading opportunities. You CAN trade internal breaks, but manage your expectations. These aren't trend reversals—they're temporary counter-moves that create pullbacks before price continues with the external trend. The internal range tells you when there's a short-term trade setup, but NOT to expect a full reversal. In the video below, I've explained what happens when you trade internal breaks without identifying the external ranges (and how to solve this): — This is just one concept from my complete trading framework. We also cover how to identify when external structure is actually shifting, the 3 timeframes every trader needs to understand and how to identify discount zones for entry points. Just comment "RANGES" and the full breakdown will automatically be DM'd to you in the next few minutes.
4:56

Why does price reverse the second you enter? Because you're reacting to micro structure shifts while institutions are still executing the macro trend. Every market operates in 2 ranges simultaneously: 1) External range (macro structure) 2) Internal range (micro structure) Every market is always operating within BOTH ranges simultaneously. 1) External Ranges How do you identify it? Look at the SIZE of the pullbacks. If one pullback is twice the size of the others—that's your external break of structure. What does it tell you? Your overall bias. If the external range is bearish, you should be looking for sells. If it's bullish, you should be looking for buys. The external range doesn't tell you when NOT to trade—it tells you WHAT DIRECTION to trade. 2) Internal Ranges How do you identify it? Look for small breaks of structure that happen WITHIN your external range. These are the tiny pullbacks that barely move price compared to the major swings. What does it tell you? Short-term trading opportunities. You CAN trade internal breaks, but manage your expectations. These aren't trend reversals—they're temporary counter-moves that create pullbacks before price continues with the external trend. The internal range tells you when there's a short-term trade setup, but NOT to expect a full reversal. In the video below, I've explained what happens when you trade internal breaks without identifying the external ranges (and how to solve this): — This is just one concept from my complete trading framework. We also cover how to identify when external structure is actually shifting, the 3 timeframes every trader needs to understand and how to identify discount zones for entry points. Just comment "RANGES" and the full breakdown will automatically be DM'd to you in the next few minutes.

The Trading Geek (Brad Goh)

21,361 Aufrufe • vor 6 Monaten

Sam Altman just handed every startup founder a one-question autopsy. Altman: “If you’re building something on GPT-4 that a reasonable observer would say we’re going to steamroll you.” Not might. Not could. Going to. He said it with the calm of someone describing weather. Because to him it is weather. The model improves. Whatever was built on the old version’s weaknesses gets washed away. That is not strategy. That is erosion. And most founders are building on the erosion line. They find a gap in the current model. They wrap a product around it. They raise money. They hire. They scale. Then OpenAI releases the next version and the gap closes and the product has no reason to exist anymore. Altman: “When we just do our fundamental job, which is make the model better with every crank, then you get the ‘OpenAI killed my startup’ meme.” He is telling you directly. They are not hunting you. They are not even thinking about you. They are just improving the model. You happen to be standing where the improvement lands. That is the part founders refuse to hear. OpenAI does not need to compete with you. It just needs to keep doing exactly what it was already doing and your entire company disappears as a side effect. You are not a competitor. You are a temporary symptom of incomplete intelligence. The moment the intelligence completes you become nothing. Then Brad Lightcap delivered the cleanest diagnostic ever spoken in venture capital. Lightcap: “Ask if a 100x improvement in the model is something they’re excited about.” One question. The entire investment thesis reduced to a single binary. Does the next model make your company more powerful or does it make your company pointless. There is no middle ground. Lightcap: “We know the companies that come to us saying, ‘We want the next model. When is it coming out? I want to be the first to try it.’” These companies built something that feeds on intelligence. The smarter the model gets the more their product can do. They are not threatened by progress. They are starving for it. Then there are the companies Lightcap never hears from. The ones who go quiet when a new model drops. The ones who read the release notes like a death sentence. The ones privately praying the next generation takes longer because every improvement shrinks the ground beneath them. If you are hoping the model stays roughly where it is you have already told the market everything it needs to know about your company. You are not building on intelligence. You are building on the absence of it. Altman: “95% of the world should be betting on the latter category.” The latter category is simple. Assume the model keeps getting better at the pace it has been getting better. Build for that world. Not the world where GPT-4 is the ceiling. The world where GPT-4 is the floor and the ceiling has not been built yet. Then Altman told a story that should be framed on the wall of every startup in the country. A medical AI company came to him that morning. They were not complaining about the model. They were not worried about being replaced. They were demanding it improve faster. Altman: “Here’s how many people are dying every day you delay.” That is what alignment with the trajectory looks like. A company so deeply built on intelligence improving that every day the model stays the same is a day someone dies who did not have to. They are not building on a flaw. They are building on a future that has not arrived fast enough. That is the difference. The wrapper startup patches what the model cannot do today. The real company builds what the model will unlock tomorrow. One is running from the train. The other is laying the track. Altman told you the train is not slowing down. Lightcap told you exactly how to know which side you are on. One question. Does a 100x smarter model make you more valuable or erase you. If you had to pause before answering you already did.
2:28

Sam Altman just handed every startup founder a one-question autopsy. Altman: “If you’re building something on GPT-4 that a reasonable observer would say we’re going to steamroll you.” Not might. Not could. Going to. He said it with the calm of someone describing weather. Because to him it is weather. The model improves. Whatever was built on the old version’s weaknesses gets washed away. That is not strategy. That is erosion. And most founders are building on the erosion line. They find a gap in the current model. They wrap a product around it. They raise money. They hire. They scale. Then OpenAI releases the next version and the gap closes and the product has no reason to exist anymore. Altman: “When we just do our fundamental job, which is make the model better with every crank, then you get the ‘OpenAI killed my startup’ meme.” He is telling you directly. They are not hunting you. They are not even thinking about you. They are just improving the model. You happen to be standing where the improvement lands. That is the part founders refuse to hear. OpenAI does not need to compete with you. It just needs to keep doing exactly what it was already doing and your entire company disappears as a side effect. You are not a competitor. You are a temporary symptom of incomplete intelligence. The moment the intelligence completes you become nothing. Then Brad Lightcap delivered the cleanest diagnostic ever spoken in venture capital. Lightcap: “Ask if a 100x improvement in the model is something they’re excited about.” One question. The entire investment thesis reduced to a single binary. Does the next model make your company more powerful or does it make your company pointless. There is no middle ground. Lightcap: “We know the companies that come to us saying, ‘We want the next model. When is it coming out? I want to be the first to try it.’” These companies built something that feeds on intelligence. The smarter the model gets the more their product can do. They are not threatened by progress. They are starving for it. Then there are the companies Lightcap never hears from. The ones who go quiet when a new model drops. The ones who read the release notes like a death sentence. The ones privately praying the next generation takes longer because every improvement shrinks the ground beneath them. If you are hoping the model stays roughly where it is you have already told the market everything it needs to know about your company. You are not building on intelligence. You are building on the absence of it. Altman: “95% of the world should be betting on the latter category.” The latter category is simple. Assume the model keeps getting better at the pace it has been getting better. Build for that world. Not the world where GPT-4 is the ceiling. The world where GPT-4 is the floor and the ceiling has not been built yet. Then Altman told a story that should be framed on the wall of every startup in the country. A medical AI company came to him that morning. They were not complaining about the model. They were not worried about being replaced. They were demanding it improve faster. Altman: “Here’s how many people are dying every day you delay.” That is what alignment with the trajectory looks like. A company so deeply built on intelligence improving that every day the model stays the same is a day someone dies who did not have to. They are not building on a flaw. They are building on a future that has not arrived fast enough. That is the difference. The wrapper startup patches what the model cannot do today. The real company builds what the model will unlock tomorrow. One is running from the train. The other is laying the track. Altman told you the train is not slowing down. Lightcap told you exactly how to know which side you are on. One question. Does a 100x smarter model make you more valuable or erase you. If you had to pause before answering you already did.

Dustin

39,109 Aufrufe • vor 4 Monaten

Robert Engle was awarded the Nobel Prize for the ARCH time series model, which is probably the most used model for calculating volatility in today's markets. Now that AI is solving 80-year-old mathematical conjectures at an unprecedented speed, isn’t it time to rethink how we look at risk? This is a question being asked by Robert Engle, Marcos Lopez de Prado, and ADIA Lab (adia_lab) on Crunch. The ADIA Lab Structural Break Challenge will reward the best crunchers with a bounty of 100,000 USDC.
1:43

Robert Engle was awarded the Nobel Prize for the ARCH time series model, which is probably the most used model for calculating volatility in today's markets. Now that AI is solving 80-year-old mathematical conjectures at an unprecedented speed, isn’t it time to rethink how we look at risk? This is a question being asked by Robert Engle, Marcos Lopez de Prado, and ADIA Lab (adia_lab) on Crunch. The ADIA Lab Structural Break Challenge will reward the best crunchers with a bounty of 100,000 USDC.

Crunch (Quant/acc)

63,194 Aufrufe • vor 5 Tagen

Q showing how to buy stock that setup (opening range highs + ATR). How do I enter on this setup? usually you buy it opening range highs like when it takes out the first one minute or five minute candle but you really don't even need to look at the uh intraday chart you really don't you just have to pay attention where when are they breaking the ranges that's just visually on the daily chart like $NVAX you know if it starts breaking that 150 area you would see it on the daily chart 150 151 and then you have to pay attention to average true range okay is the stock like sometimes they gap up a little bit but you have to look, okay if I buy let's say the stock gets to like what is at 153 okay let's say and it closed at 147 today and tomorrow it uh is at 153 intraday then you just look at okay it's up six bucks intraday it's up six dollars but the average true range is 13.6 so it's up less than half of its average true range that means you can buy it as long as the good setup is good and then you have a stop at low of the day and then after three to five days you sell half move your stop to break even and just keep trail on the 10-day moving average
1:24

Q showing how to buy stock that setup (opening range highs + ATR). How do I enter on this setup? usually you buy it opening range highs like when it takes out the first one minute or five minute candle but you really don't even need to look at the uh intraday chart you really don't you just have to pay attention where when are they breaking the ranges that's just visually on the daily chart like $NVAX you know if it starts breaking that 150 area you would see it on the daily chart 150 151 and then you have to pay attention to average true range okay is the stock like sometimes they gap up a little bit but you have to look, okay if I buy let's say the stock gets to like what is at 153 okay let's say and it closed at 147 today and tomorrow it uh is at 153 intraday then you just look at okay it's up six bucks intraday it's up six dollars but the average true range is 13.6 so it's up less than half of its average true range that means you can buy it as long as the good setup is good and then you have a stop at low of the day and then after three to five days you sell half move your stop to break even and just keep trail on the 10-day moving average

Qullamaggie Wisdom

14,768 Aufrufe • vor 4 Monaten

My trading rule is simple: ALWAYS trade toward the more probable side. Not sometimes. Not when I feel like it. Not only when the setup looks perfect. Always. That is why I use Intelligent Balance. The indicator tells me which side is more probable. If it shows LONGS, I only look for longs. If it shows SHORTS, I only look for shorts. A clean setup against the more probable side? Ignored. A perfect iFVG against the more probable side? Ignored. CISD against the more probable side? Ignored. Because my job is not to trade every setup. My job is to wait for price to give me an entry toward the side with higher probability. The indicator gives me the side. Price action gives me the entry. Discipline keeps me out of the wrong trades. ALWAYS toward the more probable side. That one rule removes most of the noise. Would you still take a “perfect” setup against the more probable side?
0:50

My trading rule is simple: ALWAYS trade toward the more probable side. Not sometimes. Not when I feel like it. Not only when the setup looks perfect. Always. That is why I use Intelligent Balance. The indicator tells me which side is more probable. If it shows LONGS, I only look for longs. If it shows SHORTS, I only look for shorts. A clean setup against the more probable side? Ignored. A perfect iFVG against the more probable side? Ignored. CISD against the more probable side? Ignored. Because my job is not to trade every setup. My job is to wait for price to give me an entry toward the side with higher probability. The indicator gives me the side. Price action gives me the entry. Discipline keeps me out of the wrong trades. ALWAYS toward the more probable side. That one rule removes most of the noise. Would you still take a “perfect” setup against the more probable side?

Herman Trading

22,826 Aufrufe • vor 1 Monat

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated
1:23:35

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated

Moon Dev

11,948 Aufrufe • vor 4 Monaten

I Created a 520% Trading Strategy With One Prompt I have been testing the just-released “Index” product by Fraction AI. This is basically the “ChatGPT for trading,” where you can: > explain your trading strategy in one prompt > let agents create it for you > backtest it with real market data With one prompt, I was able to create a trading strategy that returned 520% APY with a 93% win rate. The prompt is in the video, but basically, it is long $BTC and $HYPE while shorting $SOL. Impressive how easy it is today to create and backtest incredibly profitable trading strategies. Extra note: the free version is already very powerful. I do NOT have the premium account.
0:31

I Created a 520% Trading Strategy With One Prompt I have been testing the just-released “Index” product by Fraction AI. This is basically the “ChatGPT for trading,” where you can: > explain your trading strategy in one prompt > let agents create it for you > backtest it with real market data With one prompt, I was able to create a trading strategy that returned 520% APY with a 93% win rate. The prompt is in the video, but basically, it is long $BTC and $HYPE while shorting $SOL. Impressive how easy it is today to create and backtest incredibly profitable trading strategies. Extra note: the free version is already very powerful. I do NOT have the premium account.

Diego

12,594 Aufrufe • vor 3 Monaten

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

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

Livsun

188,258 Aufrufe • vor 2 Monaten

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

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

Hrundel75 🐷

12,088 Aufrufe • vor 26 Tagen

Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath. that is all it is, and it is the bluntest one there is. the same math gives you filters that lag less and cut more noise, and that gap is a real edge. this is the second half of what Simons was doing. first you accept the market is a signal buried in noise. then you build the filter that reads it, and the moving average on your chart is the crudest possible version. Oppenheim builds the real ones at the board in this lecture. here is the catch. a filter only helps if there is a real signal under the noise. smooth pure randomness and you will see a beautiful trend that means nothing. the filter is free. knowing there is a real signal worth filtering is the edge.
40:58

Alan Oppenheim, MIT professor: "Every trader alive uses a moving average. Almost none of them know it's a filter, and funds pay quants $600K for the version they were never taught." a moving average is a filter. it smooths a jumpy price to reveal the slower signal hiding underneath. that is all it is, and it is the bluntest one there is. the same math gives you filters that lag less and cut more noise, and that gap is a real edge. this is the second half of what Simons was doing. first you accept the market is a signal buried in noise. then you build the filter that reads it, and the moving average on your chart is the crudest possible version. Oppenheim builds the real ones at the board in this lecture. here is the catch. a filter only helps if there is a real signal under the noise. smooth pure randomness and you will see a beautiful trend that means nothing. the filter is free. knowing there is a real signal worth filtering is the edge.

Rossst.03

214,907 Aufrufe • vor 1 Monat

The best signal is sometimes NO signal. That is why I do not trade when Intelligent Balance shows less than 60%. Below 60% means one thing to me: NO CLEAR EDGE. And that is exactly where most traders destroy their account. They see a sweep. They see an iFVG. They see CISD. They convince themselves there is a trade. But without a strong more probable side, the setup has no real filter. For me: 60%+ = I have a side to focus on. Below 60% = I protect capital. Simple. Intelligent Balance is not only there to tell me where to trade. It is there to tell me when NOT to trade. Because forcing trades in a low-edge environment is not trading. It is gambling with extra steps. Would you skip a session if the indicator told you there is no clear edge?
0:41

The best signal is sometimes NO signal. That is why I do not trade when Intelligent Balance shows less than 60%. Below 60% means one thing to me: NO CLEAR EDGE. And that is exactly where most traders destroy their account. They see a sweep. They see an iFVG. They see CISD. They convince themselves there is a trade. But without a strong more probable side, the setup has no real filter. For me: 60%+ = I have a side to focus on. Below 60% = I protect capital. Simple. Intelligent Balance is not only there to tell me where to trade. It is there to tell me when NOT to trade. Because forcing trades in a low-edge environment is not trading. It is gambling with extra steps. Would you skip a session if the indicator told you there is no clear edge?

Herman Trading

18,993 Aufrufe • vor 1 Monat

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

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

cvxv666

98,041 Aufrufe • vor 1 Monat

The 118,000% Alpha: Building a High-Frequency AI Trading Floor with Claude Code if you think claude code is just for writing simple scripts then you are already losing to the bots that are hunting your liquidity right now. most traders are still clicking buttons while i have an ai employee running backtests on twenty eight different data sources simultaneously. i am going to show you how a strategy that returned over four hundred thousand percent was built in minutes using a secret sub agent workflow most people treat ai like a chatbot but i treat it like a quant architect that builds systems better than the devs i used to pay hundreds of thousands of dollars. there is one specific indicator combo that actually survived a stress test across tesla and bitcoin at the same time and i will reveal that logic further down. we have to talk about why your current backtests are probably lying to you before we get into the code my name is moon dev and i truly believe that code is the great equalizer in this world. for years i was the guy getting liquidated and overtrading because i was letting my emotions drive the wheel. i spent an insane amount of money hiring developers to build apps for me because i thought i was not smart enough to code myself. through that pain i realized that if i wanted to win i had to automate everything and learn to do it live on youtube for the world to see the secret to trading with claude code is not asking it for a strategy but using it to build a backtest architect. this sub agent acts as a consistent employee that understands how to test against massive datasets without getting tired. it allows me to iterate through hundreds of ideas in the time it used to take me to write one single line of python. this is how i found the strategy that hit a one hundred and eighteen thousand percent return on a single run there is a massive trap that almost every beginner falls into when they start using ai for trading. they find a strategy that looks amazing on one chart and they think they found the holy grail of wealth. that is usually just a lucky fluke or a curve fit mess that will blow up your account next week. the real secret to staying alive is the multi data testing system that claude built for me today we test every single idea against bitcoin and ethereum and solana but we also throw in apple and tesla and nvidia. if a strategy only works on crypto it is probably just riding a trend that is already over. i want to find the logic that is robust enough to handle the volatility of a meme coin and the steady grind of a blue chip stock. this is the only way to prove that the code actually has an edge in the market before we dive into the kalman filter logic i have to tell you about the dca bot i have running on solana right now. it is called housecoin and the thesis behind it is either going to make me a genius or leave me with nothing. it is buying every time we are under the five minute sma and i have been checking the transactions live. i will explain the risk management behind this "all or nothing" play shortly but first we need to look at the winners the winner of today was the acceleration bands combined with a kalman filter. the kalman filter is incredible because it helps remove the noise and lag that you get with standard moving averages. most indicators repaint which means they change their past values to look better after the price has already moved. the way i have implemented this filter prevents that trap so the results you see in the backtest are actually tradable when we ran the acceleration bands across the hourly nvidia chart it returned over two hundred percent while the underlying asset was down forty percent. that is a massive alpha gap that most people will never see because they are stuck using standard rsi settings. i have found that adding a volatility breakout with atr to this setup helps catch the moves that the banks are trying to hide. the math behind the atr breakout is what kept me from getting chopped up in the sideway ranges you might be wondering why i am giving all this code away for free on github instead of keeping it in a vault. it is because i remember what it felt like to be on the other side of the trade losing money every single day. i want to build a community of quads that are all researching and backtesting together. the goal is to chase the legacy of jim simons who proved that math and code are the only things that matter in the long run the rbi system is the framework that i follow every single day without exception. it stands for research and backtest and implement. most traders skip the middle step because they are too impatient to see the results. they hear a rumor on twitter and they buy the top only to get liquidated when the whales decide to take profits. if you do not backtest your ideas then you are just gambling with your life savings i am spending around forty to one hundred dollars a day on claude opus tokens because it is a drop in the bucket compared to what a developer would charge. this ai does not need a lunch break and it does not get bored when i ask it to create sixty different variations of a strategy. we just created five different parabolic sar versions today and found that the long only setup was the only one worth keeping. it returned sixteen thousand percent on the soul data set because it stayed out of the short side traps shorting crypto is extremely dangerous and usually not worth the stress for most people. i have found that focusing on long only strategies with a tight trail stop is the most consistent way to grow an account. the sub agent architect allowed me to verify this across twenty five data sources in less than ten minutes. this speed of iteration is the only way to stay ahead of the curve in an industry that changes every few seconds the dca bot i mentioned earlier is still grinding away and buying the dips as we speak. i have built it to be a long term play where i am slowly accumulating a position in housecoin based on smas. if the price stays under the moving average the bot keeps buying and if it goes above then it sits on its hands. it is a simple logic but it removes the human desire to "buy the moon" when the price is already overextended i found that the camarilla pivot indicator was mostly trash today when we ran the numbers. even though it looks fancy on a chart the backtest showed negative expectancy across almost every asset we tried. this is why backtesting is so important because it kills the "indicator porn" that influencers use to sell you courses. i would much rather know that a strategy is a loser now than find out after i put real money on the line the true secret to using claude code is to treat it like a partner and not just a tool. i ask it to find anomalies and then i ask it to prove me wrong by testing it against the worst market conditions in history. if a strategy can survive the 2022 crypto crash and the 2020 stock market dip then i might consider it for a live run. we are stepping on the gas every single day because there are always new anomalies popping up if you are fast enough to find them i have uploaded over twenty five new backtests to the github today for everyone to use. code is the equalizer because it does not care about your background or how much money you started with. if you can write the logic and prove the edge then the market has to pay you. i am going to keep building in public and showing the wins and the losses because that is the only way to stay real in this space the final piece of the puzzle is the mindset of iteration over perfection. i would rather run a hundred messy backtests today than spend a month trying to write one perfect script. the ai allows me to fail fast so that i can find the winners that actually move the needle. my housecoin dca bot is a testament to that philosophy of just building and letting the systems do the heavy lifting for me if you are still trading by hand you are playing a game that is rigged against you by the biggest firms in the world. they have the best servers and the best data and the best phds but they do not have your specific creativity. when you combine your ideas with the power of claude code you are creating a custom weapon that they have never seen before. i will see you in the code and we will keep chasing the goat until we find that ultimate edge
1:55:47

The 118,000% Alpha: Building a High-Frequency AI Trading Floor with Claude Code if you think claude code is just for writing simple scripts then you are already losing to the bots that are hunting your liquidity right now. most traders are still clicking buttons while i have an ai employee running backtests on twenty eight different data sources simultaneously. i am going to show you how a strategy that returned over four hundred thousand percent was built in minutes using a secret sub agent workflow most people treat ai like a chatbot but i treat it like a quant architect that builds systems better than the devs i used to pay hundreds of thousands of dollars. there is one specific indicator combo that actually survived a stress test across tesla and bitcoin at the same time and i will reveal that logic further down. we have to talk about why your current backtests are probably lying to you before we get into the code my name is moon dev and i truly believe that code is the great equalizer in this world. for years i was the guy getting liquidated and overtrading because i was letting my emotions drive the wheel. i spent an insane amount of money hiring developers to build apps for me because i thought i was not smart enough to code myself. through that pain i realized that if i wanted to win i had to automate everything and learn to do it live on youtube for the world to see the secret to trading with claude code is not asking it for a strategy but using it to build a backtest architect. this sub agent acts as a consistent employee that understands how to test against massive datasets without getting tired. it allows me to iterate through hundreds of ideas in the time it used to take me to write one single line of python. this is how i found the strategy that hit a one hundred and eighteen thousand percent return on a single run there is a massive trap that almost every beginner falls into when they start using ai for trading. they find a strategy that looks amazing on one chart and they think they found the holy grail of wealth. that is usually just a lucky fluke or a curve fit mess that will blow up your account next week. the real secret to staying alive is the multi data testing system that claude built for me today we test every single idea against bitcoin and ethereum and solana but we also throw in apple and tesla and nvidia. if a strategy only works on crypto it is probably just riding a trend that is already over. i want to find the logic that is robust enough to handle the volatility of a meme coin and the steady grind of a blue chip stock. this is the only way to prove that the code actually has an edge in the market before we dive into the kalman filter logic i have to tell you about the dca bot i have running on solana right now. it is called housecoin and the thesis behind it is either going to make me a genius or leave me with nothing. it is buying every time we are under the five minute sma and i have been checking the transactions live. i will explain the risk management behind this "all or nothing" play shortly but first we need to look at the winners the winner of today was the acceleration bands combined with a kalman filter. the kalman filter is incredible because it helps remove the noise and lag that you get with standard moving averages. most indicators repaint which means they change their past values to look better after the price has already moved. the way i have implemented this filter prevents that trap so the results you see in the backtest are actually tradable when we ran the acceleration bands across the hourly nvidia chart it returned over two hundred percent while the underlying asset was down forty percent. that is a massive alpha gap that most people will never see because they are stuck using standard rsi settings. i have found that adding a volatility breakout with atr to this setup helps catch the moves that the banks are trying to hide. the math behind the atr breakout is what kept me from getting chopped up in the sideway ranges you might be wondering why i am giving all this code away for free on github instead of keeping it in a vault. it is because i remember what it felt like to be on the other side of the trade losing money every single day. i want to build a community of quads that are all researching and backtesting together. the goal is to chase the legacy of jim simons who proved that math and code are the only things that matter in the long run the rbi system is the framework that i follow every single day without exception. it stands for research and backtest and implement. most traders skip the middle step because they are too impatient to see the results. they hear a rumor on twitter and they buy the top only to get liquidated when the whales decide to take profits. if you do not backtest your ideas then you are just gambling with your life savings i am spending around forty to one hundred dollars a day on claude opus tokens because it is a drop in the bucket compared to what a developer would charge. this ai does not need a lunch break and it does not get bored when i ask it to create sixty different variations of a strategy. we just created five different parabolic sar versions today and found that the long only setup was the only one worth keeping. it returned sixteen thousand percent on the soul data set because it stayed out of the short side traps shorting crypto is extremely dangerous and usually not worth the stress for most people. i have found that focusing on long only strategies with a tight trail stop is the most consistent way to grow an account. the sub agent architect allowed me to verify this across twenty five data sources in less than ten minutes. this speed of iteration is the only way to stay ahead of the curve in an industry that changes every few seconds the dca bot i mentioned earlier is still grinding away and buying the dips as we speak. i have built it to be a long term play where i am slowly accumulating a position in housecoin based on smas. if the price stays under the moving average the bot keeps buying and if it goes above then it sits on its hands. it is a simple logic but it removes the human desire to "buy the moon" when the price is already overextended i found that the camarilla pivot indicator was mostly trash today when we ran the numbers. even though it looks fancy on a chart the backtest showed negative expectancy across almost every asset we tried. this is why backtesting is so important because it kills the "indicator porn" that influencers use to sell you courses. i would much rather know that a strategy is a loser now than find out after i put real money on the line the true secret to using claude code is to treat it like a partner and not just a tool. i ask it to find anomalies and then i ask it to prove me wrong by testing it against the worst market conditions in history. if a strategy can survive the 2022 crypto crash and the 2020 stock market dip then i might consider it for a live run. we are stepping on the gas every single day because there are always new anomalies popping up if you are fast enough to find them i have uploaded over twenty five new backtests to the github today for everyone to use. code is the equalizer because it does not care about your background or how much money you started with. if you can write the logic and prove the edge then the market has to pay you. i am going to keep building in public and showing the wins and the losses because that is the only way to stay real in this space the final piece of the puzzle is the mindset of iteration over perfection. i would rather run a hundred messy backtests today than spend a month trying to write one perfect script. the ai allows me to fail fast so that i can find the winners that actually move the needle. my housecoin dca bot is a testament to that philosophy of just building and letting the systems do the heavy lifting for me if you are still trading by hand you are playing a game that is rigged against you by the biggest firms in the world. they have the best servers and the best data and the best phds but they do not have your specific creativity. when you combine your ideas with the power of claude code you are creating a custom weapon that they have never seen before. i will see you in the code and we will keep chasing the goat until we find that ultimate edge

Moon Dev

18,650 Aufrufe • vor 5 Monaten

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen
49:49

I Built a 37.0 Profit Factor Bot by Cracking Every TradingView Source Code tradingview is a gold mine hiding in plain sight and i just found the master key to unlock every single secret hidden within its community scripts. most traders spend their entire lives staring at candles and hoping for a miracle while the actual alpha is buried in the open source code that nobody bothers to look at. i used to be that guy who sat there getting liquidated at three in the morning because i thought i could outplay the market with my gut feeling and some drawings on a screen. it turns out that the game is completely rigged against you if you are trading manually but there is a specific way to flip the script. i am going to show you how to stop guessing and start knowing exactly what works across every possible market condition before you ever risk a single dollar. i spent years losing money and thousands on developers because i thought i was not smart enough to code the systems myself but i was wrong. the first step to cracking the market is realizing that every indicator on the super charts has a source code section that is completely open to the public. you can literally scroll through the community scripts and pull the exact logic for thousands of different strategies that people claim are the holy grail of trading. but the secret is not just having the code because most of these indicators are actually garbage that will blow your account up in a week. this is where the real loop opens because you need a way to test these ideas across twenty five different data sets in seconds rather than months. i use a custom setup with ai agents specifically a sub agent i call the backtest architect to handle the heavy lifting of turning pine script into python code. the goal is to create a factory where you can feed in a raw indicator and get back a full report on its expectancy and profit factor without lifting a finger. most people find one strategy and marry it for life but a real data dog knows that you have to iterate to success or you will get left behind. i am running eighty one different backtests right now because i know that ninety percent of what i find will be trash but that remaining ten percent is where the wealth is made. the backtest architect knows exactly how to structure the folders and data paths so that we are testing everything from the base indicator to complex versions with filters. you might think that popular tools like fibonacci or order blocks are the way to go because everyone on social media talks about them like they are law. but when i actually ran the numbers through the machine the results were embarrassing and most of those strategies just resulted in negative expectancy. it is a dangerous trap to follow the crowd into a trade just because some guru said a certain level was important when the data shows it is a coin flip at best. the dynamic swing indicator was one of the few that actually held its weight during the recent massive testing sessions we ran. it was pulling in profit factors of over thirty seven with annualized returns that look too good to be true until you see the trade list. we combined it with filters like the adx and the money flow index to see if we could refine the signals and the results were absolutely staggering. when you have a system that can run through forty data sets while you are drinking tea you realize that manual trading is a form of self harm. i realized this after spending hundreds of thousands on apps and devs only to find out that i could just learn to build these bots myself live on the internet. the speed of iteration is the only thing that matters in this game because the faster you can fail the faster you can find the one strategy that actually prints. one of the biggest hurdles i faced was thinking that i needed to be a math genius or a senior engineer to automate my trading systems. the truth is that code is the great equalizer because it allows a regular person to compete with massive hedge funds by using the same logic and speed. i decided to learn everything in public because i wanted people to see the process of losing money with liquidations and then finally finding a path to automation. the reality of the market is that it moves in cycles and what worked yesterday will almost certainly fail tomorrow unless you are constantly testing. that is why i built the agents to automatically look through the results folder and rank the top performers based on a composite score. it takes all the emotion out of the process because i am no longer looking for a reason to enter a trade i am just looking at a csv file that tells me the truth. if you are still drawing lines on a chart and hoping for the best you are basically playing a game of chance against a high speed casino. the transition from a manual trader to a systems builder is the single most important pivot you will ever make in your life. it is not about being right or wrong it is about having a positive expectancy that has been proven across thousands of trades and multiple years of history. i had to fix a few errors in the short selling logic where the agents were getting confused between maximum and minimum values for take profit levels. these tiny bugs are the difference between a winning system and a blown account so you have to be willing to dive into the code and refine the machine. but once the system is tuned and the sub agents are running it becomes a beautiful workflow that functions entirely without your input. we are currently moving through the editors picks and the trending indicators one by one because i want to have a database of every single strategy on the platform. being a data dog means you never stop searching for that edge and you never settle for a strategy that just looks okay on a single chart. you have to demand excellence from your code because the market will not give you a single inch of mercy if you are lazy with your research. the ultimate goal is to have fully automated systems trading for you so you can focus on scaling rather than staring at a screen for ten hours a day. i am already up to over eighty backtests in this single session and i plan on hitting hundreds more by the end of the week. once you realize that you can crack the code of any indicator you see on the internet you will never look at a chart the same way again. this is the power of using agents to bridge the gap between a raw idea and a finished trading bot that actually works in the real world. i am done with getting liquidated and i am done with the stress of over trading because the code handles everything with cold precision. the path to success is paved with data and if you are not willing to automate your process you are just waiting for your next liquidation to happen

Moon Dev

26,010 Aufrufe • vor 5 Monaten

The Great Equalizer: How I Iterated Through 90+ Strategies to Automate My Financial Freedom ninety strategies sounds like a death wish but it is actually the only way to find your edge in a market designed to liquidate you. most traders are out here gambling with their rent money while the big players are using automated systems to harvest their liquidations. i know this because i spent hundreds of thousands of dollars on developers for apps thinking i could never code myself. i was getting wrecked by over trading and watching my accounts hit zero while i slept. code became the great equalizer for me because it removed the emotion that was killing my bankroll. i decided to learn to code live so i could iterate to success and now i have fully automated systems trading for me instead of getting liquidated by every wick. i just saw someone lose ten million dollars in a single month because they were trading by hand and got addicted to the screen. you have to understand that if you are not automating you are the exit liquidity for someone who is. the reality of advanced futures trading is not about finding one holy grail bot that prints money forever. it is about research and back testing until you find a strategy that has a statistical advantage. one of the most slept on concepts is variable risk scaling where you actually change your position size based on how volatile the market is. instead of just betting the same amount every time you increase your size when volatility is low and scale back when the market starts moving like crazy. this keeps you in the game during the draw downs that usually wipe people out. most people do the opposite and revenge trade with bigger size when they are losing which is the fastest way to the cemetery. i used to think i needed to be the smartest guy in the room to make this work but i realized i just needed to be the most disciplined with my risk parameters. there is a secret hidden in funding rates and basis trading that most retail traders never even look at. while everyone else is trying to guess if bitcoin is going to the moon or the floor you can actually make consistent money through funding rate arbitrage. you basically buy the asset in the spot market and simultaneously sell it in the futures market when the funding rate is high. you just sit there and collect the interest payments from the gamblers who are over leveraged on the other side. it is basically free money if you can manage the fees and keep your execution precise. i used to ignore these low yield plays because i wanted the big home runs but those home runs usually came with massive strikeouts. now i look for these carry trades as a way to keep the equity curve moving up and to the right while others are sweating over every price change. most traders fail because they use lagging indicators and expect them to predict the future with one hundred percent accuracy. the truth is that even the best trend following strategies like the golden cross or moving average crossovers only have about sixty five percent accuracy. you have to combine these with filters like the average directional index or relative strength index to make sure you are not just buying a fake breakout. a lot of people get chopped up in sideways markets because they do not have a trend strength filter to tell them to stay out of the trade. i learned to use multiple time frames to confirm my breakouts because if the one hour and the four hour charts are not saying the same thing then the trade is probably a trap. you have to be a searcher looking for those golden nuggets of alpha buried in mountains of data. i used to think that machine learning and genetic algorithms were just buzzwords that did not actually work for trading. then i realized that the 1990s tech trap is real and if you are still using basic indicators without any optimization you are decades behind. genetic algorithms are wild because they simulate natural selection to find the best parameters for your strategy through trial and error. you can actually build an environment where your bot learns from its own mistakes and optimizes its decision making process over time. i spent so much time thinking i was not smart enough to do this but once i started iterating live i found that the machines are much better at following rules than i ever was. code is the only way to compete with the high frequency firms that are looking for any tiny mispricing in the order book. slippage and bad execution will eat your profits faster than a bad trade ever could if you are not careful. most people just hit the market buy button and pay the spread and the fees without a second thought. you should be using smart order routing and limit orders to capture the bid ask spread instead of paying it to the market makers. i started using time weighted average price execution to spread my larger orders out over time so i did not move the market against myself. it is these tiny details in execution that separate the professional quants from the people who are just playing around. i had to learn this the hard way after losing a fortune on bad entries and exits that could have been avoided with a few lines of code. the ultimate goal of all of this is to build a compounding machine that grows your capital while you are living your life. you have to automate the reinvestment of your profits so that your position sizes grow as your account grows without you having to manually adjust anything. i like to use automated compounding algorithms that take a portion of my wins and put them back into the systems that are performing the best. this creates a snowball effect where your returns start to accelerate as the base capital increases. it took me years to realize that i did not need to be at the desk for eighteen hours a day to make life changing money. i just needed to build a system that was smarter and more disciplined than my own human brain. cross asset skew and volatility surface arbitrage are where the real quants play when the market gets efficient. you can look for mispricings between highly correlated assets like bitcoin and ethereum and trade the spread between them. when one asset gets overvalued relative to the other you short the leader and long the laggard until they revert back to the mean. this is a much safer way to trade because you are not betting on the direction of the market but rather the relationship between two assets. i spent a lot of money trying to guess the next big move before i realized that trading the relationship between assets was much more consistent. iteration is the only way to find these winks in the market that the average trader is completely blind to. it is a cold world in finance and most people are out here trying to step on your neck to get ahead. i believe that sharing this knowledge is important because code is the only thing that can give a regular person a fighting chance against the institutions. i started from zero and learned everything through failing and losing money until i finally figured out how to automate. now i spend my time building and testing instead of worrying about the next liquidation candle. you have to decide today if you want to keep being the exit liquidity or if you want to start building your own systems. the tools are all there and the data is accessible if you are willing to put in the work and stop negotiating with yourself. successful trading is not about being lucky it is about being prepared and having a system that can handle any market regime. whether the market is in a bull run or a total crash your bots should know exactly what to do based on the rules you have coded into them. i use risk weighted allocation to make sure that my capital is always moving toward the strategies with the highest sharp ratio and the lowest volatility. this keeps the portfolio stable even when the crypto market is going through its typical insane swings. i finally found peace in this game because i know that my automated systems are following the math while everyone else is following their feelings. code is the great equalizer and it is time for you to start using it to protect your future and build your empire there are over ninety strategies you can test and most of them will not work for your specific style but you only need one or two to change your life. i have built a fat list of ideas from research and i spend every day back testing and refining them to stay ahead of the curve. do not let the fear of coding stop you from taking control of your financial destiny because i am living proof that anyone can learn. i would rather spend my time iterating to success than getting liquidated by some random news event that i could not predict. the journey from losing hundreds of thousands to fully automated success was long but it was the best investment i ever made. keep your heart open and lead with love in this game and i promise the universe will start passing you those golden nuggets of alpha you have been searching for
2:40:29

The Great Equalizer: How I Iterated Through 90+ Strategies to Automate My Financial Freedom ninety strategies sounds like a death wish but it is actually the only way to find your edge in a market designed to liquidate you. most traders are out here gambling with their rent money while the big players are using automated systems to harvest their liquidations. i know this because i spent hundreds of thousands of dollars on developers for apps thinking i could never code myself. i was getting wrecked by over trading and watching my accounts hit zero while i slept. code became the great equalizer for me because it removed the emotion that was killing my bankroll. i decided to learn to code live so i could iterate to success and now i have fully automated systems trading for me instead of getting liquidated by every wick. i just saw someone lose ten million dollars in a single month because they were trading by hand and got addicted to the screen. you have to understand that if you are not automating you are the exit liquidity for someone who is. the reality of advanced futures trading is not about finding one holy grail bot that prints money forever. it is about research and back testing until you find a strategy that has a statistical advantage. one of the most slept on concepts is variable risk scaling where you actually change your position size based on how volatile the market is. instead of just betting the same amount every time you increase your size when volatility is low and scale back when the market starts moving like crazy. this keeps you in the game during the draw downs that usually wipe people out. most people do the opposite and revenge trade with bigger size when they are losing which is the fastest way to the cemetery. i used to think i needed to be the smartest guy in the room to make this work but i realized i just needed to be the most disciplined with my risk parameters. there is a secret hidden in funding rates and basis trading that most retail traders never even look at. while everyone else is trying to guess if bitcoin is going to the moon or the floor you can actually make consistent money through funding rate arbitrage. you basically buy the asset in the spot market and simultaneously sell it in the futures market when the funding rate is high. you just sit there and collect the interest payments from the gamblers who are over leveraged on the other side. it is basically free money if you can manage the fees and keep your execution precise. i used to ignore these low yield plays because i wanted the big home runs but those home runs usually came with massive strikeouts. now i look for these carry trades as a way to keep the equity curve moving up and to the right while others are sweating over every price change. most traders fail because they use lagging indicators and expect them to predict the future with one hundred percent accuracy. the truth is that even the best trend following strategies like the golden cross or moving average crossovers only have about sixty five percent accuracy. you have to combine these with filters like the average directional index or relative strength index to make sure you are not just buying a fake breakout. a lot of people get chopped up in sideways markets because they do not have a trend strength filter to tell them to stay out of the trade. i learned to use multiple time frames to confirm my breakouts because if the one hour and the four hour charts are not saying the same thing then the trade is probably a trap. you have to be a searcher looking for those golden nuggets of alpha buried in mountains of data. i used to think that machine learning and genetic algorithms were just buzzwords that did not actually work for trading. then i realized that the 1990s tech trap is real and if you are still using basic indicators without any optimization you are decades behind. genetic algorithms are wild because they simulate natural selection to find the best parameters for your strategy through trial and error. you can actually build an environment where your bot learns from its own mistakes and optimizes its decision making process over time. i spent so much time thinking i was not smart enough to do this but once i started iterating live i found that the machines are much better at following rules than i ever was. code is the only way to compete with the high frequency firms that are looking for any tiny mispricing in the order book. slippage and bad execution will eat your profits faster than a bad trade ever could if you are not careful. most people just hit the market buy button and pay the spread and the fees without a second thought. you should be using smart order routing and limit orders to capture the bid ask spread instead of paying it to the market makers. i started using time weighted average price execution to spread my larger orders out over time so i did not move the market against myself. it is these tiny details in execution that separate the professional quants from the people who are just playing around. i had to learn this the hard way after losing a fortune on bad entries and exits that could have been avoided with a few lines of code. the ultimate goal of all of this is to build a compounding machine that grows your capital while you are living your life. you have to automate the reinvestment of your profits so that your position sizes grow as your account grows without you having to manually adjust anything. i like to use automated compounding algorithms that take a portion of my wins and put them back into the systems that are performing the best. this creates a snowball effect where your returns start to accelerate as the base capital increases. it took me years to realize that i did not need to be at the desk for eighteen hours a day to make life changing money. i just needed to build a system that was smarter and more disciplined than my own human brain. cross asset skew and volatility surface arbitrage are where the real quants play when the market gets efficient. you can look for mispricings between highly correlated assets like bitcoin and ethereum and trade the spread between them. when one asset gets overvalued relative to the other you short the leader and long the laggard until they revert back to the mean. this is a much safer way to trade because you are not betting on the direction of the market but rather the relationship between two assets. i spent a lot of money trying to guess the next big move before i realized that trading the relationship between assets was much more consistent. iteration is the only way to find these winks in the market that the average trader is completely blind to. it is a cold world in finance and most people are out here trying to step on your neck to get ahead. i believe that sharing this knowledge is important because code is the only thing that can give a regular person a fighting chance against the institutions. i started from zero and learned everything through failing and losing money until i finally figured out how to automate. now i spend my time building and testing instead of worrying about the next liquidation candle. you have to decide today if you want to keep being the exit liquidity or if you want to start building your own systems. the tools are all there and the data is accessible if you are willing to put in the work and stop negotiating with yourself. successful trading is not about being lucky it is about being prepared and having a system that can handle any market regime. whether the market is in a bull run or a total crash your bots should know exactly what to do based on the rules you have coded into them. i use risk weighted allocation to make sure that my capital is always moving toward the strategies with the highest sharp ratio and the lowest volatility. this keeps the portfolio stable even when the crypto market is going through its typical insane swings. i finally found peace in this game because i know that my automated systems are following the math while everyone else is following their feelings. code is the great equalizer and it is time for you to start using it to protect your future and build your empire there are over ninety strategies you can test and most of them will not work for your specific style but you only need one or two to change your life. i have built a fat list of ideas from research and i spend every day back testing and refining them to stay ahead of the curve. do not let the fear of coding stop you from taking control of your financial destiny because i am living proof that anyone can learn. i would rather spend my time iterating to success than getting liquidated by some random news event that i could not predict. the journey from losing hundreds of thousands to fully automated success was long but it was the best investment i ever made. keep your heart open and lead with love in this game and i promise the universe will start passing you those golden nuggets of alpha you have been searching for

Moon Dev

11,196 Aufrufe • vor 5 Monaten

William Sharpe, Stanford professor and Nobel economist: "Citadel and Two Sigma live and die by one number: the Sharpe ratio. It's mine. I built it to tell a skilled strategy from a lucky, reckless one." the thread above is about building a portfolio and knowing when to cut a strategy. sharpe gave the world the single number that answers the only question that matters: is this thing actually good, or just lucky and levered? return alone is a trap. a 40% year isn't impressive if you bet the farm for it. sharpe's ratio divides your return by the risk you took to get it, so a calm 15% can beat a wild 40%. it strips luck and leverage out of any track record, and that is exactly why every fund on earth judges itself by it. this is also how a desk decides when to kill a strategy. not "did it make money," but "did it make enough per unit of risk." a falling sharpe is the signal to cut, long before the P&L ever turns red. he published the math in 1964, won the nobel in 1990, and left it in this free lecture. same story i keep telling: the number that runs every trading floor is old, public, and free. here is the blind spot sharpe himself knew. the ratio assumes risk is smooth and symmetric. a strategy that quietly sells insurance shows a gorgeous sharpe for years, then one tail event erases a decade. a high sharpe is not proof you are safe. it is proof you have not met your bad day yet.
50:53

William Sharpe, Stanford professor and Nobel economist: "Citadel and Two Sigma live and die by one number: the Sharpe ratio. It's mine. I built it to tell a skilled strategy from a lucky, reckless one." the thread above is about building a portfolio and knowing when to cut a strategy. sharpe gave the world the single number that answers the only question that matters: is this thing actually good, or just lucky and levered? return alone is a trap. a 40% year isn't impressive if you bet the farm for it. sharpe's ratio divides your return by the risk you took to get it, so a calm 15% can beat a wild 40%. it strips luck and leverage out of any track record, and that is exactly why every fund on earth judges itself by it. this is also how a desk decides when to kill a strategy. not "did it make money," but "did it make enough per unit of risk." a falling sharpe is the signal to cut, long before the P&L ever turns red. he published the math in 1964, won the nobel in 1990, and left it in this free lecture. same story i keep telling: the number that runs every trading floor is old, public, and free. here is the blind spot sharpe himself knew. the ratio assumes risk is smooth and symmetric. a strategy that quietly sells insurance shows a gorgeous sharpe for years, then one tail event erases a decade. a high sharpe is not proof you are safe. it is proof you have not met your bad day yet.

Voltex

65,224 Aufrufe • vor 27 Tagen