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

JET UP-DOWN BALMO (Non-Commercial)

13-Wk Max 195 555 0 0 195
13-Wk Min 0 0 0 0 -555
13-Wk Avg 65 228 0 0 -163
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
January 28, 2025 0 100 0 0 -100 0.00% 1,940
January 21, 2025 0 100 0 0 -100 72.97% 1,890
December 28, 2021 0 370 0 0 -370 0.00% 3,535
December 21, 2021 0 370 0 0 -370 33.33% 3,535
September 28, 2021 0 555 0 0 -555 0.00% 3,040
September 21, 2021 0 555 0 0 -555 -384.62% 3,040
February 25, 2020 195 0 0 0 195 0.00% 2,205
February 18, 2020 195 0 0 0 195 0.00% 2,155
February 11, 2020 195 0 0 0 195 0.00% 1,415

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for JET FUEL/HEATING 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 trading strategy utilizing the Commitments of Traders (COT) report for Jet Fuel/Heating Oil (specifically, the "JET UP-DOWN BALMO" contract on the NYMEX, representing balance-month trading). This strategy is geared towards retail traders and market investors.

Important Disclaimer: Trading futures involves significant risk. This is a hypothetical strategy for educational purposes and should not be interpreted as financial advice. Always do your own due diligence and consult with a qualified financial advisor before making any trading decisions. The COT report is a tool, but it's not a crystal ball. Market conditions, geopolitical events, and other factors can significantly impact prices.

I. Understanding the Jet Fuel/Heating Oil Market & the "JET UP-DOWN BALMO" Contract

  • Jet Fuel & Heating Oil Correlation: These two commodities are closely linked because they are derived from similar crude oil distillates. Seasonal demand patterns often impact them in tandem. Heating oil demand peaks in the winter, while jet fuel demand is generally steadier but can see spikes during holiday travel periods.
  • NYMEX "JET UP-DOWN BALMO": This likely refers to a balance-month swap contract. "Balance Month" usually represents the difference between the prompt month and the average of the subsequent months up to a certain point (e.g., the balance of the year). It can be a way to hedge against fluctuations across a longer time horizon, and it can trade separately from the front-month futures contract. Understanding its exact definition is crucial, and you should consult the exchange or a broker for clarification.
  • Key Market Drivers:
    • Crude Oil Prices: Jet fuel and heating oil are derivatives of crude oil, so crude oil price movements are the primary driver.
    • Refinery Production: Refinery capacity utilization and output levels significantly impact supply. Outages, maintenance, or regulatory changes can cause price spikes.
    • Inventories: Weekly inventory reports (from the EIA in the U.S.) are closely watched. Higher-than-expected inventories can put downward pressure on prices, and lower-than-expected inventories can support prices.
    • Weather: Cold winters boost heating oil demand. Weather events like hurricanes can disrupt production and distribution.
    • Geopolitical Events: Conflicts or political instability in oil-producing regions can create price volatility.
    • Economic Growth: Strong economic growth tends to increase demand for both jet fuel (for travel and commerce) and heating oil (for industrial purposes).
    • Seasonality: Heating Oil has strong seasonality in the winter, while Jet Fuel has moderate seasonality during peak holiday travel times.

II. The Commitments of Traders (COT) Report

  • What it is: The COT report is published weekly by the Commodity Futures Trading Commission (CFTC). It breaks down the open interest (outstanding contracts) in futures markets by the type of trader holding those positions.
  • Key Trader Categories:
    • Commercials (Hedgers): These are companies directly involved in the physical production, processing, or consumption of the commodity (e.g., airlines, refineries, heating oil distributors). They use futures to hedge price risk. They are generally considered the informed traders.
    • Non-Commercials (Large Speculators): These are large investment funds, hedge funds, and other speculative entities. They trade futures for profit.
    • Non-Reportable Positions (Small Speculators): This is the residual category, representing traders whose positions are too small to be individually reported.
  • Key Data Points:
    • Net Positions: The difference between long and short positions for each trader category. A positive net position means traders are net long (bullish), and a negative net position means they are net short (bearish).
    • Changes in Positions: The change in net positions from the previous reporting period. This indicates whether traders are increasing or decreasing their bullish or bearish bets.
  • Where to Find the COT Report: The CFTC website (cftc.gov). You can download the legacy, disaggregated, or TFF (Traders in Financial Futures) reports. For commodity markets, the disaggregated report is often the most useful.

III. Trading Strategy Based on COT Report

This strategy focuses on identifying potential trend changes by observing the behavior of Commercial traders, the perceived "smart money."

  • Core Principle: Follow the Commercials. Their hedging activity often reflects their expectations for future price movements based on their deep understanding of the physical market. We assume they are hedging the price risk appropriately.

  • Strategy Steps:

    1. Data Collection and Preparation:

      • Download the disaggregated COT report for NYMEX Heating Oil and NYMEX Jet Fuel weekly (both are needed for correlated insights).
      • Specifically extract the Net Positions for:
        • Commercials (Hedgers)
        • Non-Commercials (Large Speculators)
      • Track the historical price data for the "JET UP-DOWN BALMO" contract or a similar instrument. A heating oil/jet fuel spread might also be helpful.
      • Calculate the Net Commercial Position Change from week to week.
      • Consider using a spreadsheet (Excel, Google Sheets) or a charting platform to visualize the data.

    2. Identify Key Signal Events:

      • Commercial Net Position Extremes:
        • Extreme Net Short Position (Bearish Signal): When Commercials have a historically large net short position, it suggests they expect prices to decline. This may signal a potential shorting opportunity (or a time to reduce long positions). Look for positions that are at least 2 standard deviations from the mean of their historical net short position.
        • Extreme Net Long Position (Bullish Signal): When Commercials have a historically large net long position, it suggests they expect prices to rise. This may signal a potential longing opportunity (or a time to reduce short positions). Look for positions that are at least 2 standard deviations from the mean of their historical net long position.
      • Commercial Net Position Reversals (Confirmation is Key!):
        • Bullish Reversal: Commercials have been net short, but the Net Commercial Position Change shows a significant increase in their long positions (or a decrease in their short positions). This suggests a shift in their outlook.
        • Bearish Reversal: Commercials have been net long, but the Net Commercial Position Change shows a significant increase in their short positions (or a decrease in their long positions). This suggests a shift in their outlook.

    3. Confirmation Signals: Crucial! Do NOT rely solely on the COT report.

      • Price Action Confirmation:
        • Bullish Signal: Look for price to be moving up with increasing volume.
        • Bearish Signal: Look for price to be moving down with increasing volume.
      • Inventory Data: Check the EIA weekly inventory reports.
        • Bullish Signal: Lower-than-expected inventory draws that correlate with a bullish COT signal.
        • Bearish Signal: Higher-than-expected inventory builds that correlate with a bearish COT signal.
      • Seasonality: Consider the time of year. Is it near the peak of heating oil demand season (winter) or the peak of jet fuel demand (summer)?
      • Technical Analysis: Use indicators like moving averages, RSI, MACD, or trendlines to confirm potential entry and exit points.

    4. Entry and Exit Strategies:

      • Entry:
        • Long Entry (Bullish): After receiving a confirmed bullish COT signal (Commercials increasing longs/decreasing shorts + price action + inventory confirmation), enter a long position when price breaks above a recent resistance level or a moving average.
        • Short Entry (Bearish): After receiving a confirmed bearish COT signal (Commercials increasing shorts/decreasing longs + price action + inventory confirmation), enter a short position when price breaks below a recent support level or a moving average.
      • Exit:
        • Profit Target: Set a profit target based on a multiple of your risk (e.g., 2:1 or 3:1 reward-to-risk ratio). Use technical analysis to identify potential resistance/support levels as targets.
        • Stop-Loss: Place a stop-loss order just below a recent swing low (for long positions) or just above a recent swing high (for short positions). This protects you from unexpected price movements.

    5. Risk Management:

      • Position Sizing: Never risk more than 1-2% of your trading capital on any single trade. Calculate your position size based on the distance between your entry point and your stop-loss order.
      • Diversification: Don't put all your eggs in one basket. Trade other markets to reduce overall risk.
      • Hedging: If you have a physical exposure to heating oil or jet fuel, consider using futures contracts to hedge your price risk.
      • Leverage: Be very careful with leverage. Using too much leverage can amplify both your profits and your losses.

IV. Example Scenario:

Let's say the following happens:

  1. The COT report shows Commercials have a historically large net short position in heating oil futures.
  2. The price of heating oil starts to rise, breaking above a key resistance level.
  3. The EIA inventory report shows a surprise draw in heating oil stocks.
  4. You see a bullish candlestick pattern forming.

Based on this, you could consider entering a long position in the "JET UP-DOWN BALMO" contract, placing a stop-loss below the recent swing low and setting a profit target based on a predetermined risk/reward ratio.

V. Important Considerations and Refinements:

  • Lag Effect: The COT report is released with a lag (typically 3 days). The market may have already moved significantly by the time you see the data. This means that the COT data will provide you with a good overview, but it may not be timely enough to act upon with the same day's price action.
  • Context is Key: Don't interpret the COT report in isolation. Consider the overall market environment, economic news, and geopolitical events.
  • Seasonality Adjustments: Factor in seasonal demand patterns when interpreting Commercial hedging activity. Their hedging needs will change throughout the year.
  • Trend Following vs. Contrarian: This strategy leans towards trend following (following the "smart money"). However, some traders use the COT report in a contrarian manner, betting against extreme positions. Be aware of both approaches.
  • Volatility: Adjust your position size and stop-loss levels based on market volatility.
  • Backtesting: If possible, backtest your strategy using historical data to assess its performance.
  • Continuous Monitoring: Regularly review your strategy and adjust it as needed based on market conditions and your own trading experience.
  • Beware of False Signals: The COT report is not foolproof. False signals can occur. Always use confirmation signals and sound risk management.
  • Spread Trading: Consider trading the spread between heating oil and crude oil futures. This can reduce volatility and provide opportunities based on refining margins.
  • Combine with Order Flow Analysis: Using tools to see the real-time buying and selling pressure in the market can add another layer of confirmation.

VI. Conclusion:

The COT report can be a valuable tool for understanding market sentiment and potential trend changes in the Jet Fuel/Heating Oil market. By focusing on the activity of Commercial traders and using confirmation signals, retail traders and market investors can develop a more informed and disciplined trading strategy. However, it is crucial to remember that the COT report is just one piece of the puzzle. Sound risk management, continuous learning, and adapting to changing market conditions are essential for long-term success.

Remember: This is a starting point. Refine this strategy based on your own research, risk tolerance, and trading style. Good luck!