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A 23 year old developer randomly found an open-source trading bot on GitHub. The repo already had 899 stars, so he decided to test it on a small account. He launched it in the evening. By morning, the account was up $280. The interesting part is that the bot...

149,465 views • 1 month ago •via X (Twitter)

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this is pure f*cking AI treasure 5 GitHub repos that give you the trading algo Wall Street pays millions dollars: want the engine serious quants run in production? -> NautilusTrader: a Rust-native trading engine where the backtest and the live run use the same code want a full research team arguing over every trade? -> TradingAgents: a multi-agent trading firm in one repo. analysts, researchers, a risk desk want the data terminal without the terminal bill? -> OpenBB: an open data platform for analysts, quants and AI agents want a bot that actually places the orders? -> freqtrade: free, open-source crypto trading bot with backtesting built in want all of it in one place? -> QuantDinger: an AI trading OS. research, Python strategies, backtest, paper and live trading ~282k stars of trading infrastructure. $0 in licences. now the part worth trying. every one of these has the same slow spot: the moment before the order, where something has to say yes or no. that's where Jev goes. it can't write a word. it returns BUY / SELL / HOLD with a probability in 70 to 500 milliseconds. QuantDinger already ships it as the pre-trade gate. and one repo, jev-trader, asks it buy or sell every ~300 ms and quotes a limit order on every single block. the stack in one line: OpenBB brings the data, the agents do the research, Jev makes the call, the bot places the order. the catch: fast is not the same as right. none of this is an ATM. paper trade it first. Jev + Claude + these 5 is the setup to test this month. check each repo before you install. save this.

kiosa

22,061 views • 26 days ago

this is absolutely f*cking insane Black Rock just leaked 5 GitHub repos that give you the trading desk a fund pays millions for: want a full research team arguing over every trade? -> TradingAgents: a multi-agent trading firm in one repo. analysts, researchers, a risk desk want the data terminal without the terminal bill? -> OpenBB: an open data platform for analysts, quants and AI agents want a bot that actually places the orders? -> freqtrade: free, open-source crypto trading bot with backtesting built in want the engine serious quants run in production? -> NautilusTrader: a Rust-native trading engine where the backtest and the live run use the same code want all of it in one place? -> QuantDinger: an AI trading OS. research, Python strategies, backtest, paper and live trading ~282k stars of trading infrastructure. $0 in licences. now the part worth trying. every one of these has the same slow spot: the moment before the order, where something has to say yes or no. that's where Jev goes. it can't write a word. it returns BUY / SELL / HOLD with a probability in 70 to 500 milliseconds. QuantDinger already ships it as the pre-trade gate. and one repo, jev-trader, asks it buy or sell every ~300 ms and quotes a limit order on every single block. the stack in one line: OpenBB brings the data, the agents do the research, Jev makes the call, the bot places the order. the catch: fast is not the same as right. none of this is an ATM. paper trade it first. Jev + these five is the setup to test this month. bookmark and share with a friend

kiosa

30,442 views • 27 days ago

CLAUDE BUILT A TRADING SYSTEM ON MY MAC I gave Claude full control over my Mac and just left it running overnight No prompts, no detailed instructions – I just told it to figure out how to make money on Polymarket Then I closed the laptop and went to sleep In the morning, I opened my Mac and saw the terminal still running with logs constantly updating At first it looked like random activity, but once I scrolled through it, I realized it had actually built a structured system overnight It was already tracking wallets Ranking them by performance Filtering out the ones with random entries And focusing only on the ones with consistent behavior What surprised me the most is that it didn’t stop at analysis It organized everything into a working dashboard inside the terminal Capital, PnL, winrate – all updating in real time It even ranked wallets based on performance metrics like ROI, consistency, and execution timing This is the part I would normally spend hours building manually At that point, it was ready to trade, but not actually executing anything yet So I connected it to a Telegram copytrading bot to actually execute the trades, and just let it run Bot: Polymarket: After that, it started opening positions on its own A few hours later I checked the dashboard again Capital: $12,380 P&L: +$23,128 Winrate: 100% 48 trades executed Now I’m not even trading myself I just check the dashboard and see what it’s doing And the strange part is – it keeps getting better the longer it runs

𝗖𝗛𝗔𝗜𝗡 𝗠𝗜𝗡𝗗 ⛓🧠

83,289 views • 7 months ago