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THE FIRST CROWBRAIN AUTONOMOUS TRADING EXPERIMENT IS COMPLETE I created a separate wallet for the system, deposited $50 and allowed the algorithm to execute its own signals for the first time. During the first five hours: $50 → $420 CROWBRAIN discovered tokens, analyzed price movement, volume and liquidity, generated... BUY / SELL signals, and opened and closed positions automatically. But then the market changed while the algorithm continued trading under the same rules. It took profits too late, re-entered after major price moves and failed to stop after a series of losing trades. Eventually, the profit disappeared and the overall result of the experiment went negative. That is exactly why I am testing it publicly. It would be easy to show only the $50 → $420 moment and stay silent about what happened afterward, but the purpose of this experiment is not to produce one impressive screenshot. It is to build a system that can control risk and perform consistently under different market conditions. Now I am adding: → automatic partial profit-taking → a dynamic stop-loss → position-size limits → a cooldown after consecutive losses → a daily loss limit → protection against re-entering after a sharp price increase → market-regime detection The first test proved that CROWBRAIN can already find opportunities and turn $50 into $420. It also showed that finding good entries means nothing without disciplined exits and proper risk management. The experiment continues. After the update, I will fund a new public wallet with another $50, restart the algorithm and show every trade - successful or not. Let’s see what CROWBRAIN learns from its first serious mistake.show more

sopersone

4,744 subscribers

33,764 次观看 • 7 天前 •via X (Twitter)

财经科学技术

Anya Rossi• Live Now

Private livecam show

13 条评论

Smed 的头像

Smed7 天前

Here's the real question. When can I have the crown trade for me? Can we have a crow fund manager?

DexorynLabs 的头像

DexorynLabs7 天前

Fast gain shocks the board.

rwaisys 的头像

rwaisys7 天前

respect for posting the part after the 420. a rule that shuts it off after 3 losses in a row would have kept most of it

sopersone 的头像

sopersone7 天前

yeap

tx 的头像

tx7 天前

hmmmm

Antonio Garcia 的头像

Antonio Garcia6 天前

hi are you make new push in your repo with this autotrade?

darrylsj 的头像

darrylsj7 天前

What is the value of posting these stories, I don’t want to call them lies but these are make believe and not true. What’s the upside of these posts ?

Sasha 的头像

Sasha7 天前

stop it ima pass out of laughter

Create.Love.Be 的头像

Create.Love.Be7 天前

Damn bro. 😎 These signals are MAD serious Yo!!! 🙏🏽

staus 的头像

staus7 天前

@grok is this guy ex huggingface dev/employee

Twolight 的头像

Twolight7 天前

You're token for what?

Create.Love.Be 的头像

Create.Love.Be7 天前

Boners every fugging where!!!! 😂

🌕Moonshot Tim 的头像

🌕Moonshot Tim7 天前

@grok is this true or fake?

相关视频

$CROWBRAIN IS READY FOR ITS SECOND PUBLIC TEST The first experiment proved two things: the algorithm can find opportunities quickly, but without strict risk management, profits can disappear just as fast. I fixed the main problems by adding automatic profit-taking, a dynamic stop-loss, position size limits, a cooldown after consecutive losses and protection against re-entering after a sharp price increase. Now I am creating a new public wallet, funding it with $50 and launching CROWBRAIN in autonomous trading mode again. Starting balance: $50 Wallet address: [AD4vTDFY9RfFCdTmLPqzmoo61R6kwqskLk3BHSgXmrbf] Anyone will be able to verify the balance, open positions and transaction history. I will not hide losing trades or show only profitable moments - the entire experiment will be public. No additional deposits during the test. Just $50, the updated algorithm and the market. Let’s see what CROWBRAIN has learned from its first mistake and what it can turn this wallet into.

$CROWBRAIN IS READY FOR ITS SECOND PUBLIC TEST The first experiment proved two things: the algorithm can find opportunities quickly, but without strict risk management, profits can disappear just as fast. I fixed the main problems by adding automatic profit-taking, a dynamic stop-loss, position size limits, a cooldown after consecutive losses and protection against re-entering after a sharp price increase. Now I am creating a new public wallet, funding it with $50 and launching CROWBRAIN in autonomous trading mode again. Starting balance: $50 Wallet address: [AD4vTDFY9RfFCdTmLPqzmoo61R6kwqskLk3BHSgXmrbf] Anyone will be able to verify the balance, open positions and transaction history. I will not hide losing trades or show only profitable moments - the entire experiment will be public. No additional deposits during the test. Just $50, the updated algorithm and the market. Let’s see what CROWBRAIN has learned from its first mistake and what it can turn this wallet into.

sopersone

17,542 次观看 • 6 天前

I GAVE A CROW BRAIN $50 AND LET IT TRADE BY ITSELF CROWBRAIN BOT is officially live. It is an autonomous trading bot inspired by the intelligence of one of the smartest birds on the planet. It scans new and trending tokens, analyzes price, volume and liquidity, and then makes its own decision: BUY → open a position SELL → take profit or exit WAIT → skip the trade The first experiment turned $50 into $420 in just five hours, but the algorithm later lost the profit because its risk controls were not strong enough. I fixed the main problems. The bot now takes partial profits, uses a dynamic stop-loss, limits position sizes, pauses after consecutive losses and avoids re-entering after a sharp price increase. The second public experiment starts today. Starting balance: $50 Public wallet: [AD4vTDFY9RfFCdTmLPqzmoo61R6kwqskLk3BHSgXmrbf] No additional deposits and no hidden trades. Every entry, exit, profit and loss will be verifiable directly on-chain. $50. One updated algorithm. Fully public trading. Let’s see whether a digital crow brain can survive the real market.

I GAVE A CROW BRAIN $50 AND LET IT TRADE BY ITSELF CROWBRAIN BOT is officially live. It is an autonomous trading bot inspired by the intelligence of one of the smartest birds on the planet. It scans new and trending tokens, analyzes price, volume and liquidity, and then makes its own decision: BUY → open a position SELL → take profit or exit WAIT → skip the trade The first experiment turned $50 into $420 in just five hours, but the algorithm later lost the profit because its risk controls were not strong enough. I fixed the main problems. The bot now takes partial profits, uses a dynamic stop-loss, limits position sizes, pauses after consecutive losses and avoids re-entering after a sharp price increase. The second public experiment starts today. Starting balance: $50 Public wallet: [AD4vTDFY9RfFCdTmLPqzmoo61R6kwqskLk3BHSgXmrbf] No additional deposits and no hidden trades. Every entry, exit, profit and loss will be verifiable directly on-chain. $50. One updated algorithm. Fully public trading. Let’s see whether a digital crow brain can survive the real market.

sopersone

11,753 次观看 • 6 天前

what the ffffffff i spent 12 hours building a digital crow brain that scans Solana and Robinhood Chain and gives me BUY / SELL / WAIT signals then i started trading them $100 → $1,362 CROWBRAIN. the idea is simple: crows are among the smartest birds on earth. they use tools, remember faces, solve complex problems and have around 1.5 billion neurons inside a tiny brain i wanted to build a market system inspired by that intelligence every few seconds it: → finds trending and newly created tokens across both chains → checks price movement, volume and liquidity → removes pools with less than $25K in reserves → gives me BUY / SELL / WAIT with the reason behind every decision → records every check inside a public execution log → displays the process through an interactive crow brain there is no private group and no hidden signal feed. the system finds the opportunities, but i still choose which trades to execute 12 hours of building $100 → $1,362 and i decided to share the whole thing for free: repo: next: connect a real balance and let CROWBRAIN trade automatically until then, i’ll keep trading its signals manually and share the results here should i post every signal it catches live?

what the ffffffff i spent 12 hours building a digital crow brain that scans Solana and Robinhood Chain and gives me BUY / SELL / WAIT signals then i started trading them $100 → $1,362 CROWBRAIN. the idea is simple: crows are among the smartest birds on earth. they use tools, remember faces, solve complex problems and have around 1.5 billion neurons inside a tiny brain i wanted to build a market system inspired by that intelligence every few seconds it: → finds trending and newly created tokens across both chains → checks price movement, volume and liquidity → removes pools with less than $25K in reserves → gives me BUY / SELL / WAIT with the reason behind every decision → records every check inside a public execution log → displays the process through an interactive crow brain there is no private group and no hidden signal feed. the system finds the opportunities, but i still choose which trades to execute 12 hours of building $100 → $1,362 and i decided to share the whole thing for free: repo: next: connect a real balance and let CROWBRAIN trade automatically until then, i’ll keep trading its signals manually and share the results here should i post every signal it catches live?

sopersone

46,665 次观看 • 7 天前

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

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 次观看 • 6 个月前

$DXYZ Trade Recap I want to share my full trading journey on $DXYZ, from the first entry to the final exit. I first posted this stock on April 30th and took my initial position at $31.58. Within seven days, the stock exploded to $60+, and my position doubled quickly. My usual rule is simple: When my investment doubles, I sell all or most of the position. This time, I only sold half. On May 13th, I bought back the shares I sold, around $51, and shared that update as well. Price pushed back to the $70 area, but after forming a clear double top and failing to break $71, I sold the shares I added on May 13th at price $59. Soon after, the stock dropped sharply to the $50 area. I bought again around $50, with a stop slightly below $47, and that stop was hit. Later, when price pulled back to the $38 range, I entered again and waited for price action into the SpaceX IPO. I eventually exited all remaining shares in premarket before the IPO, around $36. That completes my entire trade sequence on this name. I made a profit overall, but not as much as I originally expected. The key reason is: Price never broke above the previous $70 resistance. Looking back, the part I didn’t execute well was letting my bias take over. I believed the stock could go much higher, and because of that, I didn’t follow my usual discipline: I didn’t sell the entire position when I doubled my investment the first time. I didn’t sell everything when the stock failed to break the previous high. Both moments were clear opportunities to lock in the full gain. Still, it was a solid learning experience and a profitable trade overall. Thanks for reading, and I hope this recap helps others stay disciplined in their own trading.

$DXYZ Trade Recap I want to share my full trading journey on $DXYZ, from the first entry to the final exit. I first posted this stock on April 30th and took my initial position at $31.58. Within seven days, the stock exploded to $60+, and my position doubled quickly. My usual rule is simple: When my investment doubles, I sell all or most of the position. This time, I only sold half. On May 13th, I bought back the shares I sold, around $51, and shared that update as well. Price pushed back to the $70 area, but after forming a clear double top and failing to break $71, I sold the shares I added on May 13th at price $59. Soon after, the stock dropped sharply to the $50 area. I bought again around $50, with a stop slightly below $47, and that stop was hit. Later, when price pulled back to the $38 range, I entered again and waited for price action into the SpaceX IPO. I eventually exited all remaining shares in premarket before the IPO, around $36. That completes my entire trade sequence on this name. I made a profit overall, but not as much as I originally expected. The key reason is: Price never broke above the previous $70 resistance. Looking back, the part I didn’t execute well was letting my bias take over. I believed the stock could go much higher, and because of that, I didn’t follow my usual discipline: I didn’t sell the entire position when I doubled my investment the first time. I didn’t sell everything when the stock failed to break the previous high. Both moments were clear opportunities to lock in the full gain. Still, it was a solid learning experience and a profitable trade overall. Thanks for reading, and I hope this recap helps others stay disciplined in their own trading.

SEPTINVESTING

19,304 次观看 • 3 个月前

The GPT-6 Astra brain, a neural copy of 169 winning Robinhood memecoin traders, is about to touch real money for the first time. Six gates stand between what it wants and my deposit, and I'm not one of them. > PROVENANCE. Whose fill is it really. Gifted or dust dies here, 1 fill in 11 > COHORT. Who went in, at what cost, with what record. Averaging down is not entering > TOKEN. Seeded, or can't even sell. A sell probe runs before a dollar moves > MARKET. How far above the wallets' own cost, and whether the candle is already tired > RISK. Never above 4% of the deposit, five positions max, the day stops at minus 6% > EXECUTE. Slippage cap, two tries. No fill, walk away The three middle gates have to say yes at the same second or nothing happens. The right token at the wrong price parks and knocks again in 90 seconds. A token that turns out seeded after entry closes itself, whatever the PnL. Half of every profit goes back into the deposit that sizes the next trade. Half buys $FOMOBRAIN and burns it. Every result goes into the score of the wallet that caused it, so the judge learns what its own picks did. Every no gets written down with its reason. The gates are built, and the wallet is next. God bless us.

The GPT-6 Astra brain, a neural copy of 169 winning Robinhood memecoin traders, is about to touch real money for the first time. Six gates stand between what it wants and my deposit, and I'm not one of them. > PROVENANCE. Whose fill is it really. Gifted or dust dies here, 1 fill in 11 > COHORT. Who went in, at what cost, with what record. Averaging down is not entering > TOKEN. Seeded, or can't even sell. A sell probe runs before a dollar moves > MARKET. How far above the wallets' own cost, and whether the candle is already tired > RISK. Never above 4% of the deposit, five positions max, the day stops at minus 6% > EXECUTE. Slippage cap, two tries. No fill, walk away The three middle gates have to say yes at the same second or nothing happens. The right token at the wrong price parks and knocks again in 90 seconds. A token that turns out seeded after entry closes itself, whatever the PnL. Half of every profit goes back into the deposit that sizes the next trade. Half buys $FOMOBRAIN and burns it. Every result goes into the score of the wallet that caused it, so the judge learns what its own picks did. Every no gets written down with its reason. The gates are built, and the wallet is next. God bless us.

cvxv666

11,917 次观看 • 11 天前

I gave my Grok Bot two options: multiply or die. It came back asking for $250 to hire a team of six. The same headcount on a real desk is three analysts and a risk officer. That is $400,000 a year before anyone opens a position. Mine cost $250 once and about $300 a month to keep breathing. Mine took $250 to $611 on day one, out of a wallet anyone can open and read. Most of the build is not about making it trade. It is about stopping it. Every agent's job description ends with a list of what it may never do without asking me first. One of the six is not allowed to trade at all. Its entire job is killing what the other five found, and its no beats every score on the desk. The one that makes the final call never touches the market either. It only signs. Day three the account was back to $180 and it opened nothing for nine hours while every account I follow posted green screenshots. That was the day the build started working. You could have this running by Friday. Most people reading this will not, and in a few months they will be paying somebody who did. The whole build is in the post below ↓ Save it while it still sounds strange. Give it a quarter and this is just how a retail account works.

I gave my Grok Bot two options: multiply or die. It came back asking for $250 to hire a team of six. The same headcount on a real desk is three analysts and a risk officer. That is $400,000 a year before anyone opens a position. Mine cost $250 once and about $300 a month to keep breathing. Mine took $250 to $611 on day one, out of a wallet anyone can open and read. Most of the build is not about making it trade. It is about stopping it. Every agent's job description ends with a list of what it may never do without asking me first. One of the six is not allowed to trade at all. Its entire job is killing what the other five found, and its no beats every score on the desk. The one that makes the final call never touches the market either. It only signs. Day three the account was back to $180 and it opened nothing for nine hours while every account I follow posted green screenshots. That was the day the build started working. You could have this running by Friday. Most people reading this will not, and in a few months they will be paying somebody who did. The whole build is in the post below ↓ Save it while it still sounds strange. Give it a quarter and this is just how a retail account works.

NO1ennn

27,007 次观看 • 24 天前

#WATCH | Delhi CM Rekha Gupta says, "Cloud seeding is a necessity for Delhi and is the first experiment of its kind. We want to try it in Delhi to see if it can help us control this very serious environmental problem. So the blessings of the people of Delhi are with the government, and we feel that this will be a successful experiment and in future, we will be able to overcome these environmental problems."

#WATCH | Delhi CM Rekha Gupta says, "Cloud seeding is a necessity for Delhi and is the first experiment of its kind. We want to try it in Delhi to see if it can help us control this very serious environmental problem. So the blessings of the people of Delhi are with the government, and we feel that this will be a successful experiment and in future, we will be able to overcome these environmental problems."

ANI

27,261 次观看 • 11 个月前

Trading consolidations is a guaranteed way to burn money. The breakout retest is the ONLY strategy that works when markets move sideways—and it's ridiculously profitable when done right. First, here's why consolidation trading doesn’t work: • Too much volatility. • Unpredictable price action. • Market manipulation in both directions. That’s why we trade the breakout retest: Here’s the 4-steps to it: Step 1: Draw the box When price consolidates, I draw a box from the lowest point to the highest point. Then I wait. Step 2: Wait for the breakout I'm waiting for one thing: a big momentum candlestick that breaks out of the box. Ideally, this candle aligns with the higher timeframe trend. Step 3: Identify the imbalance That momentum candle creates a gap—the space between the low of the candle before the breakout and the high of the candle after. Step 4: Enter on the retest Price pulls back to retest that imbalance around 50%—fair value. When it does, I enter. Stop loss above the imbalance. Target 2-3R. Why this works: The market always moves from imbalance to balance to imbalance. That pullback after the breakout? It's the market seeking fair value before continuing. The bottom line: Stop trading consolidation. Start positioning on retests. If you can't wait for the retest, you're not ready to be profitable. — This is just a breakdown of one of the trading strategies we covered in our 2-hour long cryptocurrency trading course. I also discussed the trend pullback strategy, how to trade liquidity sweep reversals, and why understanding liquidity is the only way to avoid becoming exit liquidity. Just comment "COURSE" and I'll DM it to you immediately so you can watch it.

Trading consolidations is a guaranteed way to burn money. The breakout retest is the ONLY strategy that works when markets move sideways—and it's ridiculously profitable when done right. First, here's why consolidation trading doesn’t work: • Too much volatility. • Unpredictable price action. • Market manipulation in both directions. That’s why we trade the breakout retest: Here’s the 4-steps to it: Step 1: Draw the box When price consolidates, I draw a box from the lowest point to the highest point. Then I wait. Step 2: Wait for the breakout I'm waiting for one thing: a big momentum candlestick that breaks out of the box. Ideally, this candle aligns with the higher timeframe trend. Step 3: Identify the imbalance That momentum candle creates a gap—the space between the low of the candle before the breakout and the high of the candle after. Step 4: Enter on the retest Price pulls back to retest that imbalance around 50%—fair value. When it does, I enter. Stop loss above the imbalance. Target 2-3R. Why this works: The market always moves from imbalance to balance to imbalance. That pullback after the breakout? It's the market seeking fair value before continuing. The bottom line: Stop trading consolidation. Start positioning on retests. If you can't wait for the retest, you're not ready to be profitable. — This is just a breakdown of one of the trading strategies we covered in our 2-hour long cryptocurrency trading course. I also discussed the trend pullback strategy, how to trade liquidity sweep reversals, and why understanding liquidity is the only way to avoid becoming exit liquidity. Just comment "COURSE" and I'll DM it to you immediately so you can watch it.

The Trading Geek (Brad Goh)

11,008 次观看 • 8 个月前

Something interesting is going to be released soon... ✨ Kitt The Inner Circle Trader "If I had to trade only one model for the rest of my life, considering everything I've publicly disclosed, my choice would be either the second stage of re-distribution in an MMSM or the second stage of re-accumulation in an MMBM. With either of these, I believe I could consistently generate substantial profits without the need to explore alternative strategies. These models rely on specific components of both the buy and sell sides of the market curve, which are directly interconnected. This isn't a matter of identifying support and resistance levels; it's about understanding the logic of order flow. In the case of the market maker sell model, I focus on identifying a pool of liquidity beneath the initial consolidation. When I spot this sellside opportunity, I patiently await a reversal. This reversal should lead to a drop of at least 50% from the smart money's reversal point down to the sellside liquidity. If it achieves this, and then begins to rally once more, I'll look to correlate it with the other side of the curve, where the market previously rallied before reversing. This will provide me with an array that initially signaled a bullish trend but now acts as a reversal indicator. This marks the second stage of distribution or redistribution, and it usually happens swiftly, pushing prices towards the sellside. In essence, I'm waiting for a unicorn setup, where all the pieces align perfectly, and I have everything in my favor. I'll risk 5% on such a trade. This approach involves re-accumulation, where the sellside drops down to 50%, and then I match it with another array to capture the reversal. Now, picture a market maker model involving a consolidation phase where relative equal lows are formed, followed by an upward rally, possibly forming a consolidation that resembles a bull flag pattern. Subsequently, it rallies out of that consolidation. Sometimes, it may create a second stage of re-accumulation as it trades towards a premium array level—a level I consider a liquidity draw. If I'm feeling bullish, I'd aim for that level. I don't necessarily need to be there at the exact moment; I might spot the opportunity later and act accordingly. If it's reacting off of a level, that should offer sellside. So, you know where sellside delivery. The market should drop down. So, I'm anticipating price reacting and reversing at the smart money reversal once it starts to break down. If it goes back up a little bit, that's the smart money reversal. Low risk sell is the next stage and then they'll drop. When we reach the low-risk sell, it's important that the drop reaches at least 50% of the total range from the smart money reversal to the sellside I'm targeting. As long as it accomplishes this, I have confidence that the subsequent rally will reach a premium array on the left side of the curve before the market makes its high and reverses. Why would it do that? Because it's part of a larger continuation. So when and how would I determine when it's going to fail ,that first leg of re-distribution on the sell side, if it doesn't pierce 50% of that range from the smart money reversal down to the sell side liquidity. If it doesn't do that, then it's not going to go down there. It's going to be a continuation of reverse and go the other way." #ict #ICT

Something interesting is going to be released soon... ✨ Kitt The Inner Circle Trader "If I had to trade only one model for the rest of my life, considering everything I've publicly disclosed, my choice would be either the second stage of re-distribution in an MMSM or the second stage of re-accumulation in an MMBM. With either of these, I believe I could consistently generate substantial profits without the need to explore alternative strategies. These models rely on specific components of both the buy and sell sides of the market curve, which are directly interconnected. This isn't a matter of identifying support and resistance levels; it's about understanding the logic of order flow. In the case of the market maker sell model, I focus on identifying a pool of liquidity beneath the initial consolidation. When I spot this sellside opportunity, I patiently await a reversal. This reversal should lead to a drop of at least 50% from the smart money's reversal point down to the sellside liquidity. If it achieves this, and then begins to rally once more, I'll look to correlate it with the other side of the curve, where the market previously rallied before reversing. This will provide me with an array that initially signaled a bullish trend but now acts as a reversal indicator. This marks the second stage of distribution or redistribution, and it usually happens swiftly, pushing prices towards the sellside. In essence, I'm waiting for a unicorn setup, where all the pieces align perfectly, and I have everything in my favor. I'll risk 5% on such a trade. This approach involves re-accumulation, where the sellside drops down to 50%, and then I match it with another array to capture the reversal. Now, picture a market maker model involving a consolidation phase where relative equal lows are formed, followed by an upward rally, possibly forming a consolidation that resembles a bull flag pattern. Subsequently, it rallies out of that consolidation. Sometimes, it may create a second stage of re-accumulation as it trades towards a premium array level—a level I consider a liquidity draw. If I'm feeling bullish, I'd aim for that level. I don't necessarily need to be there at the exact moment; I might spot the opportunity later and act accordingly. If it's reacting off of a level, that should offer sellside. So, you know where sellside delivery. The market should drop down. So, I'm anticipating price reacting and reversing at the smart money reversal once it starts to break down. If it goes back up a little bit, that's the smart money reversal. Low risk sell is the next stage and then they'll drop. When we reach the low-risk sell, it's important that the drop reaches at least 50% of the total range from the smart money reversal to the sellside I'm targeting. As long as it accomplishes this, I have confidence that the subsequent rally will reach a premium array on the left side of the curve before the market makes its high and reverses. Why would it do that? Because it's part of a larger continuation. So when and how would I determine when it's going to fail ,that first leg of re-distribution on the sell side, if it doesn't pierce 50% of that range from the smart money reversal down to the sell side liquidity. If it doesn't do that, then it's not going to go down there. It's going to be a continuation of reverse and go the other way." #ict #ICT

LumiTraders

388,546 次观看 • 3 年前

This guy built an asynchronous complete-set bot and made +$111,945 on Polymarket with a 50% win rate I analyzed its trades and found that its main strategy is based on gradually accumulating both sides of the same market In 88.76% of markets, it bought both Up and Down It looks something like this: > First, the bot accumulates one side > After the underlying asset moves, it starts buying the opposite outcome > Then it switches between both sides several times as the market reprices > This way, it tries to build a position where Up + Down < $1 The average cost of these complete sets is 98.69c, which gives an edge of about 1.31c But this is not pure arbitrage. Part of its inventory remains directional, with the side determined by its model’s signal Its Polymarket nickname: norm1e69 The main edge of this trading bot comes from switching between both outcomes to build complete sets below $1, while keeping the unpaired inventory as a directional residual

This guy built an asynchronous complete-set bot and made +$111,945 on Polymarket with a 50% win rate I analyzed its trades and found that its main strategy is based on gradually accumulating both sides of the same market In 88.76% of markets, it bought both Up and Down It looks something like this: > First, the bot accumulates one side > After the underlying asset moves, it starts buying the opposite outcome > Then it switches between both sides several times as the market reprices > This way, it tries to build a position where Up + Down < $1 The average cost of these complete sets is 98.69c, which gives an edge of about 1.31c But this is not pure arbitrage. Part of its inventory remains directional, with the side determined by its model’s signal Its Polymarket nickname: norm1e69 The main edge of this trading bot comes from switching between both outcomes to build complete sets below $1, while keeping the unpaired inventory as a directional residual

VALIX

16,979 次观看 • 7 天前

I just closed a quick $73.8K trade—but not before nearly botching the whole thing. I set my take profit at 212.70 instead of 212.776. When price started dropping fast, I had to manually close all my positions with speedy fingers before hitting the wrong TP level. lol. Let me break down the trade setup: Price was bearish, then we got a market shift signalling a potential bullish move on the 15-minute structure. After price mitigated the supply zone and created a failed reaction, I knew we had a flip + sweep zone forming. Price pushed hard to the upside, but gravity eventually pulled it back down. I saw bearish momentum forming and knew price was gravitating toward the extreme demand zone below. Instead of waiting for a buy setup (which would happen during New York session—not my time), I decided to trade the pullback itself. Here’s how I entered: I waited for a huge bearish candle, then watched for price to pull back slightly. That pullback created my supply zone. When price mitigated that zone and created a lower high—boom, that's where I entered. Overall thoughts: Honestly, I rate this trade 5/10. Not perfect. I rushed the entry and couldn't use my normal platform. Some positions even filled at non-ideal prices. But here's what I did right: proper stop loss placement and taking profit at the exact point where demand would step in. — This is just one setup from my complete trading framework. I also cover how to spot market shifts before they happen, the exact 3 timeframes I use to confirm every trade, and how to identify high-probability supply and demand zones for entries. Just comment "FRAMEWORK" and I'll send you the full breakdown in your DMs.

I just closed a quick $73.8K trade—but not before nearly botching the whole thing. I set my take profit at 212.70 instead of 212.776. When price started dropping fast, I had to manually close all my positions with speedy fingers before hitting the wrong TP level. lol. Let me break down the trade setup: Price was bearish, then we got a market shift signalling a potential bullish move on the 15-minute structure. After price mitigated the supply zone and created a failed reaction, I knew we had a flip + sweep zone forming. Price pushed hard to the upside, but gravity eventually pulled it back down. I saw bearish momentum forming and knew price was gravitating toward the extreme demand zone below. Instead of waiting for a buy setup (which would happen during New York session—not my time), I decided to trade the pullback itself. Here’s how I entered: I waited for a huge bearish candle, then watched for price to pull back slightly. That pullback created my supply zone. When price mitigated that zone and created a lower high—boom, that's where I entered. Overall thoughts: Honestly, I rate this trade 5/10. Not perfect. I rushed the entry and couldn't use my normal platform. Some positions even filled at non-ideal prices. But here's what I did right: proper stop loss placement and taking profit at the exact point where demand would step in. — This is just one setup from my complete trading framework. I also cover how to spot market shifts before they happen, the exact 3 timeframes I use to confirm every trade, and how to identify high-probability supply and demand zones for entries. Just comment "FRAMEWORK" and I'll send you the full breakdown in your DMs.

The Trading Geek (Brad Goh)

12,264 次观看 • 8 个月前

TikTok just got caught running a secret experiment on 15 million Americans to find out how much money their dangerous version could make them. In 2021 the company rewrote part of its recommendation algorithm so users would stop getting buried under harmful content over and over. Then it held back 10% of its American users and left them on the OLD version. At the time that was roughly 15 million people. None of them were told. They opened the same app, saw the same logo, and scrolled a feed the company had already replaced for everyone else. Internally the practice has a clean name. It is called a backtest, and it is the same A/B test any company runs when it wants to prove a change actually worked. Companies normally run those on button colors and checkout flows. TikTok ran one on what happens to people when the app stops protecting them. Why would a business do that? Because a safer feed is a less sticky feed, and stickiness is the product. One of the 15 million was a 16 year old named Chase Nasca. He had no history of mental health issues. He committed sicide in February 2022. In March 2023, a Bloomberg Businessweek reporter emailed the company asking about Chase for a story on teenagers and the algorithm. Only then did TikTok's algorithm and safety teams go back and reconstruct his account. They found he had been assigned to the control group. The same report notes that most of what he actually searched for on the app was sports and comedy - but he was regularly shown sicide and other harmful content. Their findings became a 14 page internal report on youth safety and filter bubbles. Its key contacts list shows it went to 10 teams inside the company, including communications, legal response, policy, security and search. So the lawyers knew about it. The communications team knew. Policy, security and search all got a copy. Then came the recommendations, and this is where it gets genuinely ugly... The report proposed two fixes: The first was to shrink the control group from 10% of American users to under 1%. The second was to cut how long the same users sit inside it, from as long as a full year down to seven days. Nobody proposed stopping. And the report ran the numbers on its own suggestion. Even at 1%, it said, at least 1.8 million users would still be excluded from the safety change, and it warned those people would be left "at risk for falling into bubbles." Someone typed that sentence, sent it to 10 teams, and the practice continued. A former TikTok trust and safety team leader who worked there while the experiment was live said he had never heard of it. After seeing the details he said the control group was far too big, and that the test should have excluded minors and suicide content entirely. The staff paid to protect users did not know the experiment on users existed. TikTok's answer this week is that the 2022 test was routine, and that its purpose was to check whether safety changes were working as intended. The internal report describes its own recommendations as a way to prevent future incidents. Chase's parents sued for wrongful death. A judge dismissed the case last year after TikTok argued that Section 230 protects it from liability for what its algorithm recommends. The appeal is still pending. So the company's legal position is that it is not responsible for the videos its algorithm served a teenager, while its OWN document confirms it chose which version of that algorithm he received. Every large platform runs tests like this one. But not one of them publishes how many users are sitting in the old version at any given moment. TikTok's number was never supposed to become public.

Ricardo

31,047 次观看 • 1 个月前

This is f*cking GOLD - I made CatBrain trade $50 → $1,000 in 7 days. This cat nearly gave me a HEART ATTACK. I wanted to see what would happen if a trading model used the wiring of a cat's cortex. Give it a chart, let signals move through the network, and turn the output into a decision. Sounds simple. Watching it hold through a drawdown? ABSOLUTELY NOT. → 65 cortical regions linked by 1,139 documented connections → Price charts feed into the model’s visual regions → Signals travel through the network to produce BUY, SELL or HOLD → Trading Pons tokens, with profits and losses feeding back into training The question that got me hooked: does the structure of the network actually change how it learns to trade? Apparently, nine lives weren't enough. He wanted FINANCIAL FREEDOM.

This is f*cking GOLD - I made CatBrain trade $50 → $1,000 in 7 days. This cat nearly gave me a HEART ATTACK. I wanted to see what would happen if a trading model used the wiring of a cat's cortex. Give it a chart, let signals move through the network, and turn the output into a decision. Sounds simple. Watching it hold through a drawdown? ABSOLUTELY NOT. → 65 cortical regions linked by 1,139 documented connections → Price charts feed into the model’s visual regions → Signals travel through the network to produce BUY, SELL or HOLD → Trading Pons tokens, with profits and losses feeding back into training The question that got me hooked: does the structure of the network actually change how it learns to trade? Apparently, nine lives weren't enough. He wanted FINANCIAL FREEDOM.

BuBBliK

73,471 次观看 • 4 天前

Astarter s agent beta is open. An autonomous trading agent for BNB Smart Chain. Your funds stay in an account only you own. You grant the agent a bounded, expiring permission, you can revoke it at any time, and proceeds can only ever return to you. AI proposes. Code verifies. You set the limits. The model reads the market and builds a case. Deterministic code checks that case against the limits you signed, and decides whether it may execute at all. The model cannot widen a limit, because no code path widens one. Every decision is recorded with its reasons, including the decision not to trade. In a quiet market that is the correct output, and you will see exactly why it was reached. And you can walk away whenever you want, taking your funds with you, without asking us for anything. Try it, and tell us what to fix. We are improving it continuously. Trading involves risk. No return is promised.

Astarter s agent beta is open. An autonomous trading agent for BNB Smart Chain. Your funds stay in an account only you own. You grant the agent a bounded, expiring permission, you can revoke it at any time, and proceeds can only ever return to you. AI proposes. Code verifies. You set the limits. The model reads the market and builds a case. Deterministic code checks that case against the limits you signed, and decides whether it may execute at all. The model cannot widen a limit, because no code path widens one. Every decision is recorded with its reasons, including the decision not to trade. In a quiet market that is the correct output, and you will see exactly why it was reached. And you can walk away whenever you want, taking your funds with you, without asking us for anything. Try it, and tell us what to fix. We are improving it continuously. Trading involves risk. No return is promised.

Astarter

20,500 次观看 • 16 天前

Let’s see what happened to all these materials after I dipped them into the magical glass-forming liquid. As you can see, the entire surface of the liquid has completely solidified. But I was still able to push the side of the container in, which means that underneath, it is still liquid. So this is not one solid block of glass. Let’s look at them one by one. First, I’m taking out the pencil. Well, no glass layer formed on this one. What you can see on it is simply the dried upper crust of the liquid. To be honest, I expected this, because this isn’t really bare wood—it’s more like wood with a plastic coating. Next is the geopolymer. The result is exactly the same. This one surprised me, because this was actually the material I was most confident would develop a deposit. But apparently not. Next comes the granite. And by now, it’s pretty easy to see that the result is the same again: nothing deposited on it. The next object is the spoon. I had absolutely no expectations for this one, and absolutely nothing is exactly what happened. There’s only the dried upper crust stuck to it, and the rest will probably just run off. But what about the egg?! A few days ago, it looked as though the egg was going to be the champion, with a massive layer of glass apparently forming on it. Well, I have some bad news: not at all. And why? I have absolutely no idea. And finally, just quickly at the end… The piece of limestone suffered exactly the same fate, and so did the peach. So, in reality, the experiment was a spectacular failure. None of these objects developed a glass layer. And in my opinion, this is exactly why it’s not worth publishing the recipe yet. Because, as you can clearly see, this time it simply didn’t work—even though, in theory, I did exactly the same thing as before. So, I wish myself happy experimenting. Once again, I’ve been given a new puzzle that I have to solve. … Meanwhile, in the container right next to it, this happened. And the recipe is exactly the same! Wow! 🤯

Let’s see what happened to all these materials after I dipped them into the magical glass-forming liquid. As you can see, the entire surface of the liquid has completely solidified. But I was still able to push the side of the container in, which means that underneath, it is still liquid. So this is not one solid block of glass. Let’s look at them one by one. First, I’m taking out the pencil. Well, no glass layer formed on this one. What you can see on it is simply the dried upper crust of the liquid. To be honest, I expected this, because this isn’t really bare wood—it’s more like wood with a plastic coating. Next is the geopolymer. The result is exactly the same. This one surprised me, because this was actually the material I was most confident would develop a deposit. But apparently not. Next comes the granite. And by now, it’s pretty easy to see that the result is the same again: nothing deposited on it. The next object is the spoon. I had absolutely no expectations for this one, and absolutely nothing is exactly what happened. There’s only the dried upper crust stuck to it, and the rest will probably just run off. But what about the egg?! A few days ago, it looked as though the egg was going to be the champion, with a massive layer of glass apparently forming on it. Well, I have some bad news: not at all. And why? I have absolutely no idea. And finally, just quickly at the end… The piece of limestone suffered exactly the same fate, and so did the peach. So, in reality, the experiment was a spectacular failure. None of these objects developed a glass layer. And in my opinion, this is exactly why it’s not worth publishing the recipe yet. Because, as you can clearly see, this time it simply didn’t work—even though, in theory, I did exactly the same thing as before. So, I wish myself happy experimenting. Once again, I’ve been given a new puzzle that I have to solve. … Meanwhile, in the container right next to it, this happened. And the recipe is exactly the same! Wow! 🤯

Marcell Fóti 🪨

21,749 次观看 • 22 天前

I just found one of the biggest platform bug on Polymarket that cost me my $8.5k portfolio today. Please watch this video. I opened the exact same BTC 5m market on two different devices right next to each other. My computer monitor shows 2 minutes and 50 seconds remaining. My MacBook shows 4 minutes and 02 seconds remaining. There is more than a full minute of time difference on the exact same live market. This video is undeniable proof of exactly why I lost my money today. I was trading on my computer earlier and I waited until the 5m time frame end. When Polymarket UI showed me on my computer the timeframe was completely over and the price was safely above the target, I placed a market up order to provide liquidity. I was 100 percent sure it was a zero risk move because your platform timer showed me the market was already finished and BTC price is up from the beat price. But because of this bug my computer timer was closing 1 minute earlier than the real market time. So after I placed my order believing the market was settled as Up, the actual market was still open. It kept counting the Bitcoin price movements for the next full minute after I placed my trade. During that hidden extra minute the price of BTC dropped and the market finally settled Down, instantly wiping out my entire portfolio. When people told me it might be a UI delay I was shocked, but now I have it on video. The Polymarket timer is completely broken and out of sync across devices. My Polymarket wallet address is: 0xf0AD2eeb8F898619460a38c015a7897a4E797651 Trade URL 1: Trade URL 2: On those above two trade i lost total $8500 The first video I just recorded now when i noticed this bugs and the second video i made when my trade lost and i didn’t have any reason how its happened. I am begging Shayne Coplan 🦅 and the Polymarket support team to review this video. I did not make a trading mistake. I trusted a broken platform timer that showed completely wrong data and forced me into an active market I thought was closed. Please fix this massive bug protect your user and refund my loses.

I just found one of the biggest platform bug on Polymarket that cost me my $8.5k portfolio today. Please watch this video. I opened the exact same BTC 5m market on two different devices right next to each other. My computer monitor shows 2 minutes and 50 seconds remaining. My MacBook shows 4 minutes and 02 seconds remaining. There is more than a full minute of time difference on the exact same live market. This video is undeniable proof of exactly why I lost my money today. I was trading on my computer earlier and I waited until the 5m time frame end. When Polymarket UI showed me on my computer the timeframe was completely over and the price was safely above the target, I placed a market up order to provide liquidity. I was 100 percent sure it was a zero risk move because your platform timer showed me the market was already finished and BTC price is up from the beat price. But because of this bug my computer timer was closing 1 minute earlier than the real market time. So after I placed my order believing the market was settled as Up, the actual market was still open. It kept counting the Bitcoin price movements for the next full minute after I placed my trade. During that hidden extra minute the price of BTC dropped and the market finally settled Down, instantly wiping out my entire portfolio. When people told me it might be a UI delay I was shocked, but now I have it on video. The Polymarket timer is completely broken and out of sync across devices. My Polymarket wallet address is: 0xf0AD2eeb8F898619460a38c015a7897a4E797651 Trade URL 1: Trade URL 2: On those above two trade i lost total $8500 The first video I just recorded now when i noticed this bugs and the second video i made when my trade lost and i didn’t have any reason how its happened. I am begging Shayne Coplan 🦅 and the Polymarket support team to review this video. I did not make a trading mistake. I trusted a broken platform timer that showed completely wrong data and forced me into an active market I thought was closed. Please fix this massive bug protect your user and refund my loses.

Sheikh Silicon

88,738 次观看 • 5 个月前

This guy built an HFT algorithm on Polymarket with an average trade size of $40 Result: +$223,542 His bot trades short-term BTC/ETH Up/Down markets using a hybrid of passive market making, inventory rebalancing, and opportunistic complete-set formation: 1. It accumulates outcomes below its fair value It places BUY orders in advance and waits for them to get filled. The average price per share acquired is 46.6c 2. When the market moves, it turns part of the inventory into cheap complete sets If its Up orders get filled first and then the underlying reverses, making Down cheaper, it starts accumulating the opposite side In two-sided 5-minute markets, the median combined VWAP of both sides is around 94.8c 3. It keeps part of the inventory directional It doesn’t try to fully balance Up and Down. If it can buy a cheap hedge, part of the position turns into complete sets. If not, the original inventory remains directional His Polymarket nickname: PBot-6 You can build your own trading bot here: (Trial period available after registration) This guy’s stats: > Trades / active hour: 46.11 > Average trade: $39.67 > Win Rate: 50% The main edge of his HFT algorithm comes from consistently getting fills below its fair value and building arbitrage positions

This guy built an HFT algorithm on Polymarket with an average trade size of $40 Result: +$223,542 His bot trades short-term BTC/ETH Up/Down markets using a hybrid of passive market making, inventory rebalancing, and opportunistic complete-set formation: 1. It accumulates outcomes below its fair value It places BUY orders in advance and waits for them to get filled. The average price per share acquired is 46.6c 2. When the market moves, it turns part of the inventory into cheap complete sets If its Up orders get filled first and then the underlying reverses, making Down cheaper, it starts accumulating the opposite side In two-sided 5-minute markets, the median combined VWAP of both sides is around 94.8c 3. It keeps part of the inventory directional It doesn’t try to fully balance Up and Down. If it can buy a cheap hedge, part of the position turns into complete sets. If not, the original inventory remains directional His Polymarket nickname: PBot-6 You can build your own trading bot here: (Trial period available after registration) This guy’s stats: > Trades / active hour: 46.11 > Average trade: $39.67 > Win Rate: 50% The main edge of his HFT algorithm comes from consistently getting fills below its fair value and building arbitrage positions

VALIX

98,473 次观看 • 27 天前

The Cybertruck is finally here, I am even considering buying one after reading about it, and after being driven around in Teslas in Europe and America, they are pretty cool. The stainless steel body is uniquely weird, one wonders whether finger prints would show, what will happen to the scratches on the stainless body? The Cybertruck's stainless steel body is designed to be durable and resist corrosion, so it is certainly good for Africa, and with the top of the range costing US$69,900 and the lower end at US$39,900, that is a pretty good buy. Now of course the motoring experts will tell us that it is ugly and a tonne of turn off stuff, but Teslas sell themselves, people love them because of their innovative features. If I ever buy one, it is because it is a battery car and it can go into rough terrain and live to the story. It is a funky car that you can drive in New York and be able to take to Chamapango in Murewa. What are your thoughts?

The Cybertruck is finally here, I am even considering buying one after reading about it, and after being driven around in Teslas in Europe and America, they are pretty cool. The stainless steel body is uniquely weird, one wonders whether finger prints would show, what will happen to the scratches on the stainless body? The Cybertruck's stainless steel body is designed to be durable and resist corrosion, so it is certainly good for Africa, and with the top of the range costing US$69,900 and the lower end at US$39,900, that is a pretty good buy. Now of course the motoring experts will tell us that it is ugly and a tonne of turn off stuff, but Teslas sell themselves, people love them because of their innovative features. If I ever buy one, it is because it is a battery car and it can go into rough terrain and live to the story. It is a funky car that you can drive in New York and be able to take to Chamapango in Murewa. What are your thoughts?

Hopewell Chin’ono

102,539 次观看 • 2 年前

🚨: THIS BOT TOOK OVER POLYMARKET He already made ~$600k in just 3 weeks That's why I spent days to decode his trading edge And the technical side is where it hides... Others will charge $1,000 for this info, but not me: The wallet runs a passive market making engine with a fixed cadence of ~2 seconds. It continuously places limit orders on both sides of the book, YES and NO, then refreshes them after partial or full fills. That cadence matters. Too slow and you miss flow. Too fast and you lose priority in the queue. He found the balance. The goal is not direction, but inventory control. Every fill is part of a larger package, not a standalone trade. He keeps both sides active so exposure stays hedged and adjusts size based on fills and market pressure. That’s the management layer most people don’t see. Then comes the execution path. Orders are routed through the same function repeatedly, meaning this is a standing logic, not random clicks. After fills, positions are not just held or sold. They go through a cleanup cycle. Split. Merge. Redeem. That’s how conditional tokens are closed efficiently and profit is realized. Without this step, you’re holding fragments instead of resolved positions. PnL breakdown confirms it. Entry is flat, exits leak, but settlement generates most of the profit. That means the system is optimized for carry, not trading spreads alone. His wallet: [ Also important. This only works in high-activity regimes where both sides keep filling. If flow drops, inventory becomes risk. That’s when the system weakens. This is not a strategy you copy, but a full execution engine.

🚨: THIS BOT TOOK OVER POLYMARKET He already made ~$600k in just 3 weeks That's why I spent days to decode his trading edge And the technical side is where it hides... Others will charge $1,000 for this info, but not me: The wallet runs a passive market making engine with a fixed cadence of ~2 seconds. It continuously places limit orders on both sides of the book, YES and NO, then refreshes them after partial or full fills. That cadence matters. Too slow and you miss flow. Too fast and you lose priority in the queue. He found the balance. The goal is not direction, but inventory control. Every fill is part of a larger package, not a standalone trade. He keeps both sides active so exposure stays hedged and adjusts size based on fills and market pressure. That’s the management layer most people don’t see. Then comes the execution path. Orders are routed through the same function repeatedly, meaning this is a standing logic, not random clicks. After fills, positions are not just held or sold. They go through a cleanup cycle. Split. Merge. Redeem. That’s how conditional tokens are closed efficiently and profit is realized. Without this step, you’re holding fragments instead of resolved positions. PnL breakdown confirms it. Entry is flat, exits leak, but settlement generates most of the profit. That means the system is optimized for carry, not trading spreads alone. His wallet: [ Also important. This only works in high-activity regimes where both sides keep filling. If flow drops, inventory becomes risk. That’s when the system weakens. This is not a strategy you copy, but a full execution engine.

Dexter's Lab

21,632 次观看 • 5 个月前