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

NNG DEMARC BASIS (Non-Commercial)

13-Wk Max 1,634 0 679 0 1,634
13-Wk Min 0 0 -389 0 0
13-Wk Avg 520 0 41 0 520
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
February 28, 2023 0 0 0 0 0 -100.00% 46,887
November 29, 2022 1,511 0 0 0 1,511 51.71% 52,320
February 1, 2022 996 0 0 0 996 -30.45% 24,986
January 4, 2022 1,432 0 679 0 1,432 90.17% 26,738
December 28, 2021 753 0 0 0 753 -53.92% 26,068
November 30, 2021 1,634 0 0 0 1,634 ∞% 30,914
January 5, 2021 0 0 0 0 0 0.00% 35,875
December 29, 2020 0 0 0 0 0 0.00% 35,863
December 8, 2020 0 0 -217 0 0 -100.00% 34,833
December 1, 2020 217 0 0 0 217 0.00% 38,320
November 24, 2020 217 0 217 0 217 ∞% 36,937
November 17, 2020 0 0 0 0 0 0.00% 36,143
November 10, 2020 0 0 -389 0 0 -100.00% 36,217

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for NATURAL GAS

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.

Trading Strategy: NNG Demarc Basis (Natural Gas) - COT Report Based

Commodity: Natural Gas (specifically, the Northern Natural Gas - Demarcation Pool (Basis)) Contract Units: 2,500 MMBtu CFTC Market Code: IFED Market Exchange: ICE Futures Energy Div

Disclaimer: Trading futures involves substantial risk and is not suitable for all investors. This strategy is for educational purposes only and should not be considered financial advice. Past performance is not indicative of future results. Always conduct thorough research and consult with a qualified financial advisor before making any investment decisions.

I. Understanding the NNG Demarc Basis

  • What it is: The Northern Natural Gas Demarcation Pool Basis (NNG Demarc Basis) represents the price difference between the Henry Hub natural gas price (the benchmark) and the price of natural gas at the Demarcation Pool along the Northern Natural Gas Pipeline.
  • Why it matters: This basis reflects regional supply and demand dynamics. Factors influencing it include:
    • Pipeline Capacity: Constraints on the Northern Natural Gas pipeline can widen the basis.
    • Local Demand: Strong demand in the Midwest (served by the pipeline) can push the NNG Demarc price higher relative to Henry Hub, widening the basis.
    • Local Production: Increased local production can lower the NNG Demarc price, narrowing the basis.
    • Weather: Extreme weather conditions (both hot and cold) significantly impact demand and, therefore, the basis.
    • Storage Levels: Regional storage levels influence the need to draw gas from or inject gas into the pipeline, impacting the basis.

II. The Role of the Commitment of Traders (COT) Report

  • What it is: The COT report, published weekly by the CFTC, provides a breakdown of the positions held by different categories of traders in the futures market. For NNG Demarc Basis, we focus on:
    • Commercial Traders (Hedgers): Primarily involved in the physical natural gas business. They use futures to hedge their exposure to price fluctuations.
    • Non-Commercial Traders (Speculators): Entities like hedge funds and managed money accounts who trade futures for profit, based on market trends.
    • Non-Reportable Positions: Small traders whose positions are too small to be reported individually.
  • What it tells us: The COT report provides insights into the collective sentiment of these trader groups:
    • Commercial Traders: Their positions reflect their outlook on future physical supply and demand. A large net short position from commercials often indicates they expect lower prices.
    • Non-Commercial Traders: Their positions reflect their bets on price direction. A large net long position from non-commercials often indicates a bullish outlook.
  • Key Data Points:
    • Net Positions: (Long positions - Short positions) for each trader category.
    • Changes in Positions: Week-over-week changes in net positions to identify shifts in sentiment.
    • Open Interest: The total number of outstanding futures contracts. Increasing open interest suggests new money entering the market, confirming the prevailing trend.

III. Trading Strategy: COT-Based Approach for NNG Demarc Basis

A. Strategy Overview

This strategy seeks to identify potential overbought or oversold conditions in the NNG Demarc Basis futures market by analyzing the positions and behavior of commercial and non-commercial traders as reported in the COT report. It aims to capitalize on potential corrections in the basis price when trader sentiment becomes extreme.

B. Core Principles

  • Commercial Traders as "Smart Money": Generally, follow the trend of commercial traders. They have the most intimate knowledge of the physical gas market.
  • Speculative Excess: Look for situations where non-commercial traders have built up excessive long or short positions, suggesting a potential for a reversal.
  • Divergence: Observe divergence between price action and COT data. If the basis price is rising, but commercial traders are increasing their net short positions, it may signal an impending correction.
  • Confirmation: Always look for confirmation from other technical indicators and fundamental analysis before entering a trade.

C. Trading Signals

  1. Potential Long Signal (Basis Strengthening):

    • COT Criteria:
      • Commercial traders significantly decrease their net short positions (covering shorts).
      • Non-commercial traders significantly decrease their net long positions (taking profits or closing positions).
      • Open Interest declines or remains stable.
    • Technical Confirmation:
      • The basis price is showing signs of bottoming (e.g., a double bottom, a bullish candlestick pattern, breaking above a resistance level).
      • Momentum indicators (RSI, MACD) are showing bullish divergence.
    • Fundamental Confirmation:
      • Anticipation of increased regional demand (e.g., forecasts for cold weather in the Midwest).
      • Concerns about pipeline capacity constraints.

  2. Potential Short Signal (Basis Weakening):

    • COT Criteria:
      • Commercial traders significantly increase their net short positions (adding hedges).
      • Non-commercial traders significantly increase their net long positions (excessive speculation).
      • Open Interest increases.
    • Technical Confirmation:
      • The basis price is showing signs of topping (e.g., a double top, a bearish candlestick pattern, breaking below a support level).
      • Momentum indicators (RSI, MACD) are showing bearish divergence.
    • Fundamental Confirmation:
      • Anticipation of decreased regional demand (e.g., forecasts for mild weather in the Midwest).
      • Expectations of increased local gas production.

D. Entry and Exit Strategy

  • Entry:
    • Enter the trade after confirming the COT signal with technical and fundamental analysis.
    • Consider using a limit order at a slightly better price than the current market price to improve your entry.
  • Stop-Loss:
    • Place a stop-loss order to limit potential losses.
    • Base the stop-loss level on technical support or resistance levels, or a percentage of your account equity.
    • Consider using a trailing stop-loss to lock in profits as the trade moves in your favor.
  • Profit Target:
    • Set a profit target based on technical resistance or support levels, historical basis price ranges, or a risk-reward ratio (e.g., aim for a 2:1 or 3:1 reward-to-risk ratio).
    • Consider scaling out of the trade as you approach your profit target to reduce risk and lock in profits.

E. Risk Management

  • Position Sizing: Never risk more than 1-2% of your trading capital on any single trade.
  • Diversification: Don't put all your eggs in one basket. Diversify your portfolio across different commodities and asset classes.
  • Emotional Control: Trade with a clear and disciplined approach. Avoid making emotional decisions based on fear or greed.
  • Record Keeping: Keep a detailed record of all your trades, including entry and exit prices, reasons for the trade, and the results. This will help you learn from your mistakes and improve your strategy over time.

IV. Example Trade Scenario

Scenario: Assume the NNG Demarc Basis price has been steadily rising, and the latest COT report reveals the following:

  • Commercial Traders: Increased their net short positions by a significant amount.
  • Non-Commercial Traders: Increased their net long positions to near record highs.
  • Open Interest: Increased significantly.

Analysis: This suggests that commercial traders believe the basis is overvalued and are hedging against a potential price decline. Non-commercial traders are overly bullish, potentially creating a crowded long trade. The increasing open interest confirms that new money is fueling the rally, which might be unsustainable.

Trade Setup:

  • Signal: Potential short signal (basis weakening).
  • Technical Confirmation: Wait for a bearish candlestick pattern to form on the chart or a break below a short-term support level.
  • Entry: Enter a short position after the confirmation signal.
  • Stop-Loss: Place a stop-loss order above the recent high.
  • Profit Target: Set a profit target near a previous support level or at a predetermined risk-reward ratio.

V. Additional Considerations

  • News and Events: Stay informed about factors that could affect the NNG Demarc Basis, such as weather forecasts, pipeline maintenance announcements, and regional gas production reports.
  • Seasonality: Natural gas prices and basis differentials often exhibit seasonal patterns. Understand these patterns and incorporate them into your trading strategy.
  • Correlation: Be aware of the correlation between the NNG Demarc Basis and other natural gas benchmarks, such as Henry Hub.
  • Backtesting: Before implementing this strategy with real money, backtest it on historical data to assess its performance and identify potential weaknesses.
  • Continuous Learning: The market is constantly evolving. Stay updated on the latest market trends, news, and trading techniques to improve your trading skills.

VI. Advantages and Disadvantages of this Strategy

Advantages:

  • Data-Driven: Based on publicly available data (COT report).
  • Objective: Provides clear entry and exit signals.
  • Potentially Profitable: Can capitalize on price reversals and market inefficiencies.

Disadvantages:

  • Lagging Indicator: The COT report is released with a delay, so the data may not reflect the most current market conditions.
  • Not a Perfect Predictor: The COT report is just one piece of the puzzle. It should be used in conjunction with other forms of analysis.
  • Requires Patience: May require patience to wait for the right trade setup.
  • Basis Risk: The basis can be volatile and unpredictable due to local supply/demand conditions.

VII. Conclusion

This COT report-based trading strategy offers a framework for analyzing the NNG Demarc Basis futures market and identifying potential trading opportunities. However, it is essential to remember that no trading strategy is foolproof. Always use proper risk management techniques and conduct thorough research before making any trading decisions. By combining COT analysis with technical and fundamental analysis, you can increase your chances of success in the NNG Demarc Basis market. Remember to continually adapt and refine your strategy based on market conditions and your own trading experience.