gameworkerkim

gameworkerkim / vibe-investing

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투자를 위한 AI 투자(Vibe Investing) 큐레이션, 시장 분석 칼럼, AI 트레이딩 도구 2종 (Harness Quant v2 + Earnings Momentum Agent) 를 다루며 미국 나스닥, S&P500, 가상화페 투자를 다룹니다.

agentic-ai anthropic-claude earnings-momentum earnings-surprise financial-llm
31
6
100% credibility
Found Apr 19, 2026 at 31 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A GitHub repository curating AI investing resources, market analysis columns, and open-source Python tools for screening NASDAQ and S&P500 stocks using earnings momentum, sentiment, and multi-agent AI analysis.

How It Works

1
📖 Discover Vibe Investing

You stumble upon this friendly GitHub spot full of guides, stories, and tools for making smarter investment choices using AI helpers.

2
📰 Explore Curated Ideas

Dive into hand-picked lists of helpful AI investing tools and read engaging stories about market trends and risks to build your knowledge.

3
🔍 Pick the Earnings Tool

Choose the Earnings Momentum tool that hunts for stocks recovering from lows with strong sales growth and positive surprises.

4
🚀 Launch the Scan

Hit go and watch it automatically check hundreds of big US stocks through simple filters for growth, rebound strength, and crowd buzz.

5
🧠 Review AI Debates

Smart AI thinkers argue bull and bear sides, risks, and final calls to give balanced views on each promising stock.

🎉 Get Your Top Picks

Celebrate with a beautiful dashboard, top 30 list, charts, and clear reasons why these stocks shine for your portfolio.

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Star Growth

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AI-Generated Review

What is vibe-investing?

This repo curates AI tools for vibe investing—using natural language prompts to drive LLM agents that analyze market data, news, and sentiment for NASDAQ, S&P500, and crypto trades. It bundles awesome lists rating 30+ GitHub repos (with vibe checks on strengths, pitfalls, and user fit), three market analysis columns (LTCM risks, Microsoft Fintool acquisition, crypto perp manipulation), and two Python trading agents: Harness Quant v2 for scenario-based analysis with multi-agent debates, and Earnings Momentum Agent for monthly top-30 picks blending earnings surprises, fundamentals, and technicals. Users get runnable pipelines outputting JSON/CSV reports, HTML dashboards, and 24-month backtests claiming 83% 30-day hit rates.

Why is it gaining traction?

It stands out with objective GitHub vibe coding framework evaluations (not just star counts), real benchmarks like Alpha Arena exposing GPT flops versus DeepSeek wins, and agentic workflows where LLMs autonomously fetch price snapshots, sentiment from X/Reddit, and analyst consensus. Developers hook into vibe investing meaning via prompt templates for earnings momentum or harness strategies, plus crypto-specific pitfalls like MEV and slippage—saving weeks of repo hunting.

Who should use this?

Quant devs building vibe coding investing agents for US stocks or crypto, Korean traders eyeing pyKRX integrations, or Gen Z vibe investing reddit users wanting vibe value investing business education without cherry-picked hype. Ideal for backtesting earnings-focused pipelines or multi-agent judges before live deployment.

Verdict

Grab it for curated starting points and reference agents if you're prototyping LLM trading—docs are thorough with quick-start paths and pitfalls sections. At 31 stars and 1.0% credibility, it's early-stage (monthly updates promised), so validate backtests yourself before real capital.

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