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Sell
Based on the latest 13 weeks of non-commercial positioning data. ℹ️

DRY WHEY (Non-Commercial)

13-Wk Max 295 934 63 81 -91
13-Wk Min 176 267 -94 -255 -686
13-Wk Avg 225 548 -1 -33 -322
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
July 2, 2024 176 334 0 14 -158 -9.72% 2,317
June 25, 2024 176 320 0 34 -144 -30.91% 2,280
June 18, 2024 176 286 0 19 -110 -20.88% 2,235
June 11, 2024 176 267 -94 -190 -91 51.34% 2,133
June 4, 2024 270 457 41 -19 -187 24.29% 2,776
May 28, 2024 229 476 0 42 -247 -20.49% 2,694
May 21, 2024 229 434 0 -168 -205 45.04% 2,672
May 14, 2024 229 602 0 42 -373 -12.69% 2,678
May 7, 2024 229 560 -66 -255 -331 36.35% 2,650
April 30, 2024 295 815 43 81 -520 -7.88% 3,261
April 23, 2024 252 734 0 0 -482 26.52% 3,188
April 2, 2024 278 934 63 33 -656 4.37% 3,490
March 26, 2024 215 901 0 0 -686 17.94% 3,400

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 Sell
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 craft a comprehensive trading strategy based on the Commitments of Traders (COT) report for Cheese contracts traded on the Chicago Mercantile Exchange (CME), focusing on the needs of a retail trader and market investor.

Important Disclaimer: Trading commodity futures is inherently risky and not suitable for all investors. This strategy is for educational purposes only and should not be considered financial advice. Always conduct thorough research, understand your risk tolerance, and consult with a qualified financial advisor before making any trading decisions. Past performance is not indicative of future results.

I. Understanding the Cheese Market and COT Data

  • The Commodity: We're dealing with Cheese (Specifically, contracts based on 44,000 lbs). Price is influenced by milk production, domestic demand, exports, inventories, and global dairy markets.
  • The Contract: Pay attention to the contract specifications (CME). The contract size of 44,000 lbs. is a significant factor in determining position sizing and margin requirements.
  • The Exchange: The CME (Chicago Mercantile Exchange) is the primary market for these futures.
  • The COT Report:
    • Purpose: The COT report, released weekly by the CFTC (Commodity Futures Trading Commission), shows the positions held by different groups of traders in the futures market.
    • Key Categories:
      • Commercials (Hedgers): These are entities directly involved in the production, processing, or use of Cheese (e.g., cheese manufacturers, distributors). They use futures to hedge against price fluctuations. Generally considered the "smart money."
      • Non-Commercials (Large Speculators): These are large hedge funds, commodity trading advisors (CTAs), and other institutional investors who trade for profit.
      • Non-Reportable Positions (Small Speculators): These are smaller traders whose positions are below the reporting threshold. This category is often considered less informed.
    • Data Points:
      • Long Positions: Contracts bought to profit from rising prices.
      • Short Positions: Contracts sold to profit from falling prices.
      • Net Position: Long positions minus short positions. This is the most important figure.

II. Trading Strategy Based on the COT Report

This strategy focuses on identifying potential trend changes and confirming existing trends using COT data. It's a trend-following and contrarian approach combined.

A. Core Principles:

  1. Follow the Commercials (Hedgers): The general assumption is that Commercials have a better understanding of the fundamental supply and demand dynamics of the Cheese market because they are actively involved in the industry. Their positions are often a good indicator of where the price is likely to go.
  2. Watch for Extremes: Pay attention to when Commercials reach historically high net short positions (indicating a potential price bottom) or high net long positions (indicating a potential price top).
  3. Confirm with Price Action: The COT report is a sentiment indicator. It should be used in conjunction with price charts, technical analysis, and other fundamental data. Do not trade solely on the COT report.
  4. Manage Risk: Use appropriate stop-loss orders and position sizing to protect your capital.

B. Specific Trading Signals:

  • 1. Trend Confirmation (Following Commercials):

    • Uptrend Confirmation: If the Cheese price is in an uptrend (as determined by your technical analysis - moving averages, trendlines, etc.) AND Commercials are increasing their net long positions, this strengthens the bullish signal. Consider entering or adding to long positions.
    • Downtrend Confirmation: If the Cheese price is in a downtrend AND Commercials are increasing their net short positions, this strengthens the bearish signal. Consider entering or adding to short positions.

  • 2. Potential Trend Reversal (Contrarian Approach):

    • Potential Bottom: If the Cheese price has been falling AND Commercials reach historically high net short positions, this could indicate that the market is oversold and a bottom is near. Look for confirming bullish signals on the price chart (e.g., bullish candlestick patterns, breaks of downtrend lines). Consider taking partial profits on existing short positions or initiating small long positions. Be cautious! This is a contrarian signal and requires strong confirmation.
    • Potential Top: If the Cheese price has been rising AND Commercials reach historically high net long positions, this could indicate that the market is overbought and a top is near. Look for confirming bearish signals on the price chart (e.g., bearish candlestick patterns, breaks of uptrend lines). Consider taking partial profits on existing long positions or initiating small short positions. Be cautious! This is a contrarian signal and requires strong confirmation.
  1. Divergence: Observe the price of Cheese relative to the net position of Commercials, if price is making a new high but Commercials net position is declining than it's a sign for sell. If price is making a new low but Commercials net position is inclining than it's a sign for buy.

C. Step-by-Step Trading Process:

  1. Fundamental Analysis (Ongoing): Stay informed about the supply and demand factors affecting the Cheese market (e.g., milk production reports, export data, consumer demand).
  2. Technical Analysis (Daily): Analyze the Cheese price chart using your preferred technical indicators (e.g., moving averages, trendlines, RSI, MACD). Identify trends, support/resistance levels, and potential entry/exit points.
  3. COT Report Analysis (Weekly - after report release):
    • Download the latest COT report from the CFTC website.
    • Focus on the "Combined Futures and Options" report.
    • Track the net positions of Commercials (Hedgers) over time. Create a chart or spreadsheet to visualize the data.
    • Identify extreme levels (historically high/low net positions).
    • Look for confirmations or divergences with price action.
  4. Signal Generation: Based on your fundamental analysis, technical analysis, and COT report analysis, generate potential buy or sell signals.
  5. Entry: Enter a trade only if all your criteria are met (fundamental support, technical confirmation, AND COT report alignment).
  6. Stop-Loss: Place a stop-loss order to limit your potential losses. The placement of the stop-loss will depend on your risk tolerance and the volatility of the market, but generally, place it below a recent swing low (for long positions) or above a recent swing high (for short positions).
  7. Profit Target: Set a profit target based on your risk/reward ratio and technical analysis. Consider using support/resistance levels or Fibonacci extensions.
  8. Monitoring and Adjustment: Continuously monitor the market and your trade. Adjust your stop-loss and profit target as needed. Pay attention to new COT reports and any changes in the fundamental outlook.
  9. Exit: Exit the trade when your profit target is reached, your stop-loss is triggered, or when the market conditions change significantly.

III. Risk Management

  • Position Sizing: Never risk more than a small percentage (e.g., 1-2%) of your trading capital on any single trade. The large contract size of 44,000 lbs. means careful position sizing is critical.
  • Stop-Loss Orders: Always use stop-loss orders to limit your potential losses.
  • Diversification: Don't put all your eggs in one basket. Diversify your trading portfolio across different markets and asset classes.
  • Margin Requirements: Understand the margin requirements for trading Cheese futures and ensure you have sufficient capital in your account. Margin calls can be devastating.

IV. Examples

  • Example 1: Potential Bottom
    • The price of Cheese has been in a downtrend for several weeks.
    • Commercials have reached historically high net short positions.
    • You see a bullish engulfing candlestick pattern forming on the price chart near a key support level.
    • Action: This confluence of factors suggests a potential bottom. Consider initiating a small long position with a stop-loss order placed below the recent swing low.
  • Example 2: Trend Confirmation
    • The price of Cheese has broken above a long-term downtrend line, indicating a potential trend reversal.
    • The 50-day moving average has crossed above the 200-day moving average (a bullish signal).
    • The latest COT report shows that Commercials have started to increase their net long positions.
    • Action: This confluence of factors confirms the uptrend. Consider entering a long position with a stop-loss order placed below a recent swing low or below the 50-day moving average.

V. Data Sources

  • CFTC (Commodity Futures Trading Commission): www.cftc.gov (for COT reports)
  • CME Group: www.cmegroup.com (for contract specifications, market data)
  • Dairy Market News (USDA): https://www.ams.usda.gov/market-news/dairy (for fundamental news and analysis)
  • Trading Platforms: Reputable trading platforms that offer futures trading and COT report data integration.

VI. Important Considerations

  • Lagging Indicator: The COT report is released with a delay (usually on Fridays for the previous Tuesday's data). Market conditions can change significantly in the interim.
  • Interpretation: Interpreting COT data is not an exact science. It requires experience and judgment.
  • Market Volatility: The Cheese market can be volatile. Be prepared for price swings and unexpected events.
  • Leverage: Futures trading involves leverage, which can magnify both profits and losses. Use leverage prudently.
  • Broker Selection: Choose a reputable broker with experience in commodity futures trading and competitive commission rates.
  • Continuous Learning: The market is constantly evolving. Stay up-to-date on the latest news, trends, and trading techniques.

VII. Conclusion

This COT-based trading strategy for Cheese futures provides a framework for retail traders and market investors to identify potential trading opportunities. By combining COT data with fundamental and technical analysis, and by managing risk effectively, you can improve your chances of success in the Cheese market. Remember to continuously learn and adapt your strategy as market conditions change. Good luck!