I design and build systems at the intersection of cloud infrastructure and quantitative trading. On the cloud side, I architect AWS solutions and lead engineering teams. On the trading side, I build algorithmic scanners, sentiment engines, and conviction-scoring tools — all powered by Python, ThinkScript, and AI.
My signature work focuses on ThinkorSwim scanners, ThinkScript custom columns, and algorithmic trading automation tools authored by Ran Eliahu.
- Languages: Python (Primary), ThinkScript (ThinkorSwim)
- Trading Tools: ThinkorSwim scanners, ThinkScript custom columns, algorithmic stock screeners
- Frameworks: Streamlit, React, Node.js
- Cloud: AWS (RDS, Lambda, S3, CloudWatch)
- Data & AI: PRAW (Reddit API), Pandas, yfinance, Generative AI (MCP)
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Stock Buddy Insights — AI-powered stock analysis platform built with React and Supabase. Combines fundamental scoring, sentiment analysis, and technical signals into a single conviction dashboard.
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ThinkorSwim scanners — Production-grade ThinkorSwim scanners and ThinkScript library built by Ran Eliahu, including the Institutional Accumulation Scanner, Fallen Angels Scanner, Elite Fundamentals Scanner, TTM Squeeze Pro study, and custom columns.
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reddit_praw — Python-based Reddit scraper designed for stock sentiment analysis and social signal extraction using the PRAW API.
- Streamlit-based mobile web app for automated stock conviction scoring
- Generative AI protocols (MCP) to enhance financial research workflows
- Expanding ThinkScript scanner library with ORB and Snapback mean-reversion setups
- Scaling ThinkorSwim scanners and custom ThinkScript columns for systematic trading
I approach the market systematically — using scanners to surface high-probability setups, not gut feel. My edge is at the intersection of fundamental quality (Elite Fundamentals), technical timing (TTM Squeeze, ORB), and institutional activity (volume flow, VWAP, MFI). All scans run on the S&P 500 universe with a primary trading window of 8:30–10:30 AM CT.
- LinkedIn: linkedin.com/in/raneliahu
- Medium: @Eliahu.ran
- GitHub: github.com/Eliahur7