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

MINI EUR 3.5%FOIL RTD CAL (Non-Commercial)

13-Wk Max 195 1,499 70 248 -533
13-Wk Min 33 618 -162 -358 -1,304
13-Wk Avg 75 937 -4 -54 -862
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
September 3, 2019 85 618 -20 -62 -533 7.30% 2,589
August 27, 2019 105 680 0 0 -575 8.00% 2,393
July 30, 2019 60 685 0 -26 -625 3.99% 2,890
July 23, 2019 60 711 0 -2 -651 0.31% 2,884
July 16, 2019 60 713 0 6 -653 -0.93% 2,760
July 9, 2019 60 707 0 0 -647 19.43% 2,772
June 25, 2019 61 864 28 16 -803 1.47% 3,470
June 18, 2019 33 848 0 -299 -815 26.84% 3,240
June 11, 2019 33 1,147 0 6 -1,114 -0.54% 3,142
June 4, 2019 33 1,141 -162 -358 -1,108 15.03% 3,058
May 28, 2019 195 1,499 70 248 -1,304 -15.81% 3,831
May 21, 2019 125 1,251 58 -66 -1,126 9.92% 3,595
May 14, 2019 67 1,317 -16 -53 -1,250 2.87% 3,617

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for FUEL OIL

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 craft a comprehensive trading strategy based on the Commitment of Traders (COT) report for the MINI EUR 3.5% Fuel Oil RTD CAL contract, geared toward both retail traders and market investors. This will cover understanding the report, developing a strategy, and risk management.

Important Disclaimer: Trading commodity futures and options involves substantial risk of loss and is not suitable for everyone. This information is for educational purposes only and should not be considered investment advice. Always conduct thorough research and consult with a qualified financial advisor before making any trading decisions.

1. Understanding the COT Report for MINI EUR 3.5% FUEL OIL RTD CAL (NYME)

  • What is the COT Report? The Commitment of Traders (COT) report is released weekly by the CFTC (Commodity Futures Trading Commission). It provides a breakdown of open interest in futures markets, categorized by different types of traders.

  • Key Trader Categories (Relevant for Our Strategy):

    • Commercial Traders (Hedgers): These are entities who use the futures market to hedge their exposure to the underlying commodity (fuel oil). They are typically involved in the production, processing, or consumption of the commodity. Their primary goal is risk management, not speculation.
    • Non-Commercial Traders (Large Speculators): These are large entities, such as hedge funds and institutional investors, who trade futures for profit. They are speculators who take directional positions based on their market outlook.
    • Non-Reportable Positions (Small Speculators): This category represents the combined positions of traders who hold positions below the reporting threshold set by the CFTC. This is often assumed to be retail traders.

  • Key Data Points to Monitor:

    • Net Position: Calculated as Long Positions minus Short Positions for each category. This is the most crucial data point. A positive net position indicates the group is overall bullish, while a negative net position indicates a bearish outlook.
    • Changes in Net Positions: The week-over-week or month-over-month change in the net position. This tells you whether a group is becoming more bullish or bearish.
    • Open Interest: The total number of outstanding futures contracts. This provides a measure of overall market participation and liquidity. Increasing open interest during a price uptrend can confirm the trend's strength.

2. Data Acquisition

  • Go to the CFTC website (https://www.cftc.gov/)
  • Find the "Commitments of Traders" section.
  • Select the "Short Format" report.
  • Find the "MINI EUR 3.5%FOIL RTD CAL - NEW YORK MERCANTILE EXCHANGE" section within the report.
  • Download historical data if needed for backtesting. Many charting platforms and financial data providers also offer COT data.
  • The report is usually released every Friday after market close, reflecting data from the previous Tuesday.

3. Core Trading Strategy Based on the COT Report

The foundation of this strategy is to analyze how Commercial Traders and Non-Commercial Traders are positioning themselves and attempt to align with them. The assumption is that the commercial hedgers (fuel oil producers/consumers) have better insight into the fundamentals.

  • Strategy Name: COT Fuel Oil Trend Following (Hybrid)

  • Core Principle: Combine COT analysis with price action to identify high-probability trading opportunities.

  • Steps:

    1. Identify Trends in Commercial Traders (Hedgers):

      • Bullish Signal: Commercials decreasing their net short position (covering shorts) or increasing their net long position. This suggests they anticipate higher prices and are reducing their hedging exposure.
      • Bearish Signal: Commercials increasing their net short position (adding shorts) or decreasing their net long position. This suggests they anticipate lower prices and are increasing their hedging exposure.

    2. Confirm with Price Action:

      • Bullish Confirmation:

        • Commercials are becoming more bullish (as defined above).
        • The price of MINI EUR 3.5% Fuel Oil is in an uptrend (higher highs and higher lows).
        • Potential entry: A pullback to a support level (identified through technical analysis) within the uptrend.

      • Bearish Confirmation:

        • Commercials are becoming more bearish (as defined above).
        • The price of MINI EUR 3.5% Fuel Oil is in a downtrend (lower highs and lower lows).
        • Potential entry: A rally to a resistance level (identified through technical analysis) within the downtrend.

    3. Ignore or Trade Cautiously with Non-Reportable Positions

      • Non-Reportable (assumed retail) positions change can be disregarded or used cautiously. When the commercial positions are confirmed with an opposite change in non-reportable positions, the directional trade can be further strengthened.

4. Entry and Exit Strategy

  • Entry:

    • After identifying COT signals and price action confirmation.
    • Use a technical indicator (e.g., moving average, RSI, Stochastic) to time your entry more precisely. For example, wait for a pullback to a 50-day moving average in an uptrend, combined with a bullish reversal candlestick pattern.

  • Stop-Loss:

    • Place the stop-loss order below the most recent swing low for long positions or above the most recent swing high for short positions. Alternatively, use a fixed percentage or ATR (Average True Range) based stop-loss to control risk.

  • Take-Profit:

    • Set a target based on:
      • Technical Levels: Identify potential resistance levels (for longs) or support levels (for shorts) on the chart.
      • Risk/Reward Ratio: Aim for a minimum risk/reward ratio of 1:2 or 1:3 (i.e., potential profit is 2 or 3 times greater than your potential loss).
      • Trailing Stop:* Move the stop-loss order as the price moves in your favor, locking in profits.

5. Refinement and Additional considerations

  • Calendar Spreads: Consider using calendar spreads (buying a contract in one month and selling a contract in another month) to capitalize on anticipated changes in the forward curve of fuel oil. The COT report can inform views about which parts of the curve are likely to steepen or flatten.
  • Contango and Backwardation: Pay attention to the market structure (contango vs. backwardation). Contango (future prices higher than spot prices) typically encourages hedging by producers, while backwardation (future prices lower than spot prices) encourages consumption and discourages hedging.

6. Risk Management

  • Position Sizing: Never risk more than 1-2% of your trading capital on a single trade. Calculate your position size based on your stop-loss distance.
  • Diversification: Don't put all your eggs in one basket. Diversify your portfolio across different commodities and asset classes.
  • Capital Adequacy: Ensure you have sufficient capital to withstand potential losses. Futures trading requires margin, and margin calls can occur if the market moves against you.
  • Psychological Discipline: Stick to your trading plan, even when emotions run high. Avoid impulsive decisions based on fear or greed.
  • Market Events: Be aware of events that can impact fuel oil prices (e.g., OPEC meetings, geopolitical events, weather patterns, economic data releases). Adjust your positions accordingly or stay on the sidelines if necessary.
  • Volatility: Be aware that fuel oil is known to be volatile. Be sure that your position sizing and risk management will accommodate swings.

7. Backtesting and Optimization

  • Historical Data: Obtain historical COT data and price data for MINI EUR 3.5% Fuel Oil RTD CAL.
  • Backtesting Software: Use backtesting software (e.g., TradingView, MultiCharts) to simulate the performance of your strategy over different time periods.
  • Parameter Optimization: Experiment with different parameters (e.g., moving average periods, RSI levels, risk/reward ratios) to identify the settings that produce the best results.
  • Walk-Forward Optimization: Divide your data into training and testing sets. Optimize the parameters on the training set, then test the optimized strategy on the testing set. This helps to avoid overfitting.

8. Example Scenario:

  1. COT Data: The latest COT report shows that Commercial Traders have significantly reduced their net short positions in MINI EUR 3.5% Fuel Oil over the past few weeks.
  2. Price Action: The price of fuel oil is in a clear uptrend, with higher highs and higher lows.
  3. Technical Analysis: The price has recently pulled back to the 50-day moving average, which is acting as support. A bullish engulfing candlestick pattern forms at the support level.
  4. Entry: Enter a long position near the 50-day moving average, after confirmation.
  5. Stop-Loss: Place the stop-loss order below the most recent swing low (below the 50-day moving average).
  6. Take-Profit: Set a target based on a previous resistance level, or use a trailing stop-loss to capture potential profits as the uptrend continues.

9. Key Considerations for Retail vs. Market Investors:

  • Retail Traders:
    • Focus on shorter-term trades (days or weeks).
    • May use options strategies to limit risk and leverage capital.
    • Be more active in managing positions.
  • Market Investors:
    • May take a longer-term view (months or years).
    • May use futures to hedge existing fuel oil exposure or to express a long-term view on the market.
    • Less frequent adjustments to positions.

10. Continual Improvement

  • Track Your Performance: Keep a detailed trading journal to track your trades, including entry and exit prices, stop-loss levels, take-profit levels, and reasons for your decisions.
  • Analyze Your Results: Regularly review your trading journal to identify patterns and areas for improvement.
  • Adapt to Changing Market Conditions: The fuel oil market is constantly evolving. Be prepared to adapt your strategy as needed.

This detailed framework provides a starting point for developing a COT-based trading strategy for MINI EUR 3.5% Fuel Oil. Remember to always practice responsible risk management and continually refine your strategy based on your own experience and market analysis. Good luck!