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Market Sentiment
Neutral (Overbought)
Based on the latest 13 weeks of non-commercial positioning data. ℹ️

Cotton No. 2 (Non-Commercial)

13-Wk Max 72,674 132,148 5,481 15,988 -11,738
13-Wk Min 59,870 77,082 -6,766 -13,336 -62,137
13-Wk Avg 66,717 108,127 44 -2,316 -41,410
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
April 29, 2025 65,344 77,082 4,547 -8,793 -11,738 53.19% 210,605
April 22, 2025 60,797 85,875 927 -2,451 -25,078 11.87% 217,691
April 15, 2025 59,870 88,326 -6,766 -13,336 -28,456 18.76% 222,397
April 8, 2025 66,636 101,662 -3,893 -10,846 -35,026 16.56% 266,116
April 1, 2025 70,529 112,508 5,481 -6,546 -41,979 22.27% 289,328
March 25, 2025 65,048 119,054 623 5,325 -54,006 -9.54% 283,040
March 18, 2025 64,425 113,729 -1,512 -8,932 -49,304 13.08% 272,839
March 11, 2025 65,937 122,661 -4,074 -9,487 -56,724 8.71% 270,769
March 4, 2025 70,011 132,148 -2,663 15,988 -62,137 -42.89% 280,617
February 25, 2025 72,674 116,160 354 6,772 -43,486 -17.31% 268,701
February 18, 2025 72,320 109,388 3,488 -2,009 -37,068 12.91% 278,259
February 11, 2025 68,832 111,397 3,935 -4,267 -42,565 16.16% 287,555
February 4, 2025 64,897 115,664 131 8,470 -50,767 -19.65% 289,974

Net Position (13 Weeks) - Non-Commercial

Change in Long and Short Positions (13 Weeks) - Non-Commercial

COT Interpretation for COTTON

Comprehensive Guide to COT Reports for Agricultural Markets

Table of Contents

Introduction

The Commitment of Traders (COT) reports are particularly valuable for agricultural commodity markets, where a complex mix of producers, processors, speculators, and index funds creates unique market dynamics. This specialized guide focuses on applying COT analysis specifically to agricultural futures markets to gain trading and hedging advantages.

Agricultural markets present distinct characteristics in COT reports due to their seasonal production cycles, weather dependencies, global supply chain factors, and the essential nature of these commodities in the food supply chain. Understanding these nuances can provide significant analytical advantages.

Agricultural COT Reports: Key Characteristics

The CFTC provides specialized report formats that are particularly relevant for agricultural markets:

  1. Supplemental COT Report

    Created specifically for agricultural commodities to address the growing influence of index traders. This report separates index traders from the traditional commercial category, providing greater visibility into true commercial hedging versus passive long-only index investment.

  2. Disaggregated COT Report

    Particularly useful for agricultural markets as it separates:

    • Producer/Merchant/Processor/User: Actual agricultural industry participants
    • Swap Dealers: Often representing index exposure
    • Managed Money: Speculative funds and commodity trading advisors
    • Other Reportables: Other large traders
    • Non-Reportable Positions: Smaller traders
  3. Combined Futures and Options Report

    Important for agricultural markets where options strategies are frequently used by producers and processors for hedging.

Agricultural Markets Covered

The COT reports cover the following major agricultural futures markets:

Grains and Oilseeds

  • Corn (CBOT)
  • Soybeans (CBOT)
  • Wheat (CBOT, KCBT, MGEX)
  • Soybean Oil (CBOT)
  • Soybean Meal (CBOT)
  • Oats (CBOT)
  • Rough Rice (CBOT)
  • Canola (ICE)

Softs

  • Cotton (ICE)
  • Coffee (ICE)
  • Sugar (ICE)
  • Cocoa (ICE)
  • Orange Juice (ICE)

Livestock

  • Live Cattle (CME)
  • Feeder Cattle (CME)
  • Lean Hogs (CME)

Dairy

  • Class III Milk (CME)

Special Considerations for Agricultural Markets

  1. Seasonality

    Agricultural COT data must be interpreted within the context of seasonal production cycles:

    • Planting Seasons: Typically see increased hedging by producers
    • Growing Seasons: Weather concerns can drive speculative activity
    • Harvest Periods: Often see peak short hedging by producers
    • Storage Periods: Commercial positions shift from producers to processors and merchants
  2. USDA Reports Impact

    Major USDA reports cause significant position adjustments:

    • Prospective Plantings (March)
    • Acreage Report (June)
    • Crop Production Reports (Monthly)
    • WASDE Reports (Monthly)
    • Grain Stocks Reports (Quarterly)
  3. Weather Sensitivity

    Weather events can drive rapid position changes:

    • Drought conditions
    • Excessive rainfall
    • Early/late frosts
    • Global weather patterns (El Niño/La Niña)
  4. Global Production Cycles

    Unlike financial markets, agricultural markets must account for different hemispheric growing seasons:

    • North American harvest vs. South American harvest
    • Northern vs. Southern Hemisphere production windows

Understanding Trader Categories in Agricultural Markets

Producer/Merchant/Processor/User

Who they are: Farmers, grain elevators, food companies, feed manufacturers

Trading behavior:

  • Producers typically hedge by selling futures (short)
  • Processors typically hedge by buying futures (long)
  • Net position often reflects current point in seasonal cycle

Interpretation keys:

  • Increasing short positions ahead of harvest indicates producer hedging
  • Increasing long positions indicates processor price risk management
  • Extreme positions relative to seasonal norms may signal price turning points

Swap Dealers in Agricultural Markets

Who they are: Banks and dealers who provide commodity index exposure to clients

Trading behavior:

  • Predominantly long-biased due to index composition
  • Position changes often reflect fund flows rather than price views
  • Less responsive to short-term price movements

Interpretation keys:

  • Significant position changes may reflect institutional money flows
  • Generally less predictive for short-term price movements
  • Important for understanding overall market structure

Managed Money in Agricultural Markets

Who they are: Commodity Trading Advisors (CTAs), hedge funds, commodity pools

Trading behavior:

  • Typically trend-following
  • Responsive to technical signals and fundamental data
  • More volatile position changes than other categories

Interpretation keys:

  • Extreme positions often signal potential market turning points
  • Rapid position changes may precede significant price movements
  • Divergences between positions and price can be powerful signals

Seasonal Patterns in Agricultural COT Data

Corn

  • January-March: Processors often increase long positions
  • April-June: Producer short hedging increases with planting progress
  • July-August: Weather markets drive speculative positioning
  • September-November: Peak producer short hedging during harvest
  • December: Year-end position squaring

Soybeans

  • February-April: South American harvest impacts positioning
  • May-July: U.S. growing season uncertainty drives speculative activity
  • August-October: Producer hedging increases ahead of U.S. harvest
  • November-January: Processor buying often increases post-harvest

Wheat

  • March-May: Winter wheat condition reports impact positioning
  • June-August: Northern Hemisphere harvest creates heavy commercial short positioning
  • September-October: Planting intentions for new crop influence positions
  • November-February: Southern Hemisphere harvest impacts

Cotton

  • February-April: Planting intentions drive positioning
  • May-July: Growing season uncertainties
  • August-October: Harvest hedging peaks
  • November-January: Mill buying often increases

Live Cattle

Demonstrates less pronounced seasonality than crops

  • Feedlot placement cycles influence commercial hedging patterns
  • Seasonal demand patterns (grilling season, holidays) affect processor hedging

Index Fund Impact on Agricultural Markets

Understanding Index Involvement

  • Commodity indices like the S&P GSCI and Bloomberg Commodity Index maintain significant agricultural exposure
  • Index funds maintain predominantly long positions with periodic rebalancing
  • The Supplemental COT Report specifically identifies index trader positions

Key Considerations

  • Index positions tend to be less responsive to short-term price movements
  • "Roll periods" when indices shift positions between contract months can create temporary price pressure
  • Index participation has grown significantly since early 2000s, altering traditional market dynamics

How to Use Index Data

  • Major changes in index positions may signal institutional asset allocation shifts
  • Divergences between index positioning and price can identify potential opportunities
  • Understanding index roll schedules helps anticipate potential market impacts

Case Studies: Major Agricultural Markets

Corn Market

Commercial Positioning: Typically net short, with seasonal variation

Key COT Signals:

  • Commercials reducing short positions during price declines often precedes rallies
  • Managed Money net position extremes frequently coincide with price turning points
  • Commercial vs. Managed Money position gaps widening signals potential reversals

Soybean Market

Commercial Positioning: Varies greatly with global supply dynamics

Key COT Signals:

  • South American harvest periods create unique positioning patterns
  • Processor long positions increasing can signal anticipated demand strength
  • Spread positions between soybeans and products (meal, oil) provide crush margin insights

Live Cattle Market

Commercial Positioning: Processors often net short, feedlots net long

Key COT Signals:

  • Pack
  • Packer short coverage often precedes price rallies
  • Extreme speculative long positions frequently signal potential tops
  • Divergences between feeder and live cattle positioning provide spread opportunities

Trading Strategies for Agricultural Markets

  1. Harvest Pressure Strategy

    Setup: Monitor producer short hedging building before/during harvest

    Entry: Look for commercial short position peaks coinciding with price lows

    Exit: When commercial shorts begin covering and prices stabilize

    Markets: Particularly effective in grains and cotton

  2. Weather Premium Fade

    Setup: Identify extreme speculative positions during weather scares

    Entry: When managed money reaches historical position extremes

    Exit: As weather concerns normalize and positions revert

    Markets: Particularly effective in growing-season grain markets

  3. Commercial Signal Strategy

    Setup: Track commercial position changes relative to price

    Entry: When commercials significantly reduce net short positions during price declines

    Exit: When commercials begin increasing short positions again as prices rise

    Markets: Works across most agricultural commodities

  4. Processor Demand Strategy

    Setup: Monitor processor long positions for signs of anticipated demand

    Entry: When processor longs increase significantly during price weakness

    Exit: When prices rise to reflect the improved demand outlook

    Markets: Particularly effective in processing crops like soybeans, cotton, and cattle

  5. Commercial/Speculator Divergence Strategy

    Setup: Identify growing gaps between commercial and speculative positioning

    Entry: When the gap reaches historical extremes

    Exit: When the gap begins to narrow and price confirms

    Markets: Applicable across all agricultural markets

Combining COT Data with Fundamental Analysis

USDA Reports

  • Compare COT positioning changes before and after major USDA reports
  • Look for confirmation or divergence between report data and position adjustments
  • Monitor commercial reaction to reports for insight into industry interpretation

Crop Progress and Condition

  • Weekly crop condition reports often drive speculative positioning
  • Commercial reaction to condition changes can provide valuable trading signals
  • Divergences between conditions and positioning may identify mispriced markets

Global Supply and Demand Factors

  • International crop production changes drive positioning in globally traded markets
  • Export sales reports influence commercial hedging activities
  • Currency movements impact relative positioning in internationally traded commodities

Integrating Seasonal Fundamentals

  • Compare current positioning to historical seasonal patterns
  • Identify when positions are abnormal for the current point in the season
  • Use seasonal tendencies to anticipate upcoming position changes

Common Pitfalls and How to Avoid Them

  1. Ignoring Seasonality

    Pitfall: Interpreting position levels without seasonal context

    Solution: Always compare current positions to historical seasonal norms

    Example: Producer short positions naturally increase during harvest, not necessarily bearish

  2. Overlooking Contract Roll Impacts

    Pitfall: Misinterpreting position changes during index roll periods

    Solution: Be aware of standard roll schedules for major indices

    Example: Apparent commercial selling during roll periods may be temporary technical flows

  3. Misunderstanding Report Categories

    Pitfall: Not recognizing the nuances between different COT report formats

    Solution: Use the Supplemental and Disaggregated reports for better clarity

    Example: Index fund positions in Legacy reports can distort true commercial hedger activity

  4. Reacting to Single-Week Changes

    Pitfall: Overemphasizing one week's position changes

    Solution: Focus on multi-week trends and significant position changes

    Example: Weather-driven temporary position adjustments vs. fundamental trend changes

  5. Neglecting Spread Positions

    Pitfall: Focusing only on outright positions, missing spread implications

    Solution: Monitor spreading activity, especially in related markets

    Example: Soybean/corn spread positions can provide insight into acreage competition

Resources for Agricultural COT Analysis

Specialized Data Services

  • AgResource Company: Provides COT analysis specific to agricultural markets
  • Hightower Report: Offers regular COT commentary for agricultural commodities
  • Brugler Marketing: Features agricultural-focused COT interpretation

Software Tools

  • Commodity Research Bureau (CRB): Offers historical COT data visualization for agricultural markets
  • DTN ProphetX: Includes agricultural COT analysis tools
  • AgriCharts: Provides specialized agricultural market data including COT information

Educational Resources

  • Agricultural Extension Services: Many offer educational materials on hedging and market analysis
  • CME Group: Provides educational content specific to agricultural markets
  • ICE Exchange: Offers resources for soft commodity trading and analysis

Government Resources

  • USDA ERS (Economic Research Service): Provides contextual market analysis
  • CFTC Agricultural Advisory Committee: Publishes recommendations and analysis
  • USDA AMS (Agricultural Marketing Service): Offers complementary market data

© 2025 - This guide is for educational purposes only and does not constitute financial advice. Agricultural markets involve significant risk, and positions should be managed according to individual risk tolerance and objectives.

Market Neutral (Overbought)
Based on the latest 13 weeks of non-commercial positioning data.
📊 COT Sentiment Analysis Guide

This guide helps traders understand how to interpret Commitments of Traders (COT) reports to generate potential Buy, Sell, or Neutral signals using market positioning data.

🧠 How It Works
  • Recent Trend Detection: Tracks net position and rate of change (ROC) over the last 13 weeks.
  • Overbought/Oversold Check: Compares current net positions to a 1-year range using percentiles.
  • Strength Confirmation: Validates if long or short positions are dominant enough for a signal.
✅ Signal Criteria
Condition Signal
Net ↑ for 13+ weeks AND ROC ↑ for 13+ weeks AND strong long dominance Buy
Net ↓ for 13+ weeks AND ROC ↓ for 13+ weeks AND strong short dominance Sell
Net in top 20% of 1-year range AND net uptrend ≥ 3 Neutral (Overbought)
Net in bottom 20% of 1-year range AND net downtrend ≥ 3 Neutral (Oversold)
None of the above conditions met Neutral
🧭 Trader Tips
  • Trend traders: Follow Buy/Sell signals when all trend and strength conditions align.
  • Contrarian traders: Use Neutral (Overbought/Oversold) flags to anticipate reversals.
  • Swing traders: Use sentiment as a filter to increase trade confidence.
Example:
Net positions rising, strong long dominance, in top 20% of historical range.
Result: Neutral (Overbought) — uptrend may be too crowded.
  • COT data is delayed (released on Friday, based on Tuesday's positions) - it's not real-time.
  • Combine with price action, FVG, liquidity, or technical indicators for best results.
  • Use percentile filters to avoid buying at extreme highs or selling at extreme lows.

Trading Strategy Based on COT Report for Cotton No. 2 (ICE Futures U.S.)

This trading strategy utilizes the Commitments of Traders (COT) report for Cotton No. 2 futures (ICUS) to identify potential trading opportunities for retail traders and market investors. It combines COT data with price action analysis and other technical indicators for confirmation.

I. Understanding the COT Report for Cotton No. 2:

The COT report details the positions held by different categories of traders in the Cotton No. 2 futures market. The key trader categories to focus on are:

  • Commercials (Hedgers): These are companies that produce or consume cotton, using futures to hedge against price fluctuations. Their primary motivation is not speculation. They are considered the "smart money" in the market.
  • Non-Commercials (Large Speculators): These are large managed money accounts, hedge funds, and other institutional investors who are primarily speculating on price movements.
  • Non-Reportable Positions (Small Speculators/Retail Traders): This category represents positions that are too small to be reported individually. Their aggregate behavior is often seen as following the trend rather than leading it.

Key Data Points to Analyze:

  • Net Position: The difference between long and short positions for each trader category. This indicates the overall directional bias.
  • Changes in Net Positions: The week-over-week change in the net positions for each category. This shows the changing sentiment.
  • Historical Context: Compare the current net positions to historical data (e.g., 1-year, 3-year, 5-year averages) to identify extreme levels.
  • Percentage of Open Interest: The percentage of the total open interest controlled by each trader category. This provides insight into their influence.

II. Trading Strategy Based on COT Analysis:

A. Core Strategy - Following the Smart Money (Commercials):

The fundamental principle is to align your trading direction with the "smart money" - the commercials.

  1. Identify Commercial Positioning:

    • Look for periods when Commercials have a historically large net short position (implying they expect prices to decline).
    • Look for periods when Commercials have a historically large net long position (implying they expect prices to rise).
    • Use a historical COT data chart to visually identify these extremes. Consider using standard deviations from the mean to define "extreme."

  2. Price Action Confirmation: Crucially important

    • Commercials Net Short (Bearish Scenario): Wait for price action confirmation of a downtrend. Look for:
      • Breakdown below key support levels.
      • Formation of lower highs and lower lows.
      • Bearish candlestick patterns (e.g., bearish engulfing, evening star).
    • Commercials Net Long (Bullish Scenario): Wait for price action confirmation of an uptrend. Look for:
      • Breakout above key resistance levels.
      • Formation of higher highs and higher lows.
      • Bullish candlestick patterns (e.g., bullish engulfing, morning star).

  3. Entry Trigger:

    • Enter a short position after the price confirms the downtrend in the bearish scenario. Consider using a pullback to a resistance level as an entry point.
    • Enter a long position after the price confirms the uptrend in the bullish scenario. Consider using a pullback to a support level as an entry point.

  4. Stop-Loss Placement:

    • Short Position: Place the stop-loss order above the recent swing high or above a significant resistance level.
    • Long Position: Place the stop-loss order below the recent swing low or below a significant support level.

  5. Profit Target:

    • Set a profit target based on technical analysis, such as Fibonacci extensions, previous swing highs/lows, or key support/resistance levels.
    • Consider a risk/reward ratio of at least 1:2.

  6. Money Management:

    • Risk no more than 1-2% of your trading capital on any single trade.
    • Adjust position size to account for the distance between entry and stop-loss.

B. Analyzing Non-Commercial Positioning:

While the commercials are the primary focus, the non-commercials can provide additional insights.

  1. Confirmation/Contradiction:

    • If Non-Commercials are positioned in the same direction as Commercials, it strengthens the signal.
    • If Non-Commercials are positioned in the opposite direction of Commercials, it creates a potential conflict and requires more caution. Consider reducing position size or waiting for stronger price action confirmation.

  2. Extreme Positioning:

    • Pay attention to periods when Non-Commercials have historically large net long or net short positions. These extreme levels can signal potential reversals, especially if Commercials are positioned in the opposite direction.

  3. Momentum Shifts:

    • Track the changes in Non-Commercial positions. A rapid shift in their net position can indicate a change in market sentiment.

C. Utilizing Other Technical Indicators:

Combine COT analysis with other technical indicators for further confirmation and to refine entry and exit points.

  • Moving Averages: Use moving averages (e.g., 50-day, 200-day) to identify the overall trend.
  • Relative Strength Index (RSI): Use RSI to identify overbought or oversold conditions.
  • Moving Average Convergence Divergence (MACD): Use MACD to identify potential trend changes.
  • Volume Analysis: Look for increasing volume during breakouts and downtrends to confirm the strength of the move.

III. Example Trade Scenario (Hypothetical):

  1. COT Report: The latest COT report shows that Commercials have a historically large net short position in Cotton No. 2 futures.
  2. Price Action: The price breaks below a key support level and forms a series of lower highs and lower lows. A bearish engulfing candlestick pattern appears.
  3. Confirmation: Non-Commercials are also net short, albeit less extreme than Commercials.
  4. Entry: Enter a short position on a pullback to a resistance level.
  5. Stop-Loss: Place the stop-loss order above the recent swing high.
  6. Profit Target: Set a profit target based on Fibonacci extensions.

IV. Risk Management and Considerations:

  • COT Reports are Lagging Indicators: The COT report is released with a delay (usually on Fridays for the previous Tuesday). Price action may have already started to reflect the changes in positioning.
  • Fundamental Analysis: Consider fundamental factors that can influence cotton prices, such as weather patterns, planting conditions, supply and demand data, and global economic conditions.
  • Market Volatility: Cotton prices can be volatile. Be prepared for price swings and adjust your position size accordingly.
  • Practice and Patience: COT-based trading requires patience and discipline. Practice on a demo account before risking real capital.
  • No Guarantee of Success: The COT report is a tool to help identify potential trading opportunities, but it does not guarantee success. Markets can be irrational and unpredictable.
  • Contract Roll: Pay attention to contract roll periods, where traders are shifting their positions to the next contract month. This can cause temporary distortions in price action.
  • Liquidity Cotton No. 2 is generally a liquid market but keep an eye on volumes to ensure sufficient liquidity for your trading size.

V. Disclaimer:

This is a general trading strategy based on COT report analysis for educational purposes only and should not be considered financial advice. Trading futures involves substantial risk of loss. You should carefully consider your investment objectives, risk tolerance, and financial situation before trading. Always conduct your own research and consult with a qualified financial advisor before making any investment decisions.