COT Contrarian Detector

Detect crowded speculative positioning in CFTC futures markets (COT report analysis) to find contrarian setups using Jason Shapiro’s methodology. Screens large-speculator (“non-commercial”) net positioning across 65 futures markets (indices, rates, FX, metals, energy, crypto) via the FMP Commitment of Traders API, computes a 3-year and 26-week COT Index per market, and classifies extremes as CROWDED_LONG / CROWDED_SHORT. Use when the user asks about COT report analysis, crowded positioning, “who is trapped”, speculative positioning extremes, contrarian futures setups, or wants to run Jason Shapiro-style analysis. This skill automates crowding DETECTION only (step 1 of 5) — it does not generate trade signals by itself.

FMP Required

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

Implements step 1 of Jason Shapiro’s COT (Commitment of Traders) contrarian process: detect when large speculators are crowded into one side of a futures market. Crowded positioning is a precondition for a contrarian trade, not a trade signal — a market only becomes tradable once crowding is confirmed by a news failure and price-action reversal (steps 2-3), which this skill guides the user through manually.

Core thesis (Shapiro): Large speculators (hedge funds, CTAs, momentum traders) tend to be maximally positioned at trend exhaustion, not trend inception. When they are already crowded onto one side, the next big move is statistically more likely to run them over than to reward them further. Fade the speculators, not the commercials (commercials hedge for structural reasons and are not a crowd-psychology signal).

2. When to Use

English:

  • “What markets are the speculators crowded into right now?”
  • “Run a COT report analysis” / “Show me COT positioning extremes”
  • “Is anyone ‘trapped’ in gold / the dollar / bonds right now?”
  • User wants to find contrarian futures setups
  • User asks for a Jason Shapiro-style COT screen

Japanese:

  • 「COTレポートで買われすぎ・売られすぎのポジションを調べて」
  • 「投機筋が偏っている市場は？」
  • 「ジェイソン・シャピロ式の逆張り分析をして」

Do NOT use when:

  • The user wants a trade signal right now — crowding alone is not actionable; see Guardrails below
  • The user is asking about individual equities — COT reports cover CFTC futures markets only (indices, rates, FX, metals, energy, agri, crypto), not single stocks

3. Prerequisites

  • FMP API Key: Required. Set FMP_API_KEY environment variable or pass --api-key. COT endpoints require an FMP Premium+ plan — a free-tier key will not have access.
  • Python 3.9+ with requests installed.
  • API Budget: One call per market (23 for --core, up to ~65 for the full universe), plus one call for the market list when neither --symbols nor --core is given.

4. Quick Start 

# Curated core futures universe (23 liquid/representative markets)
python3 skills/cot-contrarian-detector/scripts/screen_cot_crowding.py --core --output-dir reports/

# Explicit symbols
python3 skills/cot-contrarian-detector/scripts/screen_cot_crowding.py --symbols "ES,GC,CL" --output-dir reports/

# Full universe (all ~65 markets FMP's COT list covers)
python3 skills/cot-contrarian-detector/scripts/screen_cot_crowding.py --output-dir reports/

5. Workflow

Phase 1: Run the crowding screen 

# Curated core futures universe (23 liquid/representative markets)
python3 skills/cot-contrarian-detector/scripts/screen_cot_crowding.py --core --output-dir reports/

# Explicit symbols
python3 skills/cot-contrarian-detector/scripts/screen_cot_crowding.py --symbols "ES,GC,CL" --output-dir reports/

# Full universe (all ~65 markets FMP's COT list covers)
python3 skills/cot-contrarian-detector/scripts/screen_cot_crowding.py --output-dir reports/

The script fetches each market’s weekly legacy COT report (large-speculator long/short positions), computes a 156-week (3-year) and 26-week COT Index per market, and classifies extremes:

  • CROWDED_LONG — COT Index >= 90 (near the 3-year net-long high)
  • CROWDED_SHORT — COT Index <= 10 (near the 3-year net-short high)
  • NEUTRAL — everything in between

Markets with insufficient history to compute the index are never silently dropped — they appear in a skipped list with the reason (e.g. “insufficient history: 40/156 weeks”).

Phase 2: Present the crowding report

Present the generated Markdown report, highlighting:

  • Which markets are CROWDED_LONG / CROWDED_SHORT and by how much
  • The 26-week index for context (is the crowding fresh or aging?)
  • Week-over-week net-position swings (fast-moving crowds are more fragile)
  • The methodology note and disclaimer — crowding is not a trade signal

Phase 3: Guide steps 2-5 manually (Shapiro process)

For any CROWDED_LONG / CROWDED_SHORT market the user wants to pursue, load references/shapiro-methodology.md and walk through the remaining steps — these are not automated:

  1. Crowding detection (done — this skill)
  2. News failure — use WebSearch to check whether recent news favorable to the crowd’s direction failed to move price the way the crowd would expect (e.g. crowded-long market doesn’t rally on bullish news). This is the core edge and the most important manual confirmation.
  3. Price-action confirmation — check the weekly chart for a reversal pattern or a failure at a new high/low.
  4. Entry — against the crowd, with a stop at the recent swing extreme and small, fixed-risk sizing (see position-sizer skill).
  5. Exit — when positioning normalizes toward neutral (COT Index back toward 50) or the stop is hit.

Never recommend an entry from crowding alone — steps 2 and 3 must both confirm first.

6. Resources

References:

  • skills/cot-contrarian-detector/references/cot-index-calculation.md
  • skills/cot-contrarian-detector/references/shapiro-methodology.md

Scripts:

  • skills/cot-contrarian-detector/scripts/cot_index.py
  • skills/cot-contrarian-detector/scripts/screen_cot_crowding.py