Market Breadth Analyzer Skill

Purpose

Quantify market breadth health using a data-driven 6-component scoring system (0-100). Uses TraderMonty's publicly available CSV data to measure how broadly the market is participating in a rally or decline.

Score direction: 100 = Maximum health (broad participation), 0 = Critical weakness.

No API key required - uses freely available CSV data from GitHub Pages.

When to Use This Skill

English:

• User asks "Is the market rally broad-based?" or "How healthy is market breadth?"

• User wants to assess market participation rate

• User asks about advance-decline indicators or breadth thrust

• User wants to know if the market is narrowing (fewer stocks participating)

• User asks about equity exposure levels based on breadth conditions

Japanese:

• 「マーケットブレッドスはどうですか？」「市場の参加率は？」

• 「上昇は広がっている？」「一部の銘柄だけの上昇？」

• ブレッドス指標に基づくエクスポージャー判断

• 市場の健康度をデータで確認したい

Prerequisites

• Python 3.8+ with requests library (for fetching CSV data)

• Internet access to reach GitHub Pages URLs

• No API keys required - uses freely available public CSV data

Difference from Breadth Chart Analyst

Aspect

Market Breadth Analyzer

Breadth Chart Analyst

Data Source

CSV (automated)

Chart images (manual)

API Required

None

None

Output

Quantitative 0-100 score

Qualitative chart analysis

Components

6 scored dimensions

Visual pattern recognition

Repeatability

Fully reproducible

Analyst-dependent

Execution Workflow

Phase 1: Execute Python Script

Run the analysis script:

python3 skills/market-breadth-analyzer/scripts/market_breadth_analyzer.py \

  --detail-url "https://tradermonty.github.io/market-breadth-analysis/market_breadth_data.csv" \

  --summary-url "https://tradermonty.github.io/market-breadth-analysis/market_breadth_summary.csv"

The script will:

• Fetch detail CSV (~2,500 rows, 2016-present) and summary CSV (8 metrics)

• Validate data freshness (warn if > 5 days old)

• Calculate all 6 component scores (with automatic weight redistribution if any component lacks data)

• Generate composite score with zone classification

• Track score history and compute trend (improving/deteriorating/stable)

• Output JSON and Markdown reports

Phase 2: Present Results

Present the generated Markdown report to the user, highlighting:

• Composite score and health zone

• Strongest and weakest components

• Recommended equity exposure level

• Key breadth levels to watch

• Any data freshness warnings

6-Component Scoring System

#

Component

Weight

Key Signal

1

Breadth Level & Trend

25%

Current 8MA level + 200MA trend direction + 8MA direction modifier

2

8MA vs 200MA Crossover

20%

Momentum via MA gap and direction

3

Peak/Trough Cycle

20%

Position in breadth cycle

4

Bearish Signal

15%

Backtested bearish signal flag

5

Historical Percentile

10%

Current vs full history distribution

6

S&P 500 Divergence

10%

Multi-window (20d + 60d) price vs breadth divergence

Weight Redistribution: If any component lacks sufficient data (e.g., no peak/trough markers detected), it is excluded and its weight is proportionally redistributed among the remaining components. The report shows both original and effective weights.

Score History: Composite scores are persisted across runs (keyed by data date). The report includes a trend summary (improving/deteriorating/stable) when multiple observations are available.

Health Zone Mapping (100 = Healthy)

Score

Zone

Equity Exposure

Action

80-100

Strong

90-100%

Full position, growth/momentum favored

60-79

Healthy

75-90%

Normal operations

40-59

Neutral

60-75%

Selective positioning, tighten stops

20-39

Weakening

40-60%

Profit-taking, raise cash

0-19

Critical

25-40%

Capital preservation, watch for trough

Data Sources

Detail CSV: market_breadth_data.csv

• ~2,500 rows from 2016-02 to present

• Columns: Date, S&P500_Price, Breadth_Index_Raw, Breadth_Index_200MA, Breadth_Index_8MA, Breadth_200MA_Trend, Bearish_Signal, Is_Peak, Is_Trough, Is_Trough_8MA_Below_04

Summary CSV: market_breadth_summary.csv

• 8 aggregate metrics (average peaks, average troughs, counts, analysis period)

Both are publicly hosted on GitHub Pages - no authentication required.

Output Files

• JSON: market_breadth_YYYY-MM-DD_HHMMSS.json

• Markdown: market_breadth_YYYY-MM-DD_HHMMSS.md

• History: market_breadth_history.json (persists across runs, max 20 entries)

Reference Documents

references/breadth_analysis_methodology.md

• Full methodology with component scoring details

• Threshold explanations and zone definitions

• Historical context and interpretation guide

When to Load References

• First use: Load methodology reference for framework understanding

• Regular execution: References not needed - script handles scoring