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

Canola (Non-Commercial)

13-Wk Max 126,425 109,686 25,613 27,984 83,403
13-Wk Min 44,665 36,356 -27,523 -32,801 -60,541
13-Wk Avg 88,705 61,018 1,803 -1,405 27,687
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 119,759 36,356 3,544 -1,371 83,403 6.26% 251,557
May 6, 2025 116,215 37,727 8,345 -853 78,488 13.27% 236,291
April 29, 2025 107,870 38,580 13,293 -8,163 69,290 44.86% 222,908
April 22, 2025 94,577 46,743 25,613 -1,369 47,834 129.40% 211,810
April 15, 2025 68,964 48,112 24,299 -28,773 20,852 164.72% 197,612
April 8, 2025 44,665 76,885 -4,639 -32,801 -32,220 46.64% 219,966
April 1, 2025 49,304 109,686 3,408 3,249 -60,382 0.26% 249,211
March 25, 2025 45,896 106,437 -16,124 19,387 -60,541 -141.87% 245,713
March 18, 2025 62,020 87,050 -24,864 27,984 -25,030 -189.98% 238,784
March 11, 2025 86,884 59,066 -27,523 5,620 27,818 -54.37% 239,565
March 4, 2025 114,407 53,446 -12,018 7,382 60,961 -24.14% 241,742
February 25, 2025 126,425 46,064 10,244 -1,019 80,361 16.30% 241,713
February 18, 2025 116,181 47,083 19,859 -7,534 69,098 65.68% 249,095

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for CANOLA AND PRODUCTS

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.

Canola Trading Strategy based on COT Report (Retail & Market Investor)

This strategy outlines a method for trading Canola Futures (ICE Futures U.S. - ICUS) using the Commitment of Traders (COT) report. It's designed for both retail traders with smaller accounts and market investors with larger portfolios.

I. Understanding the COT Report & Canola Dynamics:

A. Commitment of Traders (COT) Report Basics:

  • The COT report, released weekly by the CFTC (Commodity Futures Trading Commission), categorizes futures market participants into:
    • Commercials (Hedgers): Primarily processors and producers who use futures to hedge against price fluctuations of the physical commodity (e.g., canola processors, farmers). They are considered the informed group.
    • Non-Commercials (Large Speculators): Primarily hedge funds, managed money, and other large speculative investors. They trade for profit based on market trends and analysis.
    • Non-Reportable Positions (Small Speculators): Smaller traders whose positions are below the reporting threshold.
  • Key COT Report Data Points:
    • Net Position: The difference between long and short positions for each group. A positive net position indicates a net long bias, while a negative position indicates a net short bias.
    • Change in Net Position: The weekly change in the net position of each group, indicating a shift in sentiment.

B. Canola Market Specifics:

  • Supply & Demand Drivers:
    • Global Production: Major canola-producing regions include Canada, Australia, Europe, and China. Production reports from these regions are critical.
    • Weather: Adverse weather events (drought, excessive rain, frost) in key growing regions can significantly impact supply and prices.
    • Demand for Canola Oil & Meal: Canola oil is used in food production and biofuels. Canola meal is a protein-rich animal feed. Global demand for these products drives canola futures prices.
    • Currency Exchange Rates: Fluctuations in the Canadian dollar (CAD) relative to the US dollar (USD) can impact canola prices, as Canada is a major exporter.
    • Government Policies & Trade Agreements: Changes in agricultural policies or trade agreements can impact canola supply and demand.
  • Typical Trading Seasonality: Canola prices often exhibit seasonal patterns related to planting, growing, and harvesting cycles. Understanding these patterns can help with trade timing. (Generally harvest pressure in Fall)
  • Intermarket relationships: Observe correlations with soybean and other vegetable oil markets.

II. Trading Strategy:

A. Core Strategy - Commercials as Indicators:

  • Premise: Commercials (hedgers) are typically the most knowledgeable participants in the canola market. Their actions often precede significant price movements.
  • Signal Generation:
    1. Identify Extremes in Commercials' Net Position: Look for periods where commercials have reached historically high net short positions (expecting lower prices) or historically high net long positions (expecting higher prices).
    2. Confirm with Price Action: Wait for price action to confirm the signal. For example, if commercials are heavily net short, wait for a breakout above a resistance level or a change in trend to confirm a potential rally.
    3. Look for Divergences: Pay attention to instances where price is moving in one direction while the commercial traders positioning is moving the other way. This can be a sign of a possible upcoming reversal.
  • Entry & Exit Rules:
    • Long Entry: When commercials are heavily net long (or reducing net shorts) and price breaks above a resistance level or a trendline.
      • Stop-Loss: Place a stop-loss order below a recent swing low or a key support level.
      • Profit Target: Set a profit target based on technical analysis (e.g., Fibonacci extensions, previous highs) or a multiple of your risk (e.g., 2:1 or 3:1 risk-reward ratio).
    • Short Entry: When commercials are heavily net short (or reducing net longs) and price breaks below a support level or a trendline.
      • Stop-Loss: Place a stop-loss order above a recent swing high or a key resistance level.
      • Profit Target: Set a profit target based on technical analysis (e.g., Fibonacci retracements, previous lows) or a multiple of your risk (e.g., 2:1 or 3:1 risk-reward ratio).
  • Scaling & Position Sizing:
    • Retail Trader: Allocate a small percentage of your trading capital to each trade (e.g., 1-2%). Use a smaller contract size if necessary (e.g., Mini-Canola, if available, or consider options).
    • Market Investor: Allocate a larger percentage of your portfolio (e.g., 5-10%) to canola futures, but still maintain a diversified portfolio. Consider scaling into positions gradually to manage risk.

B. Supplementary Analysis:

  • Technical Analysis:
    • Trend Identification: Use trendlines, moving averages, and other technical indicators to identify the overall trend of the canola market. Trade in the direction of the prevailing trend.
    • Support & Resistance Levels: Identify key support and resistance levels to help determine entry and exit points.
    • Chart Patterns: Look for chart patterns (e.g., head and shoulders, double tops/bottoms) to confirm potential trend reversals.
  • Fundamental Analysis:
    • Monitor USDA Reports: Pay close attention to the USDA's (United States Department of Agriculture) Crop Production reports, WASDE (World Agricultural Supply and Demand Estimates) reports, and other agricultural publications.
    • Weather Monitoring: Track weather patterns in key canola-growing regions. Subscribe to weather services or follow agricultural meteorologists.
    • Global Demand Analysis: Stay informed about global demand for canola oil and meal, especially from major importing countries.
  • Intermarket Analysis: Monitor the prices of related agricultural commodities, such as soybeans, soybean oil, and wheat. Strong correlations can provide valuable insights.

III. Risk Management:

  • Stop-Loss Orders: Always use stop-loss orders to limit potential losses. Adjust your stop-loss orders as the trade progresses to lock in profits.
  • Position Sizing: Determine your position size based on your risk tolerance and account size. Never risk more than you can afford to lose.
  • Diversification: Don't put all your eggs in one basket. Diversify your portfolio across different asset classes and commodities.
  • Volatility Considerations: Canola futures can be volatile. Be prepared for price swings and adjust your position size accordingly.
  • Trading Psychology: Maintain a disciplined and unemotional approach to trading. Avoid chasing losses or getting overly confident after a winning trade.

IV. COT Report Interpretation Examples:

  • Example 1: Commercials Heavily Net Short, Price Consolidating
    • Situation: The COT report shows that commercials have a historically high net short position. The price of canola is consolidating within a range.
    • Interpretation: Commercials are anticipating lower prices. The consolidation suggests that the market is unsure.
    • Trading Action: Monitor the price action closely. If the price breaks below the bottom of the range, consider entering a short position with a stop-loss order above the top of the range.
  • Example 2: Commercials Heavily Net Long, Price Trending Up
    • Situation: The COT report shows that commercials have a historically high net long position. The price of canola is trending upward.
    • Interpretation: Commercials are anticipating higher prices. The uptrend confirms their bullish sentiment.
    • Trading Action: Consider entering a long position on a pullback with a stop-loss order below a recent swing low.

V. Tools and Resources:

  • CFTC Website: For accessing the COT reports (cftc.gov).
  • Trading Platform: A reliable trading platform with access to canola futures (ICE Futures U.S. - ICUS).
  • News & Information: Agricultural news websites, financial news outlets, and market commentary.
  • Charting Software: Software for technical analysis and charting (TradingView, MetaTrader).

VI. Important Considerations and Cautions:

  • Lagging Indicator: The COT report is a lagging indicator. It reflects past positioning and doesn't guarantee future price movements.
  • Market Complexity: The canola market is influenced by many factors. Don't rely solely on the COT report.
  • Data Revisions: The CFTC can revise the COT report data, so it's essential to use the most up-to-date information.
  • Backtesting: Before implementing this strategy with real money, backtest it using historical data to evaluate its performance.
  • Continuous Learning: The market is constantly evolving. Stay informed, adapt your strategy, and continuously improve your trading skills.
  • Brokerage and Exchange Fees: Carefully review fees for trading futures.

VII. Conclusion:

This COT report-based strategy provides a framework for trading canola futures. By understanding the dynamics of the market, analyzing the COT report, and combining it with technical and fundamental analysis, traders can increase their chances of success. However, remember that trading futures involves significant risk, and no strategy can guarantee profits. Thorough risk management and continuous learning are essential for long-term success. Always consult a financial advisor before making investment decisions.