New to Claude Skills? Learn how to install them →

Get Claude Skills
tradermonty on GitHub

Stockbee 20% Study

Free

Analyze explosive stock movements for research insights.

by tradermonty2.6k stars on tradermonty/claude-trading-skills
Updated Aug 10, 2026
Get this skill

Free · Opens the source repo

What Stockbee 20% Study does

The Stockbee 20% Study skill allows users to conduct a comprehensive analysis of US equities that have experienced significant price movements of +20% or -20%. This skill facilitates the creation of structured study records based on large price movers, enabling users to classify catalysts, analyze context, and track forward outcomes. By summarizing recurring patterns, it serves as a valuable resource for traders and researchers looking to understand market behavior and identify potential trading strategies.

This skill is particularly useful for those who want to run daily studies on stock movements, backfill historical data, and identify trends such as continuation or reversal patterns. It does not provide direct buy or sell signals, making it ideal for users focused on research and model building rather than immediate trading actions. The workflow includes scanning for movers, enriching event data with catalysts, updating outcomes over various time horizons, and summarizing cohort statistics.

Users can leverage the skill to build a model book of explosive market moves, analyze failures, and derive edge hints for future strategies. The output includes detailed reports and structured data files, which can be utilized for further analysis or integration with other tools. This skill is well-suited for quantitative analysts, traders, and researchers who are looking to deepen their understanding of market dynamics through systematic study of stock price movements.

When to use it

Use this skill when you need to analyze daily stock movements of +20% or -20% and want to understand the underlying catalysts and outcomes.

When not to use it

This skill is not suitable for users seeking real-time trading signals or execution instructions, as it focuses on research and analysis rather than trading actions.

What you can build with it

Daily Stock Movement Analysis

Run daily scans to identify stocks that moved significantly and analyze their catalysts.

Historical Data Backfill

Backfill and analyze historical 20% movers to understand market behavior over time.

Cohort Pattern Summary

Summarize cohort statistics to identify recurring patterns and potential trading strategies.

How to install Stockbee 20% Study

View source

1. Install with the skills CLI

npx skills add tradermonty/claude-trading-skills/stockbee-20pct-study --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by tradermonty

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:

python3 skills/stockbee-20pct-study/scripts/run_20pct_study.py scan \
  --prices-json data/us_daily_ohlcv.json \
  --as-of 2026-06-28 \
  --lookback-days 5 \
  --include-down-movers \
  --state-file state/stockbee/20pct_study_events.jsonl \
  --output-dir reports/

Step 2: Enrich and Classify Events

Use structured catalyst data when available. The enrichment step is best-effort: if no news record is found, the event remains a price-only NO_CLEAR_NEWS study record.

python3 skills/stockbee-20pct-study/scripts/run_20pct_study.py enrich \
  --events-json reports/stockbee_20pct_events_YYYY-MM-DD_HHMMSS.json \
  --news-json data/catalysts_YYYY-MM-DD.json \
  --market-regime reports/market_regime_latest.json \
  --state-file state/stockbee/20pct_study_events.jsonl \
  --output-dir reports/

Step 3: Update Matured Forward Outcomes

Update 1-day, 3-day, 5-day, 10-day, and 20-day forward outcomes after enough future bars exist.

python3 skills/stockbee-20pct-study/scripts/run_20pct_study.py update-outcomes \
  --prices-json data/us_daily_ohlcv.json \
  --state-file state/stockbee/20pct_study_events.jsonl \
  --horizons 1,3,5,10,20 \
  --output-dir reports/

The update records close return, MFE, MAE, direction-adjusted continuation return, and outcome tags.

Step 4: Summarize Cohorts

python3 skills/stockbee-20pct-study/scripts/run_20pct_study.py summarize \
  --state-file state/stockbee/20pct_study_events.jsonl \
  --group-by direction,catalyst.label,technical_context.pattern_label,technical_context.close_quality \
  --min-sample 10 \
  --output-dir reports/

Treat rule_candidates and exported edge hints as research prompts. Require representative chart review, sample-size thresholds, and out-of-sample validation before changing trade rules.

Step 5: Historical Backfill

python3 skills/stockbee-20pct-study/scripts/run_20pct_study.py backfill \
  --from 2020-01-01 \
  --to 2026-06-28 \
  --prices-json data/us_daily_ohlcv.json \
  --min-abs-return-pct 20 \
  --include-down-movers \
  --state-file state/stockbee/20pct_study_events.jsonl \
  --output-dir reports/

Backfill records are marked CURRENT_UNIVERSE_BACKFILL_SURVIVORSHIP_BIAS by default. Add --survivorship-complete only when the supplied OHLCV includes delisted symbols and historical universe coverage.

Output Format

  • stockbee_20pct_events_YYYY-MM-DD_HHMMSS.json — scan metadata and event records
  • stockbee_20pct_daily_report_YYYY-MM-DD_HHMMSS.md — human-readable daily 20% study report
  • stockbee_20pct_enriched_YYYY-MM-DD_HHMMSS.json — enriched event records
  • stockbee_20pct_outcome_update_YYYY-MM-DD_HHMMSS.json/md — matured forward outcome update
  • stockbee_20pct_cohort_summary_YYYY-MM-DD_HHMMSS.json/md — cohort statistics and rule candidates
  • stockbee_20pct_edge_hints_YYYY-MM-DD_HHMMSS.yaml — edge-hint export for downstream research skills
  • state/stockbee/20pct_study_events.jsonl — durable 20% mover model book

Resources

  • references/methodology.md — 20% study methodology and review checklist
  • references/event_schema.md — JSONL event record schema
  • references/catalyst_taxonomy.md — catalyst and risk label definitions
  • references/scoring_system.md — event quality and study priority scoring
  • references/cohort_mining_rules.md — overfitting controls and sample-size rules
  • scripts/run_20pct_study.py — CLI for scan, enrich, update-outcomes, summarize, and backfill

Frequently asked questions about Stockbee 20% Study

Similar skills

Scientific Problem Selection

Streamline your research problem selection process.

Nextflow Development

Run nf-core bioinformatics pipelines with ease.

Nature Reviewer Assessment

Simulate peer review for scientific manuscripts.

Research Writing Pipeline

Streamline your scientific writing with structured proposal-first methodologies.

Nature Literature Downloader

Efficiently download academic literature from various sources.

Auto Research

Streamline your NeMo-RL experiments with automated workflows.