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

Soybeans (Non-Commercial)

13-Wk Max 191,535 195,637 20,538 24,435 59,473
13-Wk Min 158,653 124,694 -11,757 -46,471 -34,283
13-Wk Avg 170,435 162,466 112 -2,051 7,969
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
April 29, 2025 184,167 124,694 -7,368 -11,157 59,473 6.80% 752,688
April 22, 2025 191,535 135,851 8,711 3,188 55,684 11.01% 813,041
April 15, 2025 182,824 132,663 20,538 -46,471 50,161 397.73% 815,871
April 8, 2025 162,286 179,134 3,633 16,969 -16,848 -379.73% 868,685
April 1, 2025 158,653 162,165 -3,060 -13,958 -3,512 75.63% 853,961
March 25, 2025 161,713 176,123 -5,610 523 -14,410 -74.10% 853,368
March 18, 2025 167,323 175,600 1,565 -2,298 -8,277 31.82% 830,437
March 11, 2025 165,758 177,898 4,404 -17,739 -12,140 64.59% 810,374
March 4, 2025 161,354 195,637 702 24,435 -34,283 -224.96% 813,417
February 25, 2025 160,652 171,202 -6,261 -1,353 -10,550 -86.99% 828,710
February 18, 2025 166,913 172,555 -3,449 8,974 -5,642 -183.20% 902,685
February 11, 2025 170,362 163,581 -11,757 18,628 6,781 -81.75% 904,578
February 4, 2025 182,119 144,953 -594 -6,409 37,166 18.55% 890,575

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for SOYBEANS

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 for Soybeans Based on the COT Report (Retail Traders & Market Investors)

This strategy utilizes the Commitment of Traders (COT) report to identify potential trading opportunities in soybeans traded on the Chicago Board of Trade (CBT). It's designed to be adaptable for both retail traders and market investors, considering their different risk tolerances and investment horizons.

Understanding the COT Report

The COT report provides a weekly breakdown of positions held by different participant categories in the futures market. For soybeans, the key categories are:

  • Commercials (Hedgers): These are companies involved in the production, processing, or merchandising of soybeans. They use futures contracts primarily to hedge their price risk.
  • Non-Commercials (Large Speculators): These are large traders, including hedge funds and commodity trading advisors (CTAs), who trade futures primarily for profit.
  • Non-Reportable (Small Speculators): This group represents individual retail traders and smaller speculative entities. Their positions are aggregated as the remaining percentage of open interest.

Key COT Data to Monitor:

  • Net Positions: This is the difference between the number of long (buying) and short (selling) contracts held by each category. It indicates their overall sentiment towards soybeans.
  • Changes in Net Positions: Monitoring the change in net positions from week to week reveals shifts in sentiment and potential trend changes.
  • Historical Context: Comparing current COT data to historical trends helps determine if current positions are unusually high or low, signaling potential overbought or oversold conditions.
  • Open Interest: The total number of outstanding soybean futures contracts. A rising open interest alongside increasing bullish positions can confirm an upward trend. Conversely, a falling open interest with increasing bearish positions can confirm a downward trend.

Trading Strategy Principles:

This strategy is based on the following principles:

  1. Follow the Commercials (Hedgers): Commercials are considered the most informed participants in the market as they have a direct vested interest in the underlying commodity. A consistent, strong trend in their net position can indicate a likely direction for the market.

  2. Monitor Non-Commercials (Large Speculators): Large speculators can amplify price movements, especially during trending markets. Their sentiment should align with the commercials to confirm a trade.

  3. Identify Extreme Positions: When either commercials or large speculators reach historically extreme net positions (either extremely long or extremely short), it may signal a potential reversal of the current trend.

  4. Use Technical Confirmation: Combine COT analysis with technical indicators (e.g., moving averages, trendlines, RSI, MACD) to confirm potential trade setups.

Trading Rules (Adaptable for Retail & Institutional):

1. Identifying a Bullish Setup:

  • Commercials: The net short position of commercials is decreasing (covering shorts), indicating that they are less concerned about downward price risk. Ideally, their net short position is at a historical low.
  • Non-Commercials: The net long position of non-commercials is increasing, confirming bullish sentiment. Ideally, their net long position should not be at historical highs, as this can indicate overbought conditions.
  • Technical Confirmation: Price breaks above a key resistance level, a moving average crossover (e.g., 50-day above 200-day), or a bullish candlestick pattern.
  • Entry: Enter a long position after technical confirmation, such as a breakout above resistance or a pullback to a support level after a breakout.
  • Stop-Loss: Place a stop-loss order below a recent swing low or support level to limit potential losses.
  • Target: Set a price target based on technical analysis, such as a Fibonacci extension level or a previous high.

2. Identifying a Bearish Setup:

  • Commercials: The net short position of commercials is increasing (adding shorts), indicating that they are more concerned about downward price risk. Ideally, their net short position is at a historical high.
  • Non-Commercials: The net long position of non-commercials is decreasing, confirming bearish sentiment. Ideally, their net short position should not be at historical highs, as this can indicate oversold conditions.
  • Technical Confirmation: Price breaks below a key support level, a moving average crossover (e.g., 50-day below 200-day), or a bearish candlestick pattern.
  • Entry: Enter a short position after technical confirmation, such as a breakdown below support or a rally to a resistance level after a breakdown.
  • Stop-Loss: Place a stop-loss order above a recent swing high or resistance level to limit potential losses.
  • Target: Set a price target based on technical analysis, such as a Fibonacci extension level or a previous low.

Risk Management & Position Sizing:

  • Risk Tolerance: Determine your risk tolerance before entering any trade. Risk only a small percentage (e.g., 1-2%) of your trading capital on each trade.
  • Position Sizing: Calculate the appropriate position size based on your risk tolerance and the distance between your entry point and stop-loss order.
  • Diversification: Don't put all your eggs in one basket. Diversify your portfolio across different asset classes and commodities.
  • Avoid Over-Leverage: Using excessive leverage can amplify both profits and losses. Retail traders should use conservative leverage levels.

Specific Strategies for Retail Traders:

  • Swing Trading: Retail traders can use this strategy for swing trading, holding positions for a few days to a few weeks. Focus on identifying short-term trends confirmed by the COT report and technical indicators.
  • Options Trading: Retail traders could also use options to limit the risk by buying options based on this data
  • Daily COT Analysis: Analyze the COT report on a daily basis to identify trends in large fund movements.

Specific Strategies for Market Investors:

  • Long-Term Positioning: Market investors can use the COT report to identify long-term trends in soybeans and adjust their portfolio allocations accordingly. They may consider investing in soybean ETFs or futures contracts with longer expiration dates.
  • Hedging Strategies: Market participants that use soybeans as raw material or food item can use the strategy to predict the soybean prices and hedge their positions.
  • Index Tracking: Market investors can use the COT report to gain valuable insight into the commodity market. It would aid in proper fund allocation

Example Trade Scenario (Bullish):

  1. COT Report: Commercials have been consistently covering their short positions over the past few weeks. Non-Commercials are increasing their long positions.
  2. Technical Analysis: Soybean prices break above a key resistance level at $12.50 per bushel.
  3. Entry: Enter a long position at $12.55.
  4. Stop-Loss: Place a stop-loss order below the recent swing low at $12.20.
  5. Target: Set a price target based on Fibonacci extensions at $13.00.

Important Considerations:

  • Lag Time: The COT report is released with a delay, so it's not a real-time indicator. Market conditions can change between the reporting date and the report's release.
  • Other Factors: The soybean market is influenced by various factors, including weather conditions, crop yields, global demand, government policies, and currency fluctuations. Consider these factors alongside the COT report.
  • False Signals: The COT report is not a perfect predictor of future price movements. False signals can occur, so always use risk management techniques.
  • Continuous Learning: Continuously monitor market conditions, refine your trading strategy, and learn from your successes and failures.
  • Backtesting: Before implementing this strategy with real money, thoroughly backtest it using historical data to assess its performance and identify potential weaknesses.
  • Paper Trading: Practice the strategy in a simulated trading environment (paper trading) before risking real capital.

Data Sources:

Disclaimer: This strategy is for educational purposes only and should not be considered financial advice. Trading in commodity futures involves substantial risk of loss. You should carefully consider your financial situation and risk tolerance before trading. Consult with a qualified financial advisor before making any investment decisions.