LangAlpha
Unverified ML strategy on Multi by Chen-zexi. BotFinder score 18 out of 100.
Multi-Agent Financial Research workflow
Source: github
BotFinder analysis pending.
LangAlpha
LangAlpha ⚠️ Notice: This repository is early work and is no longer considered best practice as of March 26, 2026. If you are interested in an Agent for Finance, please visit ginlix-ai/LangAlpha for the most recent work. Table of Contents - LangAlpha - Table of Contents - Key Technologies - Core Functionality: Market Intelligence Agent Workflow - Damodaran Valuation Model: - Trading Strategy: - Repository Structure - Example Analysis - General Guide for Usage: - How to get better result: - What LangAlpha Does Well: - Limitations to Keep in Mind: - Data Accessible by Agent - Getting Started - 1. Clone the Repository - 2. Docker Setup with Web UI (Recommended) Note: Stocksflags is now renamed to LangAlpha LangAlpha is a multi-agent AI equity analysis tool designed to provide comprehensive insights into the stock market. It leverages Large Language Models (LLMs) and agentic workflows to automate data gathering, processing, and analysis. Key Technologies Programming Language: Python AI/LLM Frameworks: LangChain, LangGraph Core Agent Workflow: Implemented in src/agent/marketintelligenceag
⚠ No verified equity curve — no track-record source connected.
Drawdown profile
Data unavailable — contact the owner.
Verification ledger
How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
No score history is stored yet — only the current score is shown.
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⚠ No live verification account connected — ask for proof before buying.
Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)