正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

My dad asked me why I stare at Python scripts at 3am instead of sleeping. "I'm not trading. I'm calculating." Every price on Polymarket comes from one equation: P(i) = exp(qᵢ / b) / Σ exp(qⱼ / b) This is the softmax function. The same math that GPT uses... to pick the next word - Polymarket uses to price every contract. Most traders see 40¢ and think "cheap." I see 40¢ and check the liquidity parameter. b = 50 → one whale swings the market 20% b = 100,000 → barely moves I'm use for copytrade bots Gluon: Half my old trades were in thin pools. One order wrecked my fill. I was losing money to the formula I didn't know existed. So I learned it. Then I built a bot around it. EV = true_prob × (1 - market_price) - (1 - true_prob) × market_price The bot checks b, calculates EV, sizes with Kelly: f* = (p × b - q) / b And executes before my morning coffee gets cold. $200 starting bankroll. 6 weeks later: $18,700. I didn't predict a single outcome. The bot just reads the math that 93% of traders ignore. Full breakdown - LMSR, expected value, Kelly sizing, 5 cognitive trapsshow more

Lunar

34,738 subscribers

217,746 次观看 • 6 个月前 •via X (Twitter)

教育科学技术财经

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

I gave Claude one prompt and it built me a bot that turned $200 into $14,000 on Polymarket No insider info, no lucky guess Just one equation nobody reads - and a bot that runs it 24/7 The price on Polymarket isn't set by people It's set by one formula - LMSR. You trade against pure math, not traders C(q) = b × ln(Σ e^(qi / b)) Someone buys 50 YES shares → price jumps from 50¢ to 62¢ It's softmax — same math GPT uses to pick the next word. Not a coincidence Then I found b — the liquidity parameter b = 50 → one whale swings the market 20% b = 100,000 → barely moves Half my old trades were in thin pools. One order wrecked my fill How much to bet? Kelly criterion f* = (p × b − q) / b 60% edge → Kelly says 20%. Pros use quarter-Kelly → 5% Not exciting. But you won't blow up Last piece. Price impact Contract at 40¢. You buy 1,000 shares - price climbs to 60¢ The edge disappears before you're filled I fed all of this into Claude. One prompt. 40 minutes. The bot checks b, sizes with Kelly, models impact - and executes before I finish my coffee b filters the pool. Kelly sizes the bet. Impact curve tells me where the edge dies I don't predict outcomes. The bot just reads the math

I gave Claude one prompt and it built me a bot that turned $200 into $14,000 on Polymarket No insider info, no lucky guess Just one equation nobody reads - and a bot that runs it 24/7 The price on Polymarket isn't set by people It's set by one formula - LMSR. You trade against pure math, not traders C(q) = b × ln(Σ e^(qi / b)) Someone buys 50 YES shares → price jumps from 50¢ to 62¢ It's softmax — same math GPT uses to pick the next word. Not a coincidence Then I found b — the liquidity parameter b = 50 → one whale swings the market 20% b = 100,000 → barely moves Half my old trades were in thin pools. One order wrecked my fill How much to bet? Kelly criterion f* = (p × b − q) / b 60% edge → Kelly says 20%. Pros use quarter-Kelly → 5% Not exciting. But you won't blow up Last piece. Price impact Contract at 40¢. You buy 1,000 shares - price climbs to 60¢ The edge disappears before you're filled I fed all of this into Claude. One prompt. 40 minutes. The bot checks b, sizes with Kelly, models impact - and executes before I finish my coffee b filters the pool. Kelly sizes the bet. Impact curve tells me where the edge dies I don't predict outcomes. The bot just reads the math

rari

52,212 次观看 • 6 个月前

My ex laughed when she saw me writing Python scripts instead of going to interviews. "You're calculating… weather probabilities?" I was. Every market on Polymarket runs on one equation: C(q) = b · ln Σ e^(qi/b) It's called LMSR. The same math that GPT uses to pick the next word - Polymarket uses to price beliefs. 93% of traders don't know this formula exists. They look at 40¢ and think "cheap." I look at 40¢ and calculate the theoretical price is 60¢. That's a 20-cent edge per share. One position: market at 0.35, my model said 0.55. Bought in. Market resolved. +$4,200. But the real edge isn't the formula. It's what happens after. I'm use for copytrade bots: Kelly criterion says bet 20% of your bankroll. Every pro I've studied bets 5%. Base rates, not gut feelings. Bayesian updates, not Twitter threads. 93% of Polymarket wallets lose money. They trade on vibes while the math is sitting on Wikipedia. My roommate just asked me to explain the formula to him. I wrote an entire breakdown - LMSR, expected value, Kelly sizing, the 5 cognitive traps that blow up accounts.

My ex laughed when she saw me writing Python scripts instead of going to interviews. "You're calculating… weather probabilities?" I was. Every market on Polymarket runs on one equation: C(q) = b · ln Σ e^(qi/b) It's called LMSR. The same math that GPT uses to pick the next word - Polymarket uses to price beliefs. 93% of traders don't know this formula exists. They look at 40¢ and think "cheap." I look at 40¢ and calculate the theoretical price is 60¢. That's a 20-cent edge per share. One position: market at 0.35, my model said 0.55. Bought in. Market resolved. +$4,200. But the real edge isn't the formula. It's what happens after. I'm use for copytrade bots: Kelly criterion says bet 20% of your bankroll. Every pro I've studied bets 5%. Base rates, not gut feelings. Bayesian updates, not Twitter threads. 93% of Polymarket wallets lose money. They trade on vibes while the math is sitting on Wikipedia. My roommate just asked me to explain the formula to him. I wrote an entire breakdown - LMSR, expected value, Kelly sizing, the 5 cognitive traps that blow up accounts.

Lunar

192,972 次观看 • 6 个月前

My dad looked at my screen and said "what is this, a hacker game?" It was a Polymarket bot making $400 while he was standing behind me He sat down. I explained Polymarket runs on one equation - softmax. The same math Claude uses to pick the next word C(q) = b · ln Σ e^(qi/b) 93% of traders don't know this formula exists They look at 40¢ and think "cheap" My bot looks at 40¢ and calculates the theoretical price is 58¢ I'm use for copytrade bots: That's an 18-cent edge per share Two more formulas do the rest: f* = (p·b − q) / b - Kelly Criterion. P(H|E) = P(E|H)·P(H) / P(E) - Bayes. I gave Claude all 4 and said "find every contract the market has wrong" $600 → $10,190. 425 trades. Still running 61.2% win rate - wrong 39% of the time. Doesn't matter. The sizing formula makes sure wins pay more than losses cost 87% of wallets lose money trading against this math The 4 formulas are on Wikipedia. The code fits in one file The only edge: my bot reads them at 3 AM when the market is mispriced and nobody's looking My dad still calls it a hacker game. But he stopped asking when I'm getting a "real job" Only math + code, no more

My dad looked at my screen and said "what is this, a hacker game?" It was a Polymarket bot making $400 while he was standing behind me He sat down. I explained Polymarket runs on one equation - softmax. The same math Claude uses to pick the next word C(q) = b · ln Σ e^(qi/b) 93% of traders don't know this formula exists They look at 40¢ and think "cheap" My bot looks at 40¢ and calculates the theoretical price is 58¢ I'm use for copytrade bots: That's an 18-cent edge per share Two more formulas do the rest: f* = (p·b − q) / b - Kelly Criterion. P(H|E) = P(E|H)·P(H) / P(E) - Bayes. I gave Claude all 4 and said "find every contract the market has wrong" $600 → $10,190. 425 trades. Still running 61.2% win rate - wrong 39% of the time. Doesn't matter. The sizing formula makes sure wins pay more than losses cost 87% of wallets lose money trading against this math The 4 formulas are on Wikipedia. The code fits in one file The only edge: my bot reads them at 3 AM when the market is mispriced and nobody's looking My dad still calls it a hacker game. But he stopped asking when I'm getting a "real job" Only math + code, no more

Lunar

108,420 次观看 • 6 个月前

$120K on a math degree to work at Starbucks then I found the one equation they should've taught first day: p(q) = e^(q/b) / Σ e^(qi/b) it's the softmax function > GPT uses it to predict words > Polymarket uses it to price beliefs I use it to make $8K/week bookmark this before student loans are due turns out differential equations were a scam

$120K on a math degree to work at Starbucks then I found the one equation they should've taught first day: p(q) = e^(q/b) / Σ e^(qi/b) it's the softmax function > GPT uses it to predict words > Polymarket uses it to price beliefs I use it to make $8K/week bookmark this before student loans are due turns out differential equations were a scam

bl888m

233,956 次观看 • 6 个月前

I gave Claude one Polymarket equation and told it to find every mispriced contract It hasn't stopped running in 4 months $600 → $14,190 Every Polymarket contract is priced by one formula: C(q) = b × ln(Σ e^(qi / b)) The pricing function inside it is softmax - the same math Claude uses to pick its next token Claude doesn't just understand this equation, it thinks in it So I gave it a task: "Scan every open contract, compute fair value, flag anything the market has wrong 24/7" It finds the gap, sizes the position by Kelly, enters before the crowd corrects Market shows 0.38, math shows 0.57, bot buys Resolution hits, bot collects 120 days 61.2% win rate 2.31 sharpe -3.8% max drawdown 425 trades 87% of Polymarket wallets are underwater They trade feelings against a formula that doesn't bluff, doesn't tilt, doesn't chase losses The edge is having something that reads the math faster than any human - and never stops looking

I gave Claude one Polymarket equation and told it to find every mispriced contract It hasn't stopped running in 4 months $600 → $14,190 Every Polymarket contract is priced by one formula: C(q) = b × ln(Σ e^(qi / b)) The pricing function inside it is softmax - the same math Claude uses to pick its next token Claude doesn't just understand this equation, it thinks in it So I gave it a task: "Scan every open contract, compute fair value, flag anything the market has wrong 24/7" It finds the gap, sizes the position by Kelly, enters before the crowd corrects Market shows 0.38, math shows 0.57, bot buys Resolution hits, bot collects 120 days 61.2% win rate 2.31 sharpe -3.8% max drawdown 425 trades 87% of Polymarket wallets are underwater They trade feelings against a formula that doesn't bluff, doesn't tilt, doesn't chase losses The edge is having something that reads the math faster than any human - and never stops looking

rari

311,933 次观看 • 6 个月前

My dad looked at my screen and said what is this, a hacker game? It was a Polymarket bot making $400 while he was standing behind me. He sat down. I explained. Polymarket runs on one equation. Softmax. The same math Claude uses to pick the next word. C(q) = b · ln Σ e^(qi/b) 93% of traders do not know this formula exists. They look at 40 cents and think cheap. My bot looks at 40 cents and calculates the theoretical price is 58 cents. That is an 18-cent edge per share. Two more formulas do the rest: f = (p·b − q) / b. Kelly Criterion. P(H|E) = P(E|H)·P(H) / P(E). Bayes. I gave Claude all 4 and said find every contract the market has wrong. $600 to $10,190. 425 trades. Still running. 61.2% win rate. Wrong 39% of the time. Does not matter. The sizing formula makes sure wins pay more than losses cost. 87% of wallets lose money trading against this math. The 4 formulas are on Wikipedia. The code fits in one file. The only edge: my bot reads them at 3 AM when the market is mispriced and nobody is looking. My dad still calls it a hacker game. But he stopped asking when I am getting a real job. I built the entire framework: Softmax arbitrage detection layer Kelly Criterion position sizing Bayesian probability recalibration Claude integration for autonomous execution 3 AM mispricing scanner The system runs 24/7. Finds where the math disagrees with the crowd. Executes before the edge compresses. No prediction. No gut feel. Just formulas. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word money 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the formula system this week. Start with $600. Scale on evidence.

My dad looked at my screen and said what is this, a hacker game? It was a Polymarket bot making $400 while he was standing behind me. He sat down. I explained. Polymarket runs on one equation. Softmax. The same math Claude uses to pick the next word. C(q) = b · ln Σ e^(qi/b) 93% of traders do not know this formula exists. They look at 40 cents and think cheap. My bot looks at 40 cents and calculates the theoretical price is 58 cents. That is an 18-cent edge per share. Two more formulas do the rest: f = (p·b − q) / b. Kelly Criterion. P(H|E) = P(E|H)·P(H) / P(E). Bayes. I gave Claude all 4 and said find every contract the market has wrong. $600 to $10,190. 425 trades. Still running. 61.2% win rate. Wrong 39% of the time. Does not matter. The sizing formula makes sure wins pay more than losses cost. 87% of wallets lose money trading against this math. The 4 formulas are on Wikipedia. The code fits in one file. The only edge: my bot reads them at 3 AM when the market is mispriced and nobody is looking. My dad still calls it a hacker game. But he stopped asking when I am getting a real job. I built the entire framework: Softmax arbitrage detection layer Kelly Criterion position sizing Bayesian probability recalibration Claude integration for autonomous execution 3 AM mispricing scanner The system runs 24/7. Finds where the math disagrees with the crowd. Executes before the edge compresses. No prediction. No gut feel. Just formulas. You only need Claude + device + 1 hour per day. Giving this free for 24 hours. To get it: 1. Comment the word money 2. Like and retweet this 3. Follow me Himanshu Kumar so I can DM you Save this post. Deploy the formula system this week. Start with $600. Scale on evidence.

Himanshu Kumar

13,333 次观看 • 2 个月前

$Last semester a professor pulled me aside after class. "You trade prediction markets?" - he asked. I said yeah, mostly vibes. He laughed and said that's why you're losing. He spent 20 minutes on a whiteboard showing me Bayes' Theorem, Kelly Criterion, and LMSR pricing. Said this is literally how quant funds approach binary markets. I took photos of everything. Went home, opened Claude, pasted my notes and said: “build me a bot that does exactly this 3 hours later I had a working Bayesian trading bot for Polymarket BTC markets. Here's the math it runs on every single trade: - Bayesian update update beliefs before entering P(H|D) = P(D|H) · P(H) / P(D) - Edge detection -only trade if you have an edge EV = p̂ − p_market - Kelly sizing-bet exactly the right amount f* = EV / p̂(1−p̂) - LMSR pricing how Polymarket actually prices markets p(q) = e^{q/b} / Σe^{qⱼ/b} (it's literally the softmax function from neural networks) 65% win rate. Losses happen. Kelly keeps them from blowing the account. Compounding does the rest. My CLAWD BOT turned $100 into $1000 in 30min The professor was right. Vibes don't compound. Math does.$

Last semester a professor pulled me aside after class. "You trade prediction markets?" - he asked. I said yeah, mostly vibes. He laughed and said that's why you're losing. He spent 20 minutes on a whiteboard showing me Bayes' Theorem, Kelly Criterion, and LMSR pricing. Said this is literally how quant funds approach binary markets. I took photos of everything. Went home, opened Claude, pasted my notes and said: “build me a bot that does exactly this 3 hours later I had a working Bayesian trading bot for Polymarket BTC markets. Here's the math it runs on every single trade: - Bayesian update update beliefs before entering P(H|D) = P(D|H) · P(H) / P(D) - Edge detection -only trade if you have an edge EV = p̂ − p_market - Kelly sizing-bet exactly the right amount f* = EV / p̂(1−p̂) - LMSR pricing how Polymarket actually prices markets p(q) = e^{q/b} / Σe^{qⱼ/b} (it's literally the softmax function from neural networks) 65% win rate. Losses happen. Kelly keeps them from blowing the account. Compounding does the rest. My CLAWD BOT turned $100 into $1000 in 30min The professor was right. Vibes don't compound. Math does.

AdiiX

174,137 次观看 • 6 个月前

I’ve made more money on Polymarket from understanding one equation than from trying to predict the actual events Long-term winrate: ~74% Net profit so far: $10k+ The reason is simple, every price on Polymarket comes from this function: pₖ(q) = e^(qₖ / b) / Σ e^(qᵢ / b) It’s the same softmax function used in neural networks Every buy pushes the exponent, every sell pulls it back So the price you see it’s just order flow passed through math Once you understand that, the game changes You stop asking who will win and start asking who pushed the probability curve too far

I’ve made more money on Polymarket from understanding one equation than from trying to predict the actual events Long-term winrate: ~74% Net profit so far: $10k+ The reason is simple, every price on Polymarket comes from this function: pₖ(q) = e^(qₖ / b) / Σ e^(qᵢ / b) It’s the same softmax function used in neural networks Every buy pushes the exponent, every sell pulls it back So the price you see it’s just order flow passed through math Once you understand that, the game changes You stop asking who will win and start asking who pushed the probability curve too far

Marik

106,119 次观看 • 6 个月前

The best Polymarket Quant bot for copy trading with a 99.3% win rate The bot doesn't take risks it uses math and statistics to consistently achieve a 99% win probability. Using this approach, it has earned +$805,000 across 29,184 predictions with 99.3% accuracy Here's a breakdown of its algorithm: 1. Price Mispricing Detection δ = actual win probability − implied probability Traders constantly overpay for cheap contracts (0.1–50¢), but the main edge is concentrated in contracts (80–99¢) that's exactly where the bot trades 2. Expected Value (EV) Calculation EV = (P_win × Payout) − (P_loss × Cost) Shows whether a bet is worth placing regardless of the outcome of any single trade 3. Kelly Criterion f* = (p × b − q) / b The most powerful position sizing formula ever discovered for trading and prediction markets Tells the algorithm what percentage of your portfolio to put into each bet to win in the long run His profile: Those who copy traded him have already made $35,000 But those who followed him and used Poly_Parlay made over $100,000 How? By simply mirroring his trades with a multiplier Instead of opening single trades, they added them all to a basket, so the odds multiplied Bot access:

sopersone

15,781 次观看 • 4 个月前

i made two bots fight to the death for my money on polymarket they called a truce and started printing together same 5-minute BTC markets, opposite strategies i was sure one would destroy the other bot A: momentum chainlink price feed, BTC trending up → buys "Up" at 35-45¢ bot B: mean reversion same feed, BTC pumps too hard → buys "Down" at 15-25¢ they rarely touch the same candle one eats trends, one eats reversals bot A catches impulses, bot B catches pullbacks 288 markets daily, $50-90k volume each python + chainlink RTDS + gamma API + post-only for maker rebates i built a gladiator arena got two money printers instead what happens if i add a third bot?

i made two bots fight to the death for my money on polymarket they called a truce and started printing together same 5-minute BTC markets, opposite strategies i was sure one would destroy the other bot A: momentum chainlink price feed, BTC trending up → buys "Up" at 35-45¢ bot B: mean reversion same feed, BTC pumps too hard → buys "Down" at 15-25¢ they rarely touch the same candle one eats trends, one eats reversals bot A catches impulses, bot B catches pullbacks 288 markets daily, $50-90k volume each python + chainlink RTDS + gamma API + post-only for maker rebates i built a gladiator arena got two money printers instead what happens if i add a third bot?

Argona

22,088 次观看 • 7 个月前

$This guy built a Bayesian Quant model and it made $1,362 a day on Polymarket The result is already +$29,972 PnL in 22 days with only $29 per average trade, repeating the same setup 9 times every hour across BTC "Up or Down" markets Several AI agents can handle probability, sizing and execution: 1. Every new BTC signal updates the probability through Bayes The model starts with a prior probability and updates it whenever new market data arrives: P(A|B) = P(B|A) × P(A) / P(B) If BTC momentum strengthens and the model moves fair Up from 54% to 62% while Polymarket still trades at 53¢, the system sees a 9¢ gap 2. Kelly decides position size f* = (bp - q) / b Where: p = model probability of winning q = 1 - p b = net payout for each unit risked f* = suggested fraction to allocate Higher probability and better payout increase f*, while a weaker edge pushes it toward zero This trader’s Polymarket account: tiredofwinning2much Follow this account and trade on Polymarket through this bot: 4,948 predictions with a 51% win rate Most profitable trades: $260 → $615 (+$355) $253 → $602 (+$349) $227 → $560 (+$333) A similar Bayesian Quant setup can be built with Grok Bot, using AI agents for probability updates, sizing and execution$

This guy built a Bayesian Quant model and it made $1,362 a day on Polymarket The result is already +$29,972 PnL in 22 days with only $29 per average trade, repeating the same setup 9 times every hour across BTC "Up or Down" markets Several AI agents can handle probability, sizing and execution: 1. Every new BTC signal updates the probability through Bayes The model starts with a prior probability and updates it whenever new market data arrives: P(A|B) = P(B|A) × P(A) / P(B) If BTC momentum strengthens and the model moves fair Up from 54% to 62% while Polymarket still trades at 53¢, the system sees a 9¢ gap 2. Kelly decides position size f* = (bp - q) / b Where: p = model probability of winning q = 1 - p b = net payout for each unit risked f* = suggested fraction to allocate Higher probability and better payout increase f*, while a weaker edge pushes it toward zero This trader’s Polymarket account: tiredofwinning2much Follow this account and trade on Polymarket through this bot: 4,948 predictions with a 51% win rate Most profitable trades: $260 → $615 (+$355) $253 → $602 (+$349) $227 → $560 (+$333) A similar Bayesian Quant setup can be built with Grok Bot, using AI agents for probability updates, sizing and execution

Daniro

59,829 次观看 • 5 天前

Americans are finding out they’ve been lied about Lindsay Clancy and no longer support her “Like, b*tch, she was rich. I'm finding out more and more about this b*tch every day: - I didn't know this was a rich b*tch that we were speaking on, on behalf of - I didn't know her husband made 40K a month and the b*tch didn't have to work - I didn't know she had a maid - I didn't know she had a housekeeper - I didn't know she had a nanny - I didn't know her kids went to school 3 days out the week - I didn't know she had both sets of grandparents helping her - I didn't know her husband worked from home I didn't know a lot of things about this b*tch. If privilege was a f*cking person” “I can understand a poor mom doing this. Like, "Oh, my kids, we don't even have food.” — a poor person, I can kinda see where they're coming from. But this b*tch was balling out of control” “Like, b*tch, and even then, I should've known they said she jumped from a second-story window. I'm like, "B*tch, who got 2 stories in the house? This b*tch got money"” I went through and fact checked this it’s all true - Glassdoor estimates her husband’s income at $480,000 per year - She did work, quit and didn’t have to work because her husbands income have - They had nanny/ housekeeping help - Lived in a very nice home - Their family was in the “upper middle class” category - Grandparents helped, kids went to school and husband worked at home all true This is not someone who deserves anyone’s sympathy. This is someone who had all the resources possibly available at her disposal

Americans are finding out they’ve been lied about Lindsay Clancy and no longer support her “Like, btch, she was rich. I'm finding out more and more about this btch every day: - I didn't know this was a rich btch that we were speaking on, on behalf of - I didn't know her husband made 40K a month and the btch didn't have to work - I didn't know she had a maid - I didn't know she had a housekeeper - I didn't know she had a nanny - I didn't know her kids went to school 3 days out the week - I didn't know she had both sets of grandparents helping her - I didn't know her husband worked from home I didn't know a lot of things about this btch. If privilege was a fcking person” “I can understand a poor mom doing this. Like, "Oh, my kids, we don't even have food.” — a poor person, I can kinda see where they're coming from. But this btch was balling out of control” “Like, btch, and even then, I should've known they said she jumped from a second-story window. I'm like, "Btch, who got 2 stories in the house? This btch got money"” I went through and fact checked this it’s all true - Glassdoor estimates her husband’s income at $480,000 per year - She did work, quit and didn’t have to work because her husbands income have - They had nanny/ housekeeping help - Lived in a very nice home - Their family was in the “upper middle class” category - Grandparents helped, kids went to school and husband worked at home all true This is not someone who deserves anyone’s sympathy. This is someone who had all the resources possibly available at her disposal

Wall Street Apes

843,303 次观看 • 8 天前

I told Claude to predict the next BTC candle using Kronos. didn't touch anything. +$4,200 overnight. Kronos isn't another LLM wrapper. it's a GPT-style model trained on 12 billion candles from 45 exchanges. Binance, NYSE, NASDAQ, LSE. it reads OHLC the way GPT reads English. > words = candle patterns > sentences = OHLC sequences > the corpus = every trade ever printed > the edge is simple: P(next | history) = softmax(W · h_t) same math GPT uses to predict the next word, except the "word" is the next candle. no twitter sentiment. no blog scraping. no hallucinated confidence. just statistics over 12B real price moves. I plugged Kronos into a 5-min BTC Polymarket bot. input: last 50 candles output: probability next candle closes up trades only when |p_model - p_market| > 0.04 72 hours: $300 → $4,500 ChatGPT looks at a chart and pattern-matches against an article it read. Kronos looks at the chart and remembers 12 billion of them. 87% of Polymarket is exit liquidity. one of these models is actually trading the market. 21.8k stars, free, MIT license. Tsinghua University release.

I told Claude to predict the next BTC candle using Kronos. didn't touch anything. +$4,200 overnight. Kronos isn't another LLM wrapper. it's a GPT-style model trained on 12 billion candles from 45 exchanges. Binance, NYSE, NASDAQ, LSE. it reads OHLC the way GPT reads English. > words = candle patterns > sentences = OHLC sequences > the corpus = every trade ever printed > the edge is simple: P(next | history) = softmax(W · h_t) same math GPT uses to predict the next word, except the "word" is the next candle. no twitter sentiment. no blog scraping. no hallucinated confidence. just statistics over 12B real price moves. I plugged Kronos into a 5-min BTC Polymarket bot. input: last 50 candles output: probability next candle closes up trades only when |p_model - p_market| > 0.04 72 hours: $300 → $4,500 ChatGPT looks at a chart and pattern-matches against an article it read. Kronos looks at the chart and remembers 12 billion of them. 87% of Polymarket is exit liquidity. one of these models is actually trading the market. 21.8k stars, free, MIT license. Tsinghua University release.

RetroChainer

94,443 次观看 • 4 个月前

This guy turned Grok Bot into an MM system and it made $1,335 a day The result is already +$65,425 PnL with only $40 per average trade while repeating the same setup 9 times every hour across BTC "Up or Down" markets Six AI agents work together as one algorithm: 1. They try to build Up + Down < 100¢ The bot accumulates both outcomes at different moments as BTC moves For example: Down at 38¢ + Up later at 56¢ = 94¢ total cost (6¢ locked on every complete set) The two entries do not need to happen at the same time 2. Order Flow tells the agents which side to accumulate next The model tracks imbalance inside the book: OBI = (B - A) / (B + A) When buying pressure shifts toward one outcome, its fair probability changes and the bot adjusts which side it wants to accumulate This trader’s Polymarket account: GoodFallen 10,322 predictions with a 50% win rate Follow this account and trade on Polymarket through this bot: Most profitable trades: $974 → $2,525 (+$1,551) $723 → $1,923 (+$1,200) $1,270 → $2,323 (+$1,053) The bot uses changes in Order Flow and BTC price to keep rebuilding the same position before resolution

This guy turned Grok Bot into an MM system and it made $1,335 a day The result is already +$65,425 PnL with only $40 per average trade while repeating the same setup 9 times every hour across BTC "Up or Down" markets Six AI agents work together as one algorithm: 1. They try to build Up + Down < 100¢ The bot accumulates both outcomes at different moments as BTC moves For example: Down at 38¢ + Up later at 56¢ = 94¢ total cost (6¢ locked on every complete set) The two entries do not need to happen at the same time 2. Order Flow tells the agents which side to accumulate next The model tracks imbalance inside the book: OBI = (B - A) / (B + A) When buying pressure shifts toward one outcome, its fair probability changes and the bot adjusts which side it wants to accumulate This trader’s Polymarket account: GoodFallen 10,322 predictions with a 50% win rate Follow this account and trade on Polymarket through this bot: Most profitable trades: $974 → $2,525 (+$1,551) $723 → $1,923 (+$1,200) $1,270 → $2,323 (+$1,053) The bot uses changes in Order Flow and BTC price to keep rebuilding the same position before resolution

Daniro

19,789 次观看 • 14 天前

My dad bet me $100 I couldn't make money on Polymarket without predicting a single outcome... I didn't predict anything. I just found two markets that move together - but one is 4 minutes late. Last month: +$22,400. He still owes me the $100. Polymarket has 500+ active markets. Most traders pick one and guess. I don't guess. I measure. Two markets. Same underlying event. Different prices. One reacts to news in 90 seconds. The other takes 6 minutes. That gap is pure math: ρ(X,Y) = Σ(xᵢ - x̄)(yᵢ - ȳ) / √[Σ(xᵢ - x̄)² · Σ(yᵢ - ȳ)²] Pearson correlation. When ρ > 0.85 - they move together. But "together" doesn't mean "at the same time." Cross-correlation at lag k tells you how many minutes one trails the other: R_xy(k) = Σ X(t) · Y(t+k) I'm use for copytrade bots: I found 14 pairs with ρ > 0.87 and lag between 2–11 minutes. The slow market hasn't repriced yet. The fast one already moved. You buy the slow one before it catches up. Z-score tells you when the spread is stretched enough to trade: z = (spread - μ) / σ |z| > 2.0 - entry. |z| 2.0 Average hold time: 23 minutes Max drawdown: 3.1% +$22,400 in 31 days. Starting capital: $500. My roommate asked me to explain the math. I wrote the full breakdown - Pearson correlation, cross-correlation lag detection, Z-score entries, Kelly sizing, and the 3 pairs that printed the most.

My dad bet me $100 I couldn't make money on Polymarket without predicting a single outcome... I didn't predict anything. I just found two markets that move together - but one is 4 minutes late. Last month: +$22,400. He still owes me the $100. Polymarket has 500+ active markets. Most traders pick one and guess. I don't guess. I measure. Two markets. Same underlying event. Different prices. One reacts to news in 90 seconds. The other takes 6 minutes. That gap is pure math: ρ(X,Y) = Σ(xᵢ - x̄)(yᵢ - ȳ) / √[Σ(xᵢ - x̄)² · Σ(yᵢ - ȳ)²] Pearson correlation. When ρ > 0.85 - they move together. But "together" doesn't mean "at the same time." Cross-correlation at lag k tells you how many minutes one trails the other: R_xy(k) = Σ X(t) · Y(t+k) I'm use for copytrade bots: I found 14 pairs with ρ > 0.87 and lag between 2–11 minutes. The slow market hasn't repriced yet. The fast one already moved. You buy the slow one before it catches up. Z-score tells you when the spread is stretched enough to trade: z = (spread - μ) / σ |z| > 2.0 - entry. |z| 2.0 Average hold time: 23 minutes Max drawdown: 3.1% +$22,400 in 31 days. Starting capital: $500. My roommate asked me to explain the math. I wrote the full breakdown - Pearson correlation, cross-correlation lag detection, Z-score entries, Kelly sizing, and the 3 pairs that printed the most.

Lunar

26,265 次观看 • 6 个月前

My ex asked what I do for a living. I said "I argue with an AI about probability at 2AM" She thought I was joking I wasn't. That AI is Claude. And those arguments turned into a Polymarket bot that runs 24/7 Every cycle it pulls 50+ markets, feeds each one to Claude with structured prompts, and gets back a probability + confidence level. If EV > 5% - it trades. If not - it waits Took me 7 prompt rewrites to get Claude from 40% accuracy to 75%. v1 was garbage. v7 is what runs now Position sizing: Quarter Kelly. The formula is on Wikipedia. The discipline to actually use it - that's the hard part 847 trades so far. GTC orders, not FOK. Fill rate went from 60% to 95% after that one switch The whole thing runs on a $5 VPS. systemd restarts it if it crashes. Telegram pings me on every fill She asked "so the computer just makes money?" Basically yes. But it took 2 weeks of building and 30+ tools to get here Now you can skip those 2 weeks via Pretracer:

My ex asked what I do for a living. I said "I argue with an AI about probability at 2AM" She thought I was joking I wasn't. That AI is Claude. And those arguments turned into a Polymarket bot that runs 24/7 Every cycle it pulls 50+ markets, feeds each one to Claude with structured prompts, and gets back a probability + confidence level. If EV > 5% - it trades. If not - it waits Took me 7 prompt rewrites to get Claude from 40% accuracy to 75%. v1 was garbage. v7 is what runs now Position sizing: Quarter Kelly. The formula is on Wikipedia. The discipline to actually use it - that's the hard part 847 trades so far. GTC orders, not FOK. Fill rate went from 60% to 95% after that one switch The whole thing runs on a $5 VPS. systemd restarts it if it crashes. Telegram pings me on every fill She asked "so the computer just makes money?" Basically yes. But it took 2 weeks of building and 30+ tools to get here Now you can skip those 2 weeks via Pretracer:

Lunar

10,345 次观看 • 5 个月前

TraderMayne reveals the one piece of advice that changed how he trades forever "The best advice a fellow trader ever gave me was from Tom Dante. It was entering the trade and then removing the P&L screen from my monitor. I couldn't see it anymore. All I would look at is the chart. Trading the chart instead of your P&L." "It's very tempting to close a big trade when you're in the green. It's very tempting to close when you're in the red. But that's trading your P&L. If I think price is going from here to here and I'm right, or here to here and I'm wrong, I should be comfortable sitting in that thing until one of those two things happens."

TraderMayne reveals the one piece of advice that changed how he trades forever "The best advice a fellow trader ever gave me was from Tom Dante. It was entering the trade and then removing the P&L screen from my monitor. I couldn't see it anymore. All I would look at is the chart. Trading the chart instead of your P&L." "It's very tempting to close a big trade when you're in the green. It's very tempting to close when you're in the red. But that's trading your P&L. If I think price is going from here to here and I'm right, or here to here and I'm wrong, I should be comfortable sitting in that thing until one of those two things happens."

Kai

25,903 次观看 • 1 个月前

Chinese student used AI from Anthropic to turn $1,000 into $1,500,000 He studies at Tsinghua University in Beijing. His account is k9Q2m In such a young age he already make a million simply knowing the right formulas and being able to use Claude Result: $1,430 → $1,550,750 44,364 trades Win rate 100% The biggest win $23,600 on a single bet k9Q2m profile: How it bots work: The bot runs 6 formulas hedge funds use simultaneously, every tick. Most traders guess. This bot calculates. Formula 1 - LMSR Pricing Polymarket prices move on a logarithmic curve. The bot knows the exact price impact before entering. Market says 31¢ for BTC up in 5 minutes. The model sees the curve is mispriced. The bot enters before the correction. Formula 2 - Kelly Criterion Renaissance Capital uses it. Two Sigma uses it. Now your bot uses it. Every bet is sized exactly right. Never too big to blow the account. Never too small to matter. $1,000 bankroll. Consistent edge. Kelly compounds it into something real. Formula 3 - EV Gap Detection The bot scans every BTC market looking for one thing: - Where is the market price wrong by more than 5%? - Market says 30¢. Real probability is 55¢. EV = +0.52. The bot enters. Most people never see this gap. The bot never misses it. Formula 4 - KL-Divergence BTC 5-minute and 15-minute markets are correlated. When they drift apart - that's an arb. The bot measures the statistical distance between them every second. When it crosses 0.2, it flags the trade. This is how hedge funds extracted $100K+ on correlated election markets. The same logic runs here. Formula 5 - Bayesian Updates New block confirmed. Volume spike. Price movement. The bot doesn't ignore signals - it updates. Prior probability was 54%. New data comes in. Posterior jumps to 71%. The bot re-prices in real time while the market is still asleep. Formula 6 - Stoikov Execution Entering at the wrong moment kills the edge. The bot calculates the reservation price-the exact point where the risk-adjusted entry makes sense. It doesn't chase. It doesn't panic. It waits for the right tick, then fills What this means in practice: - Every few seconds the bot runs all six formulas in parallel. - If LMSR confirms mispricing - EV gap is above 5% - Kelly says the bet size is justified - Bayesian posterior agrees - KL-divergence flags the correlated drift - Stoikov clears the execution price Only then does the bot enter. Six filters. One trade. This isn't a trading bot. It's a hedge fund strategy running on a prediction market. The edge is real. The math is public. The difference is most people never build it. Just insert all these formulas into Claude and create your own bot Add this post to bookmarks so you don’t lose it Soon I will publish another bot with working formulas

AdiiX

719,007 次观看 • 6 个月前

I started winning a lot more trades when I realized waiting is part of the strategy. Most of my trading session is spent waiting. - Wait for price to reach my zone - Wait for the liquidity sweep - Wait for the market shift Only when everything lines up with my plan do I think about taking a trade. None of those things are in my control. I can't make price move faster. I can't force a setup to appear. All I can do is wait until the market gives me what I'm looking for. Some days I wait for hours to take one position. Some days I don't take one at all. I'm completely fine with that. The market will always give you another opportunity tomorrow. And the less pressure I put on myself to find trades, the better my decisions become. The money you're looking for comes from the trades you have the discipline to wait for.

I started winning a lot more trades when I realized waiting is part of the strategy. Most of my trading session is spent waiting. - Wait for price to reach my zone - Wait for the liquidity sweep - Wait for the market shift Only when everything lines up with my plan do I think about taking a trade. None of those things are in my control. I can't make price move faster. I can't force a setup to appear. All I can do is wait until the market gives me what I'm looking for. Some days I wait for hours to take one position. Some days I don't take one at all. I'm completely fine with that. The market will always give you another opportunity tomorrow. And the less pressure I put on myself to find trades, the better my decisions become. The money you're looking for comes from the trades you have the discipline to wait for.

The Trading Geek (Brad Goh)

15,478 次观看 • 1 个月前