AI Hedge Fund Skill

Multi-agent investment analysis using legendary investor personas.

Project: https://github.com/virattt/ai-hedge-fund

Setup (first time)

# Clone project
git clone https://github.com/virattt/ai-hedge-fund /data/workspace/ai-hedge-fund

# Install
pip install -e /data/workspace/ai-hedge-fund --break-system-packages --quiet
pip install yfinance --break-system-packages --quiet

Run

Via skill script (auto-detects model):

python3 /data/workspace/skills/skills/ai-hedge-fund/scripts/run.py \
  --tickers NVDA \
  --analysts-all \
  --show-reasoning

Or direct CLI:

cd /data/workspace/ai-hedge-fund
python3 src/main.py \
  --tickers NVDA \
  --start-date 2026-01-01 \
  --end-date 2026-04-12 \
  --model "minimax/minimax-m2.5:free" \
  --analysts-all \
  --show-reasoning

Model Auto-Detection

Not hardcoded. The run.py script auto-detects from:

1. $OPENCLAW_LLM_MODEL environment variable
2. OpenClaw config (/root/.openclaw/openclaw.json)
3. Default: minimax/minimax-m2.5:free

You can also specify manually via --model flag.

Available Models

Any model from src/llm/api_models.json, e.g.:

• minimax/minimax-m2.5:free (default, free)
• qwen/qwen3.6-plus:free (free)
• gpt-4.1 (OpenAI)
• claude-sonnet-4-6 (Anthropic)

All 16+ Agents

Output

Each agent outputs: signal (bullish/bearish/neutral), confidence %, reasoning.

Portfolio Manager aggregates into final BUY/SELL/HOLD.

Data Source

yfinance (free, no API key needed)