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yourhanez :

Wih welcome back? 😤

2026-09-29 05:52:41

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hllgrd :

2026-09-29 05:57:35

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Rick Bryan :

eu

2026-09-29 06:23:14

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SCARF // Two-tone scarf the perfect winter accessory 🤎 From our favourite 🟨 app Comment scarf or Dm for more details 🤎🤎 #bougieonabudget #unboxing #designer #scarf #accessories

SCARF // Two-tone scarf the perfect winter accessory 🤎 From our favourite 🟨 app Comment scarf or Dm for more details 🤎🤎 #bougieonabudget #unboxing #designer #scarf #accessories

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Фотосессия за одну минуту — без студии, фотографа и больших затрат 🤯📸 Показываю, как с помощью ИИ превратить обычную фотографию в целую профессиональную фотосессию. Быстро, просто, а результат выглядит так, будто над ним работала целая команда 🔥 Сохраняйте инструкцию и попробуйте повторить! #нейросеть #иифото #фотосессия #лайфхак #обработкафото

Фотосессия за одну минуту — без студии, фотографа и больших затрат 🤯📸 Показываю, как с помощью ИИ превратить обычную фотографию в целую профессиональную фотосессию. Быстро, просто, а результат выглядит так, будто над ним работала целая команда 🔥 Сохраняйте инструкцию и попробуйте повторить! #нейросеть #иифото #фотосессия #лайфхак #обработкафото

Finally 🦦 #fyp #foryou

Finally 🦦 #fyp #foryou

💻📈 6 GITHUB REPOS THAT LET YOU RUN A HEDGE FUND FROM YOUR LAPTOP You don’t need a Wall Street office to start learning quantitative trading. Your laptop can become a small research lab for: 📊 Market data 🤖 ML strategies 📈 Backtesting 🧠 AI agents 🛡️ Risk management 💰 Portfolio management Here are 6 GitHub repos worth exploring: 1️⃣ AI HEDGE FUND 🤖 A multi-agent AI hedge fund where different agents handle areas such as fundamentals, technicals, sentiment, valuation, risk, and portfolio management. ⭐ 59K+ stars 💻 Can run locally with Python and can use Ollama for local LLMs. GitHub: virattt/ai-hedge-fund ⸻ 2️⃣ NAUTILUS TRADER ⚡ A serious algorithmic trading platform built for: → Research → Backtesting → Portfolio strategies → Live trading → Multiple asset classes Its architecture is designed to keep research/backtesting and live strategy implementations closely aligned. GitHub: NautilusTrader ⸻ 3️⃣ LIUALGOTRADER 🧮 A Python-based algorithmic trading framework with: → Backtesting → ML support → Strategy optimization → Market data → Automated trading The project explicitly describes running from a laptop as well as scaling to hosted Linux infrastructure. GitHub: LiuAlgoTrader ⸻ 4️⃣ QUANT HEDGE FUND SYSTEM 📊 An end-to-end Python project covering: → Market data collection → 25+ years of data → Backtesting → MLflow experiment tracking → Automated execution → Interactive Brokers integration Great repository to study if you’re interested in quant + MLOps + trading systems. GitHub: QuantHedgeFund ⸻ 5️⃣ AI-NATIVE HEDGE FUND 🧠 A local AI-native trading prototype combining: → Multiple agents → Strategy ensembles → Risk management → Backtesting → Local LLMs → Paper trading → Audit logs It uses Ollama + market data tools + paper trading, making it interesting for people experimenting on their own machine. GitHub: ai-native-hedge-fund ⸻ 6️⃣ AUTONOMOUS TRADING SYSTEM 🚀 A multi-strategy algorithmic trading system featuring: → 6 quantitative strategies → Backtesting → Real-time dashboard → Portfolio management → Risk controls → Paper trading The repository provides a local setup using Python and Node.js. GitHub: autonomous-trading-system ⸻ 🔥 WHAT YOU CAN LEARN FROM THESE REPOS Don’t just clone and run them. Study the architecture: Market Data ↓ Feature Engineering ↓ Strategy / ML Model ↓ Signal Generation ↓ Portfolio Construction ↓ Risk Management ↓ Backtesting ↓ Paper Trading ↓ Monitoring That’s where the real learning happens. 🎯 IF YOU’RE A DATA SCIENCE / AI STUDENT Start with: 🥇 AI Hedge Fund 🥈 AI-Native Hedge Fund 🥉 Quant Hedge Fund System Then build your own simplified version. Laptop → Data → ML → Backtest → Risk → Dashboard ⚠️ These repositories are for learning/research and paper trading. Backtested performance is not a guarantee of future returns, and don’t connect a strategy to real money until you understand the risks. #GitHub #HedgeFund #QuantFinance #AlgorithmicTrading #creatorsearchinsights

💻📈 6 GITHUB REPOS THAT LET YOU RUN A HEDGE FUND FROM YOUR LAPTOP You don’t need a Wall Street office to start learning quantitative trading. Your laptop can become a small research lab for: 📊 Market data 🤖 ML strategies 📈 Backtesting 🧠 AI agents 🛡️ Risk management 💰 Portfolio management Here are 6 GitHub repos worth exploring: 1️⃣ AI HEDGE FUND 🤖 A multi-agent AI hedge fund where different agents handle areas such as fundamentals, technicals, sentiment, valuation, risk, and portfolio management. ⭐ 59K+ stars 💻 Can run locally with Python and can use Ollama for local LLMs. GitHub: virattt/ai-hedge-fund ⸻ 2️⃣ NAUTILUS TRADER ⚡ A serious algorithmic trading platform built for: → Research → Backtesting → Portfolio strategies → Live trading → Multiple asset classes Its architecture is designed to keep research/backtesting and live strategy implementations closely aligned. GitHub: NautilusTrader ⸻ 3️⃣ LIUALGOTRADER 🧮 A Python-based algorithmic trading framework with: → Backtesting → ML support → Strategy optimization → Market data → Automated trading The project explicitly describes running from a laptop as well as scaling to hosted Linux infrastructure. GitHub: LiuAlgoTrader ⸻ 4️⃣ QUANT HEDGE FUND SYSTEM 📊 An end-to-end Python project covering: → Market data collection → 25+ years of data → Backtesting → MLflow experiment tracking → Automated execution → Interactive Brokers integration Great repository to study if you’re interested in quant + MLOps + trading systems. GitHub: QuantHedgeFund ⸻ 5️⃣ AI-NATIVE HEDGE FUND 🧠 A local AI-native trading prototype combining: → Multiple agents → Strategy ensembles → Risk management → Backtesting → Local LLMs → Paper trading → Audit logs It uses Ollama + market data tools + paper trading, making it interesting for people experimenting on their own machine. GitHub: ai-native-hedge-fund ⸻ 6️⃣ AUTONOMOUS TRADING SYSTEM 🚀 A multi-strategy algorithmic trading system featuring: → 6 quantitative strategies → Backtesting → Real-time dashboard → Portfolio management → Risk controls → Paper trading The repository provides a local setup using Python and Node.js. GitHub: autonomous-trading-system ⸻ 🔥 WHAT YOU CAN LEARN FROM THESE REPOS Don’t just clone and run them. Study the architecture: Market Data ↓ Feature Engineering ↓ Strategy / ML Model ↓ Signal Generation ↓ Portfolio Construction ↓ Risk Management ↓ Backtesting ↓ Paper Trading ↓ Monitoring That’s where the real learning happens. 🎯 IF YOU’RE A DATA SCIENCE / AI STUDENT Start with: 🥇 AI Hedge Fund 🥈 AI-Native Hedge Fund 🥉 Quant Hedge Fund System Then build your own simplified version. Laptop → Data → ML → Backtest → Risk → Dashboard ⚠️ These repositories are for learning/research and paper trading. Backtested performance is not a guarantee of future returns, and don’t connect a strategy to real money until you understand the risks. #GitHub #HedgeFund #QuantFinance #AlgorithmicTrading #creatorsearchinsights

FVG liên tục dính SL ? Sai lầm ở đâu ? #setuptrading

FVG liên tục dính SL ? Sai lầm ở đâu ? #setuptrading

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