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

GULF COAST UNL 87 GAS M2 PL RB (Non-Commercial)

13-Wk Max 0 0 0 0 0
13-Wk Min 0 0 0 0 0
13-Wk Avg 0 0 0 0 0
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
April 28, 2020 0 0 0 0 0 0.00% 12,384
March 31, 2020 0 0 0 0 0 0.00% 14,527
March 24, 2020 0 0 0 0 0 0.00% 12,639
February 25, 2020 0 0 0 0 0 0.00% 12,409
December 31, 2019 0 0 0 0 0 0.00% 13,634
December 24, 2019 0 0 0 0 0 0.00% 13,544
December 17, 2019 0 0 0 0 0 0.00% 12,648
December 10, 2019 0 0 0 0 0 0.00% 11,283
December 3, 2019 0 0 0 0 0 0.00% 10,379
November 26, 2019 0 0 0 0 0 0.00% 14,790
November 19, 2019 0 0 0 0 0 0.00% 14,389
November 12, 2019 0 0 0 0 0 0.00% 13,639
November 5, 2019 0 0 0 0 0 0.00% 11,989

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for GASOLINE

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 for retail traders and market investors using the Commitment of Traders (COT) report for GULF COAST UNL 87 GAS M2 PL RB traded on the New York Mercantile Exchange (NYME), keeping in mind that each contract represents 42,000 gallons.

Disclaimer: Trading commodity futures involves substantial risk of loss. This is for educational purposes only and not financial advice. Always consult with a qualified financial advisor before making trading decisions. The COT report is a snapshot in time and market dynamics can change quickly.

I. Understanding the COT Report for Gasoline (GULF COAST UNL 87 GAS M2 PL RB)

  • What is the COT Report? The COT report, published weekly by the CFTC (Commodity Futures Trading Commission), shows the aggregate positions held by different categories of traders in the futures market. It provides insights into the sentiment and positioning of large players.

  • Key Trader Categories:

    • Commercials (Hedgers): These are typically companies directly involved in the production, processing, or consumption of gasoline. They use futures to hedge against price fluctuations. Think of refiners, distributors, and large gas station chains. Their primary motive is not speculation but price risk management.
    • Non-Commercials (Large Speculators): These are large entities like hedge funds, managed money (CTAs - Commodity Trading Advisors), and other institutional investors who trade for profit. They are considered trend followers and price drivers.
    • Non-Reportable (Small Speculators): This category includes smaller traders whose positions are below the reporting threshold. They often follow trends but can also act as contrarian indicators.

  • Key Data Points in the COT Report:

    • Open Interest: The total number of outstanding contracts (both long and short). A rising open interest generally suggests more money is flowing into the market. Decreasing open interest can signal a weakening trend.
    • Long Positions: The number of contracts held buying market participants.
    • Short Positions: The number of contracts held selling market participants.
    • Net Positions: The difference between long and short positions (Long - Short). A positive net position indicates a bullish sentiment, while a negative net position indicates a bearish sentiment.
    • Changes from Previous Report: How the long, short, and net positions have changed from the previous week's report. This highlights shifting sentiment.
    • Percentage of Open Interest: The percentage of open interest controlled by each category, which can be useful for comparing relative positioning over time.

II. Trading Strategy Based on COT Report Analysis (GULF COAST UNL 87 GAS M2 PL RB)

This strategy combines COT data with other technical and fundamental analysis to identify potential trading opportunities. It's crucial to remember that no single indicator guarantees success, and risk management is paramount.

A. Core Principles:

  1. Trend Following with Commercials: Align your trading direction with the long-term trend indicated by Commercials. The assumption is they have the best inside knowledge of the gasoline market based on their real-world business activities. Look for times when Commercials are significantly net long or short and the trend is persistent. However, Commercials are often early to the trend, so patience is required.

  2. Confirmation with Non-Commercials: Confirm the Commercials' direction with the activity of Non-Commercials. If both groups are generally moving in the same direction (increasing net longs or net shorts), the signal is strengthened. Divergence between these two groups requires caution.

  3. Contrarian Plays with Small Speculators (Non-Reportable): Extreme positioning by Small Speculators can signal potential turning points. If they are heavily long (bullish) at a market top or heavily short (bearish) at a market bottom, it can be a contrarian signal to fade the trend. Be cautious with this.

  4. Open Interest as Validation: Use open interest to confirm the strength of a trend. Increasing open interest alongside rising prices (or decreasing prices) supports the existing trend. Decreasing open interest can signal a loss of momentum.

B. Trading Rules & Signals:

  1. Bullish Scenario:

    • Commercials: Significant and increasing net long positions in gasoline futures. This suggests they anticipate higher prices.
    • Non-Commercials: Increasing net long positions, confirming the bullish sentiment.
    • Non-Reportable: Extreme net short positions (indicating excessive bearishness among small traders), potentially signaling a bottom.
    • Open Interest: Rising open interest supports the move.
    • Technical Confirmation: Price breaks above a key resistance level (e.g., a moving average or trendline) on the gasoline futures chart. Positive momentum indicators (RSI, MACD).
    • Entry: Consider entering a long position after the price breaks resistance and the COT data supports the bullish scenario. Use a stop-loss order below the recent swing low to manage risk.
    • Profit Target: Set a profit target based on technical analysis (e.g., Fibonacci extensions, previous highs) or fundamental analysis (e.g., seasonal demand patterns).

  2. Bearish Scenario:

    • Commercials: Significant and increasing net short positions in gasoline futures. This suggests they anticipate lower prices.
    • Non-Commercials: Increasing net short positions, confirming the bearish sentiment.
    • Non-Reportable: Extreme net long positions (indicating excessive bullishness among small traders), potentially signaling a top.
    • Open Interest: Rising open interest supports the move.
    • Technical Confirmation: Price breaks below a key support level on the gasoline futures chart. Negative momentum indicators.
    • Entry: Consider entering a short position after the price breaks support and the COT data supports the bearish scenario. Use a stop-loss order above the recent swing high to manage risk.
    • Profit Target: Set a profit target based on technical analysis (e.g., Fibonacci extensions, previous lows) or fundamental analysis.

C. Risk Management:

  • Position Sizing: Never risk more than 1-2% of your trading capital on a single trade. This is especially important in volatile commodity markets.
  • Stop-Loss Orders: Always use stop-loss orders to limit potential losses. Place them at logical levels based on price action and volatility.
  • Diversification: Don't put all your eggs in one basket. Diversify your trading portfolio across different commodities and asset classes.
  • Monitor the Market: Stay informed about factors that can influence gasoline prices, such as supply disruptions (refinery outages, geopolitical events), demand changes (seasonal driving patterns, economic growth), and regulatory changes.
  • Regularly Review Your Strategy: Market conditions change. Regularly review your trading strategy and adjust it as needed. Backtesting your strategy on historical data can help you identify potential weaknesses and improve its performance.

III. Advanced Considerations & Refinements:

  • COT Index: Create a COT index for each trader category (Commercials, Non-Commercials, and Non-Reportable) to normalize the data and make it easier to compare their relative positioning over time. A COT index typically ranges from 0 to 100, with higher values indicating more extreme long positions and lower values indicating more extreme short positions. You can use this index to identify overbought and oversold conditions.
  • Lagged Correlation: Explore the lagged correlation between COT data and price movements. Sometimes, the market reacts to COT positioning with a delay of a few weeks. This can help you anticipate future price movements.
  • Spread Trading: Consider spread trading strategies that involve buying and selling different gasoline futures contracts (e.g., crack spreads, which reflect the profit margin for refining crude oil into gasoline). COT data can provide insights into the positioning of traders in these spread markets.
  • Seasonality: Gasoline prices are highly seasonal, with demand typically peaking during the summer driving season. Factor seasonality into your trading decisions.
  • Fundamental Analysis: Combine COT data with fundamental analysis of the gasoline market, including factors such as crude oil prices, refinery capacity, inventory levels, and geopolitical events.
  • Volume and Open Interest Divergence: Look for divergences between volume and open interest. For example, if prices are rising but open interest is declining, it could signal a weakening trend.
  • Commitment of Traders Supplemental Reports: Check for supplemental COT reports, which provide more detailed information about the positions of different trader categories.

IV. Data Sources & Tools:

  • CFTC Website: https://www.cftc.gov/MarketReports/CommitmentsofTraders/index.htm (Official source for COT reports)
  • Trading Platforms: Many trading platforms (e.g., TradingView, NinjaTrader, MetaTrader) provide COT data and tools for analyzing it.
  • Data Vendors: Bloomberg, Reuters, and other financial data vendors offer historical COT data and analysis tools.

V. Important Caveats:

  • Lagging Indicator: The COT report is released with a delay, so it reflects positioning as of the previous Tuesday. Market conditions can change significantly in the interim.
  • Not a Holy Grail: The COT report is just one tool among many. Don't rely on it in isolation. Combine it with other technical and fundamental analysis.
  • Interpretation is Key: Interpreting the COT report requires experience and judgment. There is no one-size-fits-all approach.
  • Market Manipulation: Large players can sometimes manipulate the market. Be aware of this risk.

VI. Example Scenario:

Let's say the latest COT report for GULF COAST UNL 87 GAS M2 PL RB shows the following:

  • Commercials: Net short position of 50,000 contracts, up from 40,000 contracts the previous week.
  • Non-Commercials: Net short position of 30,000 contracts, up from 20,000 contracts the previous week.
  • Non-Reportable: Net long position of 10,000 contracts, down from 15,000 contracts the previous week.
  • Open Interest: Rising.
  • Price: Gasoline futures are trading near a resistance level.

Interpretation:

  • The Commercials and Non-Commercials are both increasingly bearish, suggesting they anticipate lower prices.
  • Small speculators are still net long, but their position is decreasing, perhaps indicating they are starting to get squeezed.
  • Rising open interest suggests the bearish trend is gaining momentum.

Possible Trading Action:

  • Wait for a break below the resistance level on the gasoline futures chart.
  • Consider entering a short position with a stop-loss order above the resistance level.
  • Set a profit target based on technical analysis or fundamental analysis.
  • Monitor the COT report each week to see if the bearish sentiment continues.

VII. Conclusion

The COT report can be a valuable tool for understanding the positioning of large players in the gasoline market. By combining COT data with technical and fundamental analysis, and implementing sound risk management practices, retail traders and market investors can potentially identify profitable trading opportunities. Remember that the COT report is just one piece of the puzzle, and success in trading requires discipline, patience, and continuous learning. Good luck!