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

MINI SOYBEANS (Non-Commercial)

13-Wk Max 18,519 1,546 1,830 685 17,898
13-Wk Min 12,662 375 -1,406 -656 12,287
13-Wk Avg 15,354 1,029 158 -62 14,325
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
October 15, 2024 18,519 621 319 -439 17,898 4.42% 23,424
October 8, 2024 18,200 1,060 0 0 17,140 22.17% 22,338
September 24, 2024 14,884 854 0 0 14,030 -3.97% 18,571
September 26, 2023 15,619 1,009 -397 -401 14,610 0.03% 19,585
September 19, 2023 16,016 1,410 -515 -136 14,606 -2.53% 21,645
September 12, 2023 16,531 1,546 174 41 14,985 0.90% 22,545
September 5, 2023 16,357 1,505 311 1 14,852 2.13% 22,586
August 29, 2023 16,046 1,504 1,830 278 14,542 11.95% 23,013
August 22, 2023 14,216 1,226 962 685 12,990 2.18% 21,934
August 15, 2023 13,254 541 592 166 12,713 3.47% 21,320
August 8, 2023 12,662 375 -286 -162 12,287 -1.00% 21,236
August 1, 2023 12,948 537 -1,406 -656 12,411 -5.70% 21,637
July 25, 2023 14,354 1,193 0 0 13,161 -37.33% 23,075

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
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.

Mini Soybean Trading Strategy Based on the CFTC Commitment of Traders (COT) Report

This strategy outlines how retail traders and market investors can utilize the CFTC Commitment of Traders (COT) report to inform their trading decisions in Mini Soybean futures contracts (Symbol: CBT) traded on the Chicago Board of Trade (CBOT). It emphasizes a blend of COT analysis with other technical and fundamental indicators for a more robust approach.

Understanding the COT Report

The COT report, released weekly by the CFTC, provides a breakdown of open interest in futures markets, categorizing traders into three primary groups:

  • Commercial Traders (Hedgers): Primarily processors and merchants who use futures contracts to hedge their underlying physical soybean business. Their primary goal is risk management, not speculation.
  • Non-Commercial Traders (Large Speculators): Hedge funds, managed money, and other large investors who trade primarily for profit.
  • Non-Reportable Traders (Small Speculators): Smaller traders who do not meet the reporting thresholds. Often assumed to behave in the opposite way to the large speculators.

Key COT Data Points to Monitor:

  • Net Position: The difference between the number of long and short contracts held by each group. This is the most crucial metric.
  • Changes in Net Positions: The week-over-week changes in net positions indicate the direction and intensity of each group's sentiment.
  • Open Interest: The total number of outstanding futures contracts. Increasing open interest generally validates a trend, while declining open interest can signal a potential reversal.
  • Percentage of Open Interest: The percentage of open interest held by each group relative to the total open interest. This provides a relative measure of their influence.

Strategy Overview:

This strategy aims to identify potential trading opportunities by analyzing the relationships between the various trader groups, particularly focusing on the Commercials (Hedgers) and Non-Commercials (Large Speculators).

Core Principles:

  • Follow the Hedgers: Commercial traders (Hedgers) generally have superior knowledge of supply and demand dynamics in the physical soybean market. Their actions often foreshadow future price movements.
  • Fade Extreme Sentiment: When Non-Commercials (Large Speculators) become excessively bullish or bearish, look for opportunities to fade their sentiment, aligning with the potential counter-moves by Commercials.
  • Confirm with Technical Analysis: Use technical indicators and chart patterns to validate COT-based signals and fine-tune entry and exit points.
  • Consider Fundamental Factors: Integrate fundamental analysis of soybean supply, demand, weather patterns, and global trade dynamics to provide a broader context for trading decisions.

Trading Rules:

  1. COT Data Analysis:

    • Identify Divergence: Look for divergences between the net positions of Commercials and Non-Commercials. For example:
      • Bullish Signal: Soybean prices are falling or consolidating, while Commercials are increasing their net long positions (or decreasing their net short positions), and Non-Commercials are increasing their net short positions (or decreasing their net long positions).
      • Bearish Signal: Soybean prices are rising or consolidating, while Commercials are increasing their net short positions (or decreasing their net long positions), and Non-Commercials are increasing their net long positions (or decreasing their net short positions).
    • Extreme Positioning: Identify when Non-Commercials reach extreme bullish or bearish net positions relative to their historical averages. This can signal a potential sentiment shift and a trend reversal. Consider a moving average (e.g., 52-week or 104-week) of the Non-Commercial net positions to identify such extremes.
    • Open Interest Confirmation: Confirm the COT signals with open interest. Increasing open interest during a confirmed divergence strengthens the signal. Decreasing open interest may weaken the signal or indicate a potential false alarm.

  2. Technical Analysis Confirmation:

    • Trend Identification: Determine the prevailing trend in soybean prices using moving averages (e.g., 50-day, 200-day) or trendlines. Trade in the direction of the overall trend, when possible.
    • Support and Resistance Levels: Identify key support and resistance levels using price action, Fibonacci retracements, or pivot points. Use these levels to define entry and exit points, as well as stop-loss orders.
    • Candlestick Patterns: Look for candlestick patterns (e.g., engulfing patterns, doji, hammer/hanging man) near support and resistance levels to confirm potential reversals or continuations.
    • Oscillators: Use oscillators like RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) to identify overbought or oversold conditions and potential momentum shifts.

  3. Fundamental Analysis Overlay:

    • Supply and Demand: Monitor USDA reports on soybean planting, yield forecasts, and ending stocks.
    • Weather: Track weather patterns in key soybean-growing regions (e.g., US Midwest, South America). Adverse weather can significantly impact supply.
    • Global Trade: Follow developments in global trade relations, particularly between the US and China, as they are major importers of soybeans.
    • Crush Margins: Consider soybean crush margins (the profitability of processing soybeans into meal and oil). Healthy crush margins can support soybean prices.

  4. Entry, Exit, and Risk Management:

    • Entry: Enter trades only when COT signals, technical analysis, and fundamental factors align. Look for confirmation from multiple sources.
    • Stop-Loss Orders: Place stop-loss orders below key support levels (for long positions) or above key resistance levels (for short positions) to limit potential losses. Consider using a percentage-based stop-loss (e.g., 1-2% of your trading capital).
    • Profit Targets: Set profit targets based on technical analysis (e.g., resistance levels, Fibonacci extensions) or risk-reward ratio. Aim for a risk-reward ratio of at least 1:2 or 1:3.
    • Position Sizing: Adjust your position size based on your risk tolerance and the volatility of the market. Never risk more than a small percentage (e.g., 1-2%) of your trading capital on any single trade.
    • Trailing Stops: Consider using trailing stops to lock in profits as the trade moves in your favor.

Example Trade Scenario (Bullish):

  • COT Signal: Soybean prices are declining, but Commercials are significantly reducing their net short positions, while Non-Commercials are building up their net short positions. This suggests that the smart money (Commercials) believes that soybeans are undervalued and are covering their short positions.
  • Technical Analysis: Soybean prices are approaching a key support level, and a bullish engulfing candlestick pattern forms. The RSI is oversold.
  • Fundamental Analysis: USDA reports indicate that soybean planting is behind schedule due to unfavorable weather.
  • Trade: Enter a long position near the support level with a stop-loss order placed below the support and a profit target based on the next resistance level.

Example Trade Scenario (Bearish):

  • COT Signal: Soybean prices are rising, but Commercials are significantly increasing their net short positions, while Non-Commercials are building up their net long positions. This suggests that the smart money (Commercials) believes that soybeans are overvalued and are increasing their short positions.
  • Technical Analysis: Soybean prices are approaching a key resistance level, and a bearish engulfing candlestick pattern forms. The RSI is overbought.
  • Fundamental Analysis: USDA reports indicate a bumper soybean crop is expected.
  • Trade: Enter a short position near the resistance level with a stop-loss order placed above the resistance and a profit target based on the next support level.

Important Considerations:

  • Lagging Indicator: The COT report is a lagging indicator. It reflects positions taken as of the previous Tuesday and released on Friday afternoon. Market conditions can change significantly in the intervening period.
  • Not a Holy Grail: The COT report should not be used in isolation. It is most effective when combined with technical and fundamental analysis.
  • Market Manipulation: While less common, large market participants could potentially attempt to manipulate the COT data. Be aware of this possibility.
  • Data Access: Ensure reliable access to the COT report. It is available on the CFTC website.
  • Paper Trading: Practice this strategy in a simulated trading environment (paper trading) before risking real capital.
  • Emotional Control: Maintain emotional discipline and avoid making impulsive decisions.
  • Continuous Learning: Stay updated on market trends, fundamental developments, and the effectiveness of your strategy. Adapt as needed.

Conclusion:

The COT report can be a valuable tool for Mini Soybean traders, providing insights into the positioning of different market participants. By combining COT analysis with technical and fundamental analysis, traders can develop a more informed and robust trading strategy. Remember to practice proper risk management techniques and continuously refine your approach.