Back to COT Dashboard
Market Sentiment
Neutral
Based on the latest 13 weeks of non-commercial positioning data. ℹ️

CHEESE (CASH-SETTLED) (Non-Commercial)

13-Wk Max 606 7,778 133 1,919 -2,328
13-Wk Min 409 2,934 -197 -2,080 -7,345
13-Wk Avg 470 5,918 -10 86 -5,448
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 497 3,953 79 -488 -3,456 14.09% 18,061
May 6, 2025 418 4,441 -67 -2,080 -4,023 33.35% 17,302
April 29, 2025 485 6,521 1 105 -6,036 -1.75% 20,091
April 22, 2025 484 6,416 8 -111 -5,932 1.97% 19,097
April 15, 2025 476 6,527 56 -71 -6,051 2.06% 18,774
April 8, 2025 420 6,598 -13 -1,180 -6,178 15.89% 18,415
April 1, 2025 433 7,778 -5 442 -7,345 -6.48% 20,657
March 25, 2025 438 7,336 -16 669 -6,898 -11.03% 20,395
March 18, 2025 454 6,667 7 438 -6,213 -7.45% 19,408
March 11, 2025 447 6,229 -95 -454 -5,782 5.85% 17,711
March 4, 2025 542 6,683 133 1,830 -6,141 -38.19% 19,989
February 25, 2025 409 4,853 -197 1,919 -4,444 -90.89% 17,105
February 18, 2025 606 2,934 -18 94 -2,328 -5.05% 15,228

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for CHEESE

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
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.

Okay, let's break down a comprehensive trading strategy for Cheese (Cash-Settled) using the Commitment of Traders (COT) report, tailored for both retail traders and market investors. This strategy will cover the key elements, risks, and considerations for using the COT report effectively in your trading decisions.

Disclaimer: Trading commodity futures is inherently risky, and this strategy is for educational purposes only. It is not financial advice, and you should consult with a qualified financial advisor before making any trading decisions. Past performance is not indicative of future results.

I. Understanding the Basics

  • What is the Cheese (Cash-Settled) Futures Contract?

    • It represents a contract to buy or sell 20,000 pounds of Cheddar cheese at a specified price on a specified future date. It is cash settled, meaning that there is no physical delivery of cheese.
    • It trades on the Chicago Mercantile Exchange (CME).
    • Its ticker symbol will be something like "DA" for Daily Cheese

  • What is the Commitment of Traders (COT) Report?

    • A weekly report published by the Commodity Futures Trading Commission (CFTC).
    • It provides a breakdown of the positions held by different categories of traders in the futures market.
    • The report is typically released every Friday, covering data up to the previous Tuesday.

  • Key Trader Categories in the COT Report (Legacy Report):

    • Commercials (Hedgers): Entities that use futures contracts to hedge their business risks (e.g., cheese producers, distributors, processors). They are considered the "smart money" in the sense that they have direct knowledge of the underlying physical cheese market.
    • Non-Commercials (Large Speculators): Large entities, often institutional investors (e.g., hedge funds, commodity trading advisors (CTAs)), that trade futures for profit.
    • Small Speculators (Retail): Smaller traders, often individuals, who trade futures for profit. Their positions are typically considered less informed than those of Commercials and Large Speculators.

II. Building a COT-Based Trading Strategy

Here's a step-by-step strategy using the COT report for Cheese futures:

A. Data Acquisition and Preparation:

  1. Obtain the COT Report: Download the "Legacy Report" or "Disaggregated Report" from the CFTC website. You can find them here: https://www.cftc.gov/MarketReports/CommitmentsofTraders/index.htm Choose the "Chicago Mercantile Exchange" and look for the "Cheese (Cash-Settled)" contract.
  2. Organize the Data: Create a spreadsheet (Excel, Google Sheets, etc.) and input the relevant data from the COT report:
    • Date of the report
    • Commercials: Long positions, Short positions, Net positions (Long - Short)
    • Non-Commercials: Long positions, Short positions, Net positions
    • Small Speculators: Long positions, Short positions, Net positions
  3. Calculate Key Indicators:
    • Commercial Net Position: This is the most important figure. A large net short position indicates that commercial hedgers are selling (expecting prices to decline), while a large net long position suggests they are buying (expecting prices to rise).
    • Non-Commercial Net Position: This represents the speculative sentiment of large traders.
    • Total Open Interest: This reflects the total number of outstanding Cheese futures contracts. Rising open interest generally confirms a trend, while declining open interest may suggest a weakening trend.
    • COT Index (Optional): Calculate a COT Index to normalize the net positions over a period of time (e.g., 52 weeks). This helps to identify overbought and oversold conditions. Formula:
      • COT Index = ((Current Net Position - Lowest Net Position over Period) / (Highest Net Position over Period - Lowest Net Position over Period)) * 100
      • A reading above 80 suggests an overbought condition, while a reading below 20 suggests an oversold condition.
  4. Chart the Data: Create charts of the Commercial Net Position, Non-Commercial Net Position, Open Interest, and (if calculated) the COT Index. Visualizing the data makes it easier to spot trends and divergences.

B. Analyzing the COT Data and Market Context:

  1. Identify Trends: Look for sustained trends in the Commercial Net Position. Is it trending significantly more long or short? A good start is to use Moving Averages to identify trend in commercial net positions
  2. Watch for Divergences: A divergence occurs when price moves in one direction, while the Commercial Net Position moves in the opposite direction.
    • Bullish Divergence: Price is making new lows, but the Commercial Net Position is becoming less short (or more long). This could signal a potential bottom.
    • Bearish Divergence: Price is making new highs, but the Commercial Net Position is becoming less long (or more short). This could signal a potential top.
  3. Consider Open Interest: Rising Open Interest with a rising price and increasing Commercial net short positions is generally bearish. Rising Open Interest with a rising price and increasing Commercial net long positions is generally bullish. Declining Open Interest often signals a weakening trend.
  4. Factor in Market Fundamentals: The COT report is most effective when combined with fundamental analysis of the cheese market. Consider factors such as:
    • Milk Production: Changes in milk production affect cheese supply.
    • Demand: Seasonal demand, consumer preferences, export markets, and restaurant trends all influence cheese demand.
    • Government Policies: Dairy subsidies and trade agreements can impact cheese prices.
    • Weather: Weather patterns can affect milk production.
  5. Consider Cash Market Prices: Keep an eye on cash cheese prices (e.g., block and barrel Cheddar) on the CME and in other key dairy markets. Futures prices will typically follow cash prices, but divergences can create trading opportunities.

C. Formulating Trading Signals:

Based on your analysis, develop specific entry and exit rules:

  • Basic Strategy (Following Commercials):
    • Buy Signal: When the Commercial Net Position is strongly net long and price action confirms a potential bottom (e.g., a bullish candlestick pattern).
    • Sell Signal: When the Commercial Net Position is strongly net short and price action confirms a potential top (e.g., a bearish candlestick pattern).
  • Divergence Strategy:
    • Buy Signal: Bullish divergence between price and Commercial Net Position, confirmed by price action.
    • Sell Signal: Bearish divergence between price and Commercial Net Position, confirmed by price action.
  • COT Index Strategy:
    • Buy Signal: COT Index falls below 20 (oversold), and price action confirms a potential bottom.
    • Sell Signal: COT Index rises above 80 (overbought), and price action confirms a potential top.

D. Risk Management:

  1. Position Sizing: Determine the appropriate position size based on your risk tolerance and account size. A general rule is to risk no more than 1-2% of your capital on any single trade.
  2. Stop-Loss Orders: Always use stop-loss orders to limit potential losses. Place stop-loss orders at logical levels based on technical analysis (e.g., below support levels, above resistance levels).
  3. Take-Profit Orders: Set take-profit orders to lock in profits. Place take-profit orders at logical levels based on technical analysis (e.g., at resistance levels, at Fibonacci retracement levels).
  4. Volatility: Cheese can be very volatile. Adjust position sizes and stop-loss orders accordingly.
  5. Market Liquidity: Ensure there is sufficient liquidity in the Cheese futures market before entering a trade. Low liquidity can lead to slippage.

E. Monitoring and Adjustment:

  1. Regularly Review the COT Report: Stay up-to-date with the latest COT reports and adjust your analysis and trading plan accordingly.
  2. Monitor Market Fundamentals: Keep track of changes in milk production, demand, and other fundamental factors that can impact cheese prices.
  3. Adjust Stop-Loss Orders: As the trade progresses, consider adjusting your stop-loss orders to protect profits (e.g., by trailing your stop-loss order).
  4. Be Flexible: The market can change quickly. Be prepared to adjust your trading plan if the market conditions change.

III. Key Considerations for Retail Traders and Market Investors

  • Retail Traders:

    • Start Small: Begin with a small position size to limit risk while you learn.
    • Focus on Education: Educate yourself about the Cheese futures market, the COT report, and technical analysis.
    • Use Demo Accounts: Practice your trading strategy using a demo account before trading with real money.
    • Be Patient: Trading takes time and patience. Don't expect to get rich quick.

  • Market Investors:

    • Long-Term Perspective: Use the COT report to identify long-term trends in the cheese market.
    • Diversification: Diversify your portfolio across different asset classes to reduce risk.
    • Consider Managed Futures: If you don't have the time or expertise to trade Cheese futures directly, consider investing in a managed futures fund that specializes in commodity trading.

IV. Specific Tips for Cheese (Cash-Settled) Futures

  • Seasonality: Cheese prices often exhibit seasonal patterns. Demand tends to be higher during holidays and certain times of the year.
  • CME Dairy Market: Pay attention to the other dairy futures contracts traded on the CME, such as milk and butter. These markets are interconnected.
  • News and Reports: Stay informed about news and reports related to the dairy industry, such as USDA reports on milk production and cheese inventories.

V. Risks and Limitations

  • Lagging Indicator: The COT report is a lagging indicator, meaning that it reflects past positions. It doesn't predict the future.
  • False Signals: The COT report can generate false signals. Not every divergence or extreme reading leads to a profitable trade.
  • Market Manipulation: Large traders can sometimes manipulate the market, which can affect the accuracy of the COT report.
  • Black Swan Events: Unexpected events (e.g., a major disease outbreak in dairy cattle) can disrupt the market and invalidate the COT report.
  • Cash Settlement Risk: Because the cheese market is cash settled, there is less incentive to use the contract to hedge and more incentive to speculate, which might affect the accuracy of the COT report.

VI. Example Scenario

Let's say the Commercial Net Position in Cheese futures has been steadily increasing over the past few months, indicating that commercial hedgers are becoming more bullish. At the same time, price has been consolidating. You then see a bullish candlestick pattern form on the chart. Based on this analysis, you might enter a long position with a stop-loss order placed below the recent low and a take-profit order placed at a potential resistance level. You would then monitor the COT report, market fundamentals, and price action to manage the trade.

VII. Conclusion

The COT report can be a valuable tool for trading Cheese (Cash-Settled) futures, but it's essential to use it in conjunction with other forms of analysis, such as technical and fundamental analysis. By understanding the positions of different trader categories and monitoring market fundamentals, you can develop a more informed trading strategy. Remember to manage your risk carefully and stay disciplined in your approach.