Stockbee 20% Study

Build a daily event study of US equities that moved +20% or -20% over a defined window. Convert large movers into structured study records, classify the catalyst and chart context, update forward outcomes, and summarize recurring patterns for research.

This skill is a research, model-book, and setup-fluency workflow. It does not generate buy/sell signals, place orders, or output broker execution instructions.

When to Use

• User wants to run a Stockbee-style daily 20% mover study
• User asks which stocks moved +20% or -20% today, this week, or over a configurable lookback window
• User wants to backfill historical 20% movers and study what happened next
• User wants to identify continuation, reversal, exhaustion, or theme-cluster patterns
• User wants to build a model book of explosive winners, major failures, and failed low-quality pops
• User wants edge hints for downstream strategy research rather than immediate trade signals

Prerequisites

• Python 3.9+
• FMP API key for live US universe scans, or offline OHLCV JSON via --prices-json
• Optional structured news/catalyst JSON for higher-quality catalyst classification
• Recommended market regime artifact from market-regime-daily
• Recommended local state path: state/stockbee/20pct_study_events.jsonl

Workflow

Step 1: Scan for 20% Movers

Run after the US market close, or against the latest complete daily bar in an offline OHLCV file.

python3 skills/stockbee-20pct-study/scripts/run_20pct_study.py scan \
  --fmp-universe \
  --max-symbols 300 \
  --as-of 2026-06-28 \
  --lookback-days 5 \
  --min-abs-return-pct 20 \
  --min-price 5 \
  --min-dollar-volume 20000000 \
  --include-down-movers \
  --state-file state/stockbee/20pct_study_events.jsonl \
  --output-dir reports/

Use offline data instead of FMP: