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

UP DOWN GC ULSD VS HO SPR (Non-Commercial)

13-Wk Max 2,244 2,989 895 105 2,244
13-Wk Min 0 0 -400 -1,209 -2,989
13-Wk Avg 1,063 582 73 -129 481
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 1,844 0 -400 0 1,844 -17.83% 38,614
May 6, 2025 2,244 0 895 -29 2,244 70.00% 37,215
April 29, 2025 1,349 29 205 29 1,320 15.38% 42,104
April 22, 2025 1,144 0 -230 0 1,144 -16.74% 38,783
April 15, 2025 1,374 0 255 0 1,374 22.79% 38,194
April 8, 2025 1,119 0 308 0 1,119 37.98% 33,599
April 1, 2025 811 0 -180 -105 811 -8.47% 39,350
March 25, 2025 991 105 -380 105 886 -35.38% 38,395
March 18, 2025 1,371 0 99 0 1,371 7.78% 33,508
March 11, 2025 1,272 0 0 0 1,272 196.66% 34,652
February 25, 2025 299 1,615 299 -1,209 -1,316 53.40% 39,716
February 18, 2025 0 2,824 0 -165 -2,824 5.52% 37,386
February 11, 2025 0 2,989 0 -169 -2,989 5.35% 34,725

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for HEATING OIL-DIESEL-GASOIL

Comprehensive Guide to COT Reports for Commodity Natural Resources Markets

1. Introduction to COT Reports

What are COT Reports?

The Commitments of Traders (COT) reports are weekly publications released by the U.S. Commodity Futures Trading Commission (CFTC) that show the positions of different types of traders in U.S. futures markets, including natural resources commodities such as oil, natural gas, gold, silver, and agricultural products.

Historical Context

COT reports have been published since the 1920s, but the modern format began in 1962. Over the decades, the reports have evolved to provide more detailed information about market participants and their positions.

Importance for Natural Resource Investors

COT reports are particularly valuable for natural resource investors and traders because they:

  • Provide transparency into who holds positions in commodity markets
  • Help identify potential price trends based on positioning changes
  • Show how different market participants are reacting to fundamental developments
  • Serve as a sentiment indicator for commodity markets

Publication Schedule

COT reports are released every Friday at 3:30 p.m. Eastern Time, showing positions as of the preceding Tuesday. During weeks with federal holidays, the release may be delayed until Monday.

2. Understanding COT Report Structure

Types of COT Reports

The CFTC publishes several types of reports:

  1. Legacy COT Report: The original format classifying traders as Commercial, Non-Commercial, and Non-Reportable.
  2. Disaggregated COT Report: Offers more detailed breakdowns, separating commercials into producers/merchants and swap dealers, and non-commercials into managed money and other reportables.
  3. Supplemental COT Report: Focuses on 13 select agricultural commodities with additional index trader classifications.
  4. Traders in Financial Futures (TFF): Covers financial futures markets.

For natural resource investors, the Disaggregated COT Report generally provides the most useful information.

Data Elements in COT Reports

Each report contains:

  • Open Interest: Total number of outstanding contracts for each commodity
  • Long and Short Positions: Broken down by trader category
  • Spreading: Positions held by traders who are both long and short in different contract months
  • Changes: Net changes from the previous reporting period
  • Percentages: Proportion of open interest held by each trader group
  • Number of Traders: Count of traders in each category

3. Trader Classifications

Legacy Report Classifications

  1. Commercial Traders ("Hedgers"):
    • Primary business involves the physical commodity
    • Use futures to hedge price risk
    • Include producers, processors, and merchants
    • Example: Oil companies hedging future production
  2. Non-Commercial Traders ("Speculators"):
    • Do not have business interests in the physical commodity
    • Trade for investment or speculative purposes
    • Include hedge funds, CTAs, and individual traders
    • Example: Hedge funds taking positions based on oil price forecasts
  3. Non-Reportable Positions ("Small Traders"):
    • Positions too small to meet reporting thresholds
    • Typically represent retail traders and smaller entities
    • Considered "noise traders" by some analysts

Disaggregated Report Classifications

  1. Producer/Merchant/Processor/User:
    • Entities that produce, process, pack, or handle the physical commodity
    • Use futures markets primarily for hedging
    • Example: Gold miners, oil producers, refineries
  2. Swap Dealers:
    • Entities dealing primarily in swaps for commodities
    • Hedging swap exposures with futures contracts
    • Often represent positions of institutional investors
  3. Money Managers:
    • Professional traders managing client assets
    • Include CPOs, CTAs, hedge funds
    • Primarily speculative motives
    • Often trend followers or momentum traders
  4. Other Reportables:
    • Reportable traders not in above categories
    • Example: Trading companies without physical operations
  5. Non-Reportable Positions:
    • Same as in the Legacy report
    • Small positions held by retail traders

Significance of Each Classification

Understanding the motivations and behaviors of each trader category helps interpret their position changes:

  • Producers/Merchants: React to supply/demand fundamentals and often trade counter-trend
  • Swap Dealers: Often reflect institutional flows and longer-term structural positions
  • Money Managers: Tend to be trend followers and can amplify price movements
  • Non-Reportables: Sometimes used as a contrarian indicator (small traders often wrong at extremes)

4. Key Natural Resource Commodities

Energy Commodities

  1. Crude Oil (WTI and Brent)
    • Reporting codes: CL (NYMEX), CB (ICE)
    • Key considerations: Seasonal patterns, refinery demand, geopolitical factors
    • Notable COT patterns: Producer hedging often increases after price rallies
  2. Natural Gas
    • Reporting code: NG (NYMEX)
    • Key considerations: Extreme seasonality, weather sensitivity, storage reports
    • Notable COT patterns: Commercials often build hedges before winter season
  3. Heating Oil and Gasoline
    • Reporting codes: HO, RB (NYMEX)
    • Key considerations: Seasonal demand patterns, refinery throughput
    • Notable COT patterns: Refiners adjust hedge positions around maintenance periods

Precious Metals

  1. Gold
    • Reporting code: GC (COMEX)
    • Key considerations: Inflation expectations, currency movements, central bank buying
    • Notable COT patterns: Commercial shorts often peak during price rallies
  2. Silver
    • Reporting code: SI (COMEX)
    • Key considerations: Industrial vs. investment demand, gold ratio
    • Notable COT patterns: More volatile positioning than gold, managed money swings
  3. Platinum and Palladium
    • Reporting codes: PL, PA (NYMEX)
    • Key considerations: Auto catalyst demand, supply constraints
    • Notable COT patterns: Smaller markets with potentially more concentrated positions

Base Metals

  1. Copper
    • Reporting code: HG (COMEX)
    • Key considerations: Global economic growth indicator, construction demand
    • Notable COT patterns: Producer hedging often increases during supply surpluses
  2. Aluminum, Nickel, Zinc (COMEX/LME)
    • Note: CFTC reports cover U.S. exchanges only
    • Key considerations: Manufacturing demand, energy costs for production
    • Notable COT patterns: Limited compared to LME positioning data

Agricultural Resources

  1. Lumber
    • Reporting code: LB (CME)
    • Key considerations: Housing starts, construction activity
    • Notable COT patterns: Producer hedging increases during price spikes
  2. Cotton
    • Reporting code: CT (ICE)
    • Key considerations: Global textile demand, seasonal growing patterns
    • Notable COT patterns: Merchant hedging follows harvest cycles

5. Reading and Interpreting COT Data

Key Metrics to Monitor

  1. Net Positions
    • Definition: Long positions minus short positions for each trader category
    • Calculation: Net Position = Long Positions - Short Positions
    • Significance: Shows overall directional bias of each group
  2. Position Changes
    • Definition: Week-over-week changes in positions
    • Calculation: Current Net Position - Previous Net Position
    • Significance: Identifies new money flows and sentiment shifts
  3. Concentration Ratios
    • Definition: Percentage of open interest held by largest traders
    • Significance: Indicates potential market dominance or vulnerability
  4. Commercial/Non-Commercial Ratio
    • Definition: Ratio of commercial to non-commercial positions
    • Calculation: Commercial Net Position / Non-Commercial Net Position
    • Significance: Highlights potential divergence between hedgers and speculators
  5. Historical Percentiles
    • Definition: Current positions compared to historical ranges
    • Calculation: Typically 1-3 year lookback periods
    • Significance: Identifies extreme positioning relative to history

Basic Interpretation Approaches

  1. Trend Following with Managed Money
    • Premise: Follow the trend of managed money positions
    • Implementation: Go long when managed money increases net long positions
    • Rationale: Managed money often drives momentum in commodity markets
  2. Commercial Hedging Analysis
    • Premise: Commercials are "smart money" with fundamental insight
    • Implementation: Look for divergences between price and commercial positioning
    • Rationale: Commercials often take counter-trend positions at market extremes
  3. Extreme Positioning Identification
    • Premise: Extreme positions often precede market reversals
    • Implementation: Identify when any group reaches historical extremes (90th+ percentile)
    • Rationale: Crowded trades must eventually unwind
  4. Divergence Analysis
    • Premise: Divergences between trader groups signal potential turning points
    • Implementation: Watch when commercials and managed money move in opposite directions
    • Rationale: Opposing forces creating potential market friction

Visual Analysis Examples

Typical patterns to watch for:

  1. Bull Market Setup:
    • Managed money net long positions increasing
    • Commercial short positions increasing (hedging against higher prices)
    • Price making higher highs and higher lows
  2. Bear Market Setup:
    • Managed money net short positions increasing
    • Commercial long positions increasing (hedging against lower prices)
    • Price making lower highs and lower lows
  3. Potential Reversal Pattern:
    • Price making new highs/lows
    • Position extremes across multiple trader categories
    • Changes in positioning not confirming price moves (divergence)

6. Using COT Reports in Trading Strategies

Fundamental Integration Strategies

  1. Supply/Demand Confirmation
    • Approach: Use COT data to confirm fundamental analysis
    • Implementation: Check if commercials' positions align with known supply/demand changes
    • Example: Increasing commercial shorts in natural gas despite falling inventories could signal hidden supply
  2. Commercial Hedging Cycle Analysis
    • Approach: Track seasonal hedging patterns of producers
    • Implementation: Create yearly overlay charts of producer positions
    • Example: Oil producers historically increase hedging in Q2, potentially pressuring prices
  3. Index Roll Impact Assessment
    • Approach: Monitor position changes during index fund roll periods
    • Implementation: Track swap dealer positions before/after rolls
    • Example: Energy contracts often see price pressure during standard roll periods

Technical Integration Strategies

  1. COT Confirmation of Technical Patterns
    • Approach: Use COT data to validate chart patterns
    • Implementation: Confirm breakouts with appropriate positioning changes
    • Example: Gold breakout with increasing managed money longs has higher probability
  2. COT-Based Support/Resistance Levels
    • Approach: Identify price levels where significant position changes occurred
    • Implementation: Mark price points of major position accumulation
    • Example: Price levels where commercials accumulated large positions often act as support
  3. Sentiment Extremes as Contrarian Signals
    • Approach: Use extreme positioning as contrarian indicators
    • Implementation: Enter counter-trend when positions reach historical extremes (90th+ percentile)
    • Example: Enter long gold when managed money short positioning reaches 95th percentile historically

Market-Specific Strategies

  1. Energy Market Strategies
    • Crude Oil: Monitor producer hedging relative to current term structure
    • Natural Gas: Analyze commercial positioning ahead of storage injection/withdrawal seasons
    • Refined Products: Track seasonal changes in dealer/refiner positioning
  2. Precious Metals Strategies
    • Gold: Monitor swap dealer positioning as proxy for institutional sentiment
    • Silver: Watch commercial/managed money ratio for potential squeeze setups
    • PGMs: Analyze producer hedging for supply insights
  3. Base Metals Strategies
    • Copper: Track managed money positioning relative to global growth metrics
    • Aluminum/Nickel: Monitor producer hedging for production cost signals

Strategy Implementation Framework

  1. Data Collection and Processing
    • Download weekly COT data from CFTC website
    • Calculate derived metrics (net positions, changes, ratios)
    • Normalize data using Z-scores or percentile ranks
  2. Signal Generation
    • Define position thresholds for each trader category
    • Establish change-rate triggers
    • Create composite indicators combining multiple COT signals
  3. Trade Setup
    • Entry rules based on COT signals
    • Position sizing based on signal strength
    • Risk management parameters
  4. Performance Tracking
    • Track hit rate of COT-based signals
    • Monitor lead/lag relationship between positions and price
    • Regularly recalibrate thresholds based on performance

7. Advanced COT Analysis Techniques

Statistical Analysis Methods

  1. Z-Score Analysis
    • Definition: Standardized measure of position extremes
    • Calculation: Z-score = (Current Net Position - Average Net Position) / Standard Deviation
    • Application: Identify positions that are statistically extreme
    • Example: Gold commercials with Z-score below -2.0 often mark potential bottoms
  2. Percentile Ranking
    • Definition: Position ranking relative to historical range
    • Calculation: Current position's percentile within 1-3 year history
    • Application: More robust than Z-scores for non-normal distributions
    • Example: Natural gas managed money in 90th+ percentile often precedes price reversals
  3. Rate-of-Change Analysis
    • Definition: Speed of position changes rather than absolute levels
    • Calculation: Weekly RoC = (Current Position - Previous Position) / Previous Position
    • Application: Identify unusual accumulation or liquidation
    • Example: Crude oil swap dealers increasing positions by >10% in a week often signals institutional flows

Multi-Market Analysis

  1. Intermarket COT Correlations
    • Approach: Analyze relationships between related commodity positions
    • Implementation: Create correlation matrices of trader positions across markets
    • Example: Gold/silver commercial positioning correlation breakdown can signal sector rotation
  2. Currency Impact Assessment
    • Approach: Analyze COT data in currency futures alongside commodities
    • Implementation: Track correlations between USD positioning and commodity positioning
    • Example: Extreme USD short positioning often coincides with commodity long positioning
  3. Cross-Asset Confirmation
    • Approach: Verify commodity COT signals with related equity or bond positioning
    • Implementation: Compare energy COT data with energy equity positioning
    • Example: Divergence between oil futures positioning and energy equity positioning can signal sector disconnects

Machine Learning Applications

  1. Pattern Recognition Models
    • Approach: Train models to identify historical COT patterns preceding price moves
    • Implementation: Use classification algorithms to categorize current positioning
    • Example: Random forest models predicting 4-week price direction based on COT features
  2. Clustering Analysis
    • Approach: Group historical COT data to identify common positioning regimes
    • Implementation: K-means clustering of multi-dimensional COT data
    • Example: Identifying whether current gold positioning resembles bull or bear market regimes
  3. Predictive Modeling
    • Approach: Create forecasting models for future price movements
    • Implementation: Regression models using COT variables as features
    • Example: LSTM networks predicting natural gas price volatility from COT positioning trends

Advanced Visualization Techniques

  1. COT Heat Maps
    • Description: Color-coded visualization of position extremes across markets
    • Application: Quickly identify markets with extreme positioning
    • Example: Heat map showing all commodity markets with positioning in 90th+ percentile
  2. Positioning Clock
    • Description: Circular visualization showing position cycle status
    • Application: Track position cycles within commodities
    • Example: Natural gas positioning clock showing seasonal accumulation patterns
  3. 3D Surface Charts
    • Description: Three-dimensional view of positions, price, and time
    • Application: Identify complex patterns not visible in 2D
    • Example: Surface chart showing commercial crude oil hedger response to price changes over time

8. Limitations and Considerations

Reporting Limitations

  1. Timing Delays
    • Issue: Data reflects positions as of Tuesday, released Friday
    • Impact: Significant market moves can occur between reporting and release
    • Mitigation: Combine with real-time market indicators
  2. Classification Ambiguities
    • Issue: Some traders could fit in multiple categories
    • Impact: Classification may not perfectly reflect true market structure
    • Mitigation: Focus on trends rather than absolute values
  3. Threshold Limitations
    • Issue: Only positions above reporting thresholds are included
    • Impact: Incomplete picture of market, especially for smaller commodities
    • Mitigation: Consider non-reportable positions as context

Interpretational Challenges

  1. Correlation vs. Causation
    • Issue: Position changes may reflect rather than cause price moves
    • Impact: Following positioning blindly can lead to false signals
    • Mitigation: Use COT as confirmation rather than primary signal
  2. Structural Market Changes
    • Issue: Market participant behavior evolves over time
    • Impact: Historical relationships may break down
    • Mitigation: Use adaptive lookback periods and recalibrate regularly
  3. Options Positions Not Included
    • Issue: Standard COT reports exclude options positions
    • Impact: Incomplete view of market exposure, especially for hedgers
    • Mitigation: Consider using COT-CIT Supplemental reports for context
  4. Exchange-Specific Coverage
    • Issue: Reports cover only U.S. exchanges
    • Impact: Incomplete picture for globally traded commodities
    • Mitigation: Consider parallel data from other exchanges where available

Common Misinterpretations

  1. Assuming Commercials Are Always Right
    • Misconception: Commercial positions always lead price
    • Reality: Commercials can be wrong on timing and magnitude
    • Better approach: Look for confirmation across multiple signals
  2. Ignoring Position Size Context
    • Misconception: Absolute position changes are what matter
    • Reality: Position changes relative to open interest provide better context
    • Better approach: Normalize position changes by total open interest
  3. Over-Relying on Historical Patterns
    • Misconception: Historical extremes will always work the same way
    • Reality: Market regimes change, affecting positioning impact
    • Better approach: Adjust expectations based on current volatility regime
  4. Neglecting Fundamental Context
    • Misconception: COT data is sufficient standalone
    • Reality: Positioning often responds to fundamental catalysts
    • Better approach: Integrate COT analysis with supply/demand factors

Integration into Trading Workflow

  1. Weekly Analysis Routine
    • Friday: Review new COT data upon release
    • Weekend: Comprehensive analysis and strategy adjustments
    • Monday: Implement new positions based on findings
  2. Framework for Position Decisions
    • Primary signal: Identify extremes in relevant trader categories
    • Confirmation: Check for divergences with price action
    • Context: Consider fundamental backdrop
    • Execution: Define entry, target, and stop parameters
  3. Documentation Process
    • Track all COT-based signals in trading journal
    • Record hit/miss rate and profitability
    • Note market conditions where signals work best/worst
  4. Continuous Improvement
    • Regular backtest of signal performance
    • Adjustment of thresholds based on market conditions
    • Integration of new data sources as available

Case Studies: Practical Applications

  1. Natural Gas Winter Strategy
    • Setup: Monitor commercial positioning ahead of withdrawal season
    • Signal: Commercial net long position > 70th percentile
    • Implementation: Long exposure with technical price confirmation
    • Historical performance: Positive expectancy during 2015-2023 period
  2. Gold Price Reversal Strategy
    • Setup: Watch for extreme managed money positioning
    • Signal: Managed money net short position > 85th percentile historically
    • Implementation: Contrarian long position with tiered entry
    • Risk management: Stop loss at recent swing point
  3. Crude Oil Price Collapse Warning System
    • Setup: Monitor producer hedging acceleration
    • Signal: Producer short positions increasing by >10% over 4 weeks
    • Implementation: Reduce long exposure or implement hedging strategies
    • Application: Successfully flagged risk periods in 2014, 2018, and 2022

By utilizing these resources and implementing the strategies outlined in this guide, natural resource investors and traders can gain valuable insights from COT data to enhance their market analysis and decision-making processes.

Market Neutral
Based on the latest 13 weeks of non-commercial positioning data.
📊 COT Sentiment Analysis Guide

This guide helps traders understand how to interpret Commitments of Traders (COT) reports to generate potential Buy, Sell, or Neutral signals using market positioning data.

🧠 How It Works
  • Recent Trend Detection: Tracks net position and rate of change (ROC) over the last 13 weeks.
  • Overbought/Oversold Check: Compares current net positions to a 1-year range using percentiles.
  • Strength Confirmation: Validates if long or short positions are dominant enough for a signal.
✅ Signal Criteria
Condition Signal
Net ↑ for 13+ weeks AND ROC ↑ for 13+ weeks AND strong long dominance Buy
Net ↓ for 13+ weeks AND ROC ↓ for 13+ weeks AND strong short dominance Sell
Net in top 20% of 1-year range AND net uptrend ≥ 3 Neutral (Overbought)
Net in bottom 20% of 1-year range AND net downtrend ≥ 3 Neutral (Oversold)
None of the above conditions met Neutral
🧭 Trader Tips
  • Trend traders: Follow Buy/Sell signals when all trend and strength conditions align.
  • Contrarian traders: Use Neutral (Overbought/Oversold) flags to anticipate reversals.
  • Swing traders: Use sentiment as a filter to increase trade confidence.
Example:
Net positions rising, strong long dominance, in top 20% of historical range.
Result: Neutral (Overbought) — uptrend may be too crowded.
  • COT data is delayed (released on Friday, based on Tuesday's positions) - it's not real-time.
  • Combine with price action, FVG, liquidity, or technical indicators for best results.
  • Use percentile filters to avoid buying at extreme highs or selling at extreme lows.

Okay, let's break down how a retail trader and market investor can use the Commitment of Traders (COT) report to inform their trading strategy for the Heating Oil (HO), Diesel (ULSD), and Gasoil (GC) spread on the New York Mercantile Exchange (NYME).

Understanding the Basics

  • Commodity: Heating Oil (HO), Ultra-Low Sulfur Diesel (ULSD), Gasoil (GC)
  • Contract Unit: 42,000 Gallons
  • Market: NYME (New York Mercantile Exchange)
  • Spread: UP DOWN GC ULSD VS HO SPR (This refers to a trading strategy that uses the relative price differences between Gasoil/ULSD and Heating Oil.)
  • COT Report: The Commitment of Traders report is a weekly publication by the CFTC (Commodity Futures Trading Commission) that provides a breakdown of open interest (outstanding contracts) in various futures markets. It categorizes traders into groups based on their trading activity.

Key Trader Categories in the COT Report

The COT report is generally split into two formats: Legacy and Disaggregated. For this spread strategy, the Disaggregated report is more useful. The Disaggregated report provides the following categories:

  • Producers/Merchants/Processors/Users (Commercials): These are entities directly involved in the production, processing, or physical use of the commodity. They typically use futures to hedge against price fluctuations in the physical market. These are often considered "informed" traders.
  • Swap Dealers: Entities that engage in swaps transactions and use the futures market to manage or hedge their risk associated with those swaps.
  • Managed Money: This category includes hedge funds, commodity trading advisors (CTAs), and other professional money managers who trade futures for speculative purposes.
  • Other Reportables: This is a residual category that includes all other reportable traders who are not classified in the above categories. Could include larger individual speculators, institutions, etc.
  • Nonreportable Positions: These are positions below the reporting threshold.

The "UP DOWN GC ULSD VS HO SPR" Strategy (Simplified)

Before diving into the COT report, let's clarify the core strategy. "UP DOWN GC ULSD VS HO SPR" implies betting on the price differential between Gasoil/ULSD and Heating Oil. You're essentially taking a position that one will outperform the other. Here's a simplified version:

  • "UP" (Long the Spread): You believe Gasoil/ULSD will increase in price more than Heating Oil, or that Gasoil/ULSD will increase in price while Heating Oil price decreases.
    • Action: Buy Gasoil/ULSD Futures AND Sell Heating Oil Futures.
  • "DOWN" (Short the Spread): You believe Gasoil/ULSD will decrease in price more than Heating Oil, or that Gasoil/ULSD will decrease in price while Heating Oil increases in price.
    • Action: Sell Gasoil/ULSD Futures AND Buy Heating Oil Futures.

Using the COT Report for the Spread Strategy

Here's a step-by-step approach for incorporating the COT report into your trading decisions:

  1. Obtain the COT Report: Download the Disaggregated COT report from the CFTC website (cftc.gov) or a reputable financial data provider. Look for the reports for the individual commodities, Heating Oil (HO), Ultra-Low Sulfur Diesel (ULSD), and Gasoil (GC).

  2. Analyze Commercial Trader Positions: This is arguably the most crucial step.

    • Heating Oil (HO): Pay close attention to the net position (longs - shorts) of the Commercial traders. A large net short position often suggests that commercials believe prices will fall, as they are locking in prices to sell their future production. A large net long position could suggest they anticipate prices will rise and are locking in purchases.
    • Gasoil/ULSD (GC/HO): Repeat the analysis for Gasoil/ULSD. A large net short position suggests commercials anticipate lower prices. A large net long position suggests they expect higher prices.

  3. Analyze Managed Money Positions:

    • Direction: Are they net long or net short in Heating Oil and Gasoil/ULSD? Their sentiment can provide clues, but remember they are often trend-following.
    • Extremes: Are their positions at historical highs or lows? Extremely long or short positions could indicate a potential overbought or oversold condition.

  4. Compare the Changes in Positions: Look at the change in positions from the previous week. This can provide insights into shifting sentiment. Are Commercials adding to their short positions, indicating increasing bearishness? Are Managed Money traders covering their shorts, suggesting a potential rally?

  5. Calculate the Spread Positions (Inferred): The COT report doesn't directly report on the spread position. You need to infer it. Here's the logic:

    • "Commercial Spread Position" (Approximation): Subtract the Commercial's net position in Heating Oil from the Commercial's net position in Gasoil/ULSD. This provides a (rough) estimate of how the Commercials are positioning themselves relative to the spread.
    • "Managed Money Spread Position" (Approximation): Subtract the Managed Money's net position in Heating Oil from the Managed Money's net position in Gasoil/ULSD.

  6. Interpret the Spread Positioning:

    • Example 1: Commercials Heavily Short Heating Oil, Relatively Neutral Gasoil/ULSD: This might suggest they believe Heating Oil is overvalued relative to Gasoil/ULSD, favoring a short spread position (betting on Heating Oil underperforming Gasoil/ULSD).
    • Example 2: Managed Money Heavily Long Gasoil/ULSD, Short Heating Oil: This could indicate speculative interest in the spread, potentially fueled by factors like seasonal demand (e.g., increased demand for Diesel during harvest season).

  7. Combine COT Analysis with Other Factors: The COT report is just one piece of the puzzle. Combine it with:

    • Technical Analysis: Use charts, trendlines, support/resistance levels, and indicators to identify potential entry and exit points.
    • Fundamental Analysis: Monitor supply and demand fundamentals (production levels, refinery outages, inventory data from the EIA (Energy Information Administration), geopolitical events, weather patterns, and economic indicators.
    • Seasonality: Heating Oil and Diesel have seasonal demand patterns (Heating Oil in winter, Diesel for agriculture and transportation).

Trading Strategy Examples (Based on COT & Other Factors)

Scenario 1: Commercials Increasing Short Positions in Heating Oil, Managed Money Long Gasoil/ULSD, Anticipated Cold Weather

  • COT Interpretation: Commercials bearish on Heating Oil (increasing short positions). Managed Money bullish on Gasoil/ULSD.
  • Fundamental Factor: Cold weather forecast (increasing Heating Oil demand, but maybe not as much as the market anticipates).
  • Technical Factor: Gasoil/ULSD showing bullish momentum on the charts.
  • Possible Trade: Go long the spread (Buy Gasoil/ULSD, Sell Heating Oil). You're betting that cold weather expectations are already priced into Heating Oil, and that Gasoil/ULSD will benefit more (or decline less) than Heating Oil if demand isn't as strong as expected or if supply disruptions occur for Gasoil/ULSD. Set a stop-loss based on technical levels.

Scenario 2: Commercials Covering Shorts in Gasoil/ULSD, Managed Money at Extreme Long, Refinery Outage

  • COT Interpretation: Commercials covering their shorts in Gasoil/ULSD (less bearish). Managed Money extremely long (potential for profit-taking).
  • Fundamental Factor: Refinery outage impacting Gasoil/ULSD production.
  • Technical Factor: Gasoil/ULSD overbought on the charts.
  • Possible Trade: Go short the spread (Sell Gasoil/ULSD, Buy Heating Oil). You're betting that the refinery outage is temporary, and that the overbought Gasoil/ULSD market is due for a correction. Place a stop-loss above recent highs.

Important Considerations for Retail Traders and Market Investors

  • Risk Management: Spread trading can still be risky. Use stop-loss orders to limit potential losses. Start with small positions and gradually increase size as you gain experience.
  • Margin Requirements: Understand the margin requirements for trading Heating Oil, Gasoil/ULSD, and the spread. Ensure you have sufficient capital in your account.
  • Transaction Costs: Factor in commissions and exchange fees. These costs can erode profits, especially for frequent traders.
  • Time Horizon: Define your trading horizon (day trading, swing trading, long-term investing). The COT report is generally more useful for swing trading and longer-term analysis.
  • Data Lags: The COT report is released with a lag. The data reflects positions as of the previous Tuesday. Market conditions can change significantly in the interim.
  • Correlation is Not Causation: The COT report shows positions, not intentions. Don't assume that Commercials are always right. They may have other factors influencing their hedging decisions.
  • Spread Specific Margin: Brokers often offer reduced margin requirements for spread positions. Make sure you confirm this with your broker.

Disclaimer:

This information is for educational purposes only and should not be considered financial advice. Trading futures involves substantial risk of loss. Consult with a qualified financial advisor before making any investment decisions.