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

Coffee (Non-Commercial)

13-Wk Max 75,658 15,655 8,190 2,049 61,698
13-Wk Min 50,370 10,116 -8,764 -5,219 39,934
13-Wk Avg 64,544 12,699 -1,670 -314 51,845
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 56,603 10,533 -2,991 280 46,070 -6.63% 154,524
May 6, 2025 59,594 10,253 189 137 49,341 0.11% 154,370
April 29, 2025 59,405 10,116 8,190 -43 49,289 20.05% 155,503
April 22, 2025 51,215 10,159 845 -277 41,056 2.81% 146,006
April 15, 2025 50,370 10,436 -8,764 -5,219 39,934 -8.15% 149,805
April 8, 2025 59,134 15,655 -8,535 2,049 43,479 -19.58% 172,826
April 1, 2025 67,669 13,606 -3,278 1,111 54,063 -7.51% 177,426
March 25, 2025 70,947 12,495 1,065 -1,257 58,452 4.14% 175,814
March 18, 2025 69,882 13,752 -938 -612 56,130 -0.58% 168,654
March 11, 2025 70,820 14,364 -2,218 163 56,456 -4.05% 165,950
March 4, 2025 73,038 14,201 -1,701 -1,355 58,837 -0.58% 162,373
February 25, 2025 74,739 15,556 -919 1,596 59,183 -4.08% 161,872
February 18, 2025 75,658 13,960 -2,652 -653 61,698 -3.14% 162,683

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for COFFEE

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 (Oversold)
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 for Coffee C Futures (ICUS) Based on the COT Report

This strategy aims to provide retail traders and market investors with a framework for trading Coffee C futures (ICUS) based on the Commitments of Traders (COT) report. The COT report provides a breakdown of open interest positions held by different market participants, offering valuable insights into market sentiment and potential future price movements.

I. Understanding the COT Report for Coffee C (ICUS)

  • Source: CFTC (Commodity Futures Trading Commission) releases the COT report every Friday, reflecting positions held as of the previous Tuesday.
  • Data to Analyze:
    • Commercial Hedgers (Producers, Merchants, Processors, Users): These entities use futures contracts to hedge against price risk related to their physical coffee business. Their positions often reflect their expectations about future supply and demand.
    • Non-Commercial Speculators (Managed Money, Large Reporting Traders): These are typically hedge funds, commodity trading advisors (CTAs), and other large investors who trade futures contracts for profit. Their positions often reflect their view on market trends.
    • Non-Reportable Positions (Small Traders): These are small traders whose positions are below the reporting threshold. Their collective positions are often seen as contrarian indicators.
  • Key Metrics:
    • Net Positions: The difference between long and short positions for each group. A positive net position indicates a bullish outlook, while a negative net position suggests a bearish outlook.
    • Changes in Positions: Analyzing how positions have changed over time provides insights into shifting sentiment. A significant increase in net long positions by speculators may signal a developing uptrend.
    • Extreme Readings: Look for unusually high or low net positions relative to historical data. Extreme readings may indicate overbought or oversold conditions, potentially leading to reversals.

II. Trading Strategy Framework

This strategy uses a combination of COT data analysis and technical analysis to identify potential trading opportunities.

A. Identifying Potential Market Trends Using COT Data

  1. Trend Confirmation:

    • Uptrend: Look for commercial hedgers decreasing their net short positions (reducing hedging pressure) while non-commercial speculators increase their net long positions (becoming more bullish). This suggests increasing demand and speculator interest in driving prices higher.
    • Downtrend: Look for commercial hedgers increasing their net short positions (increasing hedging pressure) while non-commercial speculators decrease their net long positions (becoming more bearish). This indicates increasing supply and speculator interest in driving prices lower.

  2. Trend Weakness/Reversal Signals:

    • Divergence: Observe if price continues to move in the direction of the trend but COT data shows a weakening trend. For example, price making higher highs but speculators reducing their net long positions could signal a potential trend reversal.
    • Extreme Positions: When non-commercial speculators reach extreme net long positions (relative to historical data), the market may be overbought and vulnerable to a correction. Conversely, extreme net short positions may indicate an oversold market ripe for a rebound.
    • Commercial Hedgers as Contrarian Indicators: Commercial hedgers are often right about long-term trends. If commercial hedgers are heavily short, it could indicate an overvalued market and a potential for future price declines. If they are heavily long, it could indicate an undervalued market and potential for future price increases.

B. Technical Analysis Confirmation

Use technical analysis to confirm signals identified through COT data analysis. This can help improve the accuracy of trade entries and exits.

  • Trend Lines: Identify uptrends and downtrends and use trendline breaks as potential entry or exit signals.
  • Support and Resistance Levels: Look for price action confirming support or resistance levels. Bounce from support with a positive COT alignment or break of resistance with a similar condition increases the signal confidence.
  • Moving Averages: Use moving averages (e.g., 50-day, 200-day) to identify the overall trend and potential areas of support and resistance.
  • Momentum Indicators: RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) can help identify overbought or oversold conditions and potential momentum shifts. Confirm signals generated by COT with these indicators.
  • Candlestick Patterns: Look for candlestick patterns like engulfing patterns, dojis, or hammer patterns that confirm the COT and technical signals.

C. Entry and Exit Strategies

  • Entry:
    • Long Entry: When the COT data signals an uptrend (Commercial Hedgers decreasing net shorts, Speculators increasing net longs), confirm with technical analysis (e.g., breakout above a resistance level, bullish candlestick pattern at support).
    • Short Entry: When the COT data signals a downtrend (Commercial Hedgers increasing net shorts, Speculators decreasing net longs), confirm with technical analysis (e.g., breakout below a support level, bearish candlestick pattern at resistance).
  • Exit:
    • Profit Target: Set profit targets based on technical analysis, such as previous highs/lows, Fibonacci extensions, or risk-reward ratios.
    • Stop-Loss: Place stop-loss orders below recent swing lows (for long positions) or above recent swing highs (for short positions) to limit potential losses. Adjust stop-loss as the trade progresses to lock in profits.
    • COT Signal Reversal: If the COT data starts to contradict the initial trend (e.g., Speculators decreasing long positions after an uptrend), consider exiting the trade.

III. Risk Management

  • Position Sizing: Never risk more than 1-2% of your trading capital on any single trade.
  • Stop-Loss Orders: Always use stop-loss orders to protect against unexpected price movements.
  • Leverage: Use leverage cautiously. Coffee futures can be volatile, and excessive leverage can amplify both gains and losses.
  • Diversification: Avoid concentrating your portfolio solely on Coffee futures. Diversify across different commodities or asset classes to reduce overall risk.

IV. Example Trade Scenario

  1. Observation: The COT report shows that over the past four weeks, non-commercial speculators have been significantly increasing their net long positions in Coffee C futures, while commercial hedgers have been decreasing their net short positions.
  2. Technical Analysis: The price of Coffee C has broken above a key resistance level at $1.60/lb and is trending upwards. The 50-day moving average is above the 200-day moving average, confirming the uptrend.
  3. Entry: Enter a long position at $1.61/lb, anticipating further upward movement.
  4. Stop-Loss: Place a stop-loss order below the recent swing low at $1.58/lb.
  5. Profit Target: Set a profit target at $1.70/lb, based on previous resistance levels.
  6. Monitoring: Continue to monitor the COT report and technical indicators. If the COT data begins to weaken (speculators reducing long positions), or if the price breaks below the 50-day moving average, consider reducing or exiting the position.

V. Considerations & Important Notes

  • Fundamental Analysis: While this strategy focuses on COT data and technical analysis, consider incorporating fundamental analysis (weather conditions, supply and demand factors, political events in coffee-producing regions) for a more comprehensive view.
  • Lagging Indicator: The COT report is a lagging indicator, meaning it reflects past positions and may not always accurately predict future price movements.
  • Market Volatility: Coffee futures are subject to significant price volatility. Be prepared for unexpected price swings.
  • Trading Experience: This strategy is intended for traders with some experience in futures trading and technical analysis.
  • Backtesting: Before implementing this strategy with real money, backtest it on historical data to assess its profitability and risk profile.
  • Continuous Learning: Continuously refine your trading strategy based on market conditions and your own experience. The market is always evolving, and staying informed is crucial for success.
  • Emotional Control: Stick to your trading plan and avoid making emotional decisions. Don't let fear or greed drive your trading.
  • Broker Choice: Choose a reputable broker with low commission fees, a reliable trading platform, and access to the necessary data and tools.

Disclaimer: Trading futures involves substantial risk of loss and is not suitable for all investors. This strategy is provided for informational purposes only and should not be construed as investment advice. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions.