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

NAT GAS ICE LD1 (Non-Commercial)

13-Wk Max 1,528,650 291,850 171,651 74,074 1,372,213
13-Wk Min 1,144,664 117,119 -150,603 -102,192 887,401
13-Wk Avg 1,376,473 198,796 -1,477 4,634 1,177,678
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹī¸ Open Int.
April 29, 2025 1,144,664 189,658 -34,587 -102,192 955,006 7.62% 7,514,194
April 22, 2025 1,179,251 291,850 -68,160 28,206 887,401 -9.80% 7,830,944
April 15, 2025 1,247,411 263,644 -150,603 -5,714 983,767 -12.84% 7,752,445
April 8, 2025 1,398,014 269,358 -72,654 30,003 1,128,656 -8.34% 7,712,088
April 1, 2025 1,470,668 239,355 864 39,287 1,231,313 -3.03% 7,678,048
March 25, 2025 1,469,804 200,068 17,485 14,780 1,269,736 0.21% 7,910,382
March 18, 2025 1,452,319 185,288 -27,550 6,984 1,267,031 -2.65% 7,965,747
March 11, 2025 1,479,869 178,304 -48,781 17,837 1,301,565 -4.87% 7,985,639
March 4, 2025 1,528,650 160,467 60,606 12,277 1,368,183 3.66% 7,827,222
February 25, 2025 1,468,044 148,190 -54,018 -1,659 1,319,854 -3.82% 7,977,423
February 18, 2025 1,522,062 149,849 171,651 -41,344 1,372,213 18.37% 7,768,115
February 11, 2025 1,350,411 191,193 167,426 74,074 1,159,218 8.76% 7,476,729
February 4, 2025 1,182,985 117,119 19,116 -12,292 1,065,866 3.04% 7,351,825

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 â‰Ĩ 3 Neutral (Overbought)
Net in bottom 20% of 1-year range AND net downtrend â‰Ĩ 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 for Natural Gas (NAT GAS ICE LD1) Based on the COT Report

This strategy outlines how a retail trader and a market investor can use the Commitment of Traders (COT) report for NAT GAS ICE LD1 to inform their trading decisions. It incorporates fundamental analysis, technical analysis, and risk management for a comprehensive approach.

I. Understanding the COT Report for Natural Gas (NAT GAS ICE LD1 - IFED):

  • What is the COT Report? The COT report is a weekly publication released by the CFTC (Commodity Futures Trading Commission) that details the positions held by various types of market participants in futures markets. It helps understand the collective sentiment and positioning of different trader groups.

  • Key Categories in the Report:

    • Commercials: Entities that use natural gas in their business (e.g., producers, processors, utilities). They are typically considered "hedgers" aiming to manage price risk.
    • Non-Commercials (Large Speculators): Hedge funds, managed money, and other large entities trading for profit. Their positions often reflect directional bets on price.
    • Non-Reportable Positions: Positions too small to be reported individually. Often considered retail traders and smaller speculators.

  • Data Points to Focus On:

    • Net Positions: Long positions minus short positions for each category. This shows the overall bullish or bearish stance.
    • Changes in Positions: The week-over-week change in net positions. This reveals the direction of shifting sentiment.
    • Historical Context: Compare current positions to historical levels to identify extreme readings that may signal potential reversals.

II. Fundamental Analysis (Complementing COT Data):

COT data is most effective when combined with fundamental analysis. Consider these factors:

  • Supply:
    • Production: US natural gas production levels (tracked by EIA). Increased production can pressure prices.
    • Imports/Exports: LNG (Liquefied Natural Gas) exports are a major demand factor. Increased exports support prices.
    • Storage Levels: EIA's weekly storage report is crucial. High storage levels often lead to price declines, while low levels support prices.
  • Demand:
    • Weather: Heating demand in winter and cooling demand in summer significantly impacts natural gas usage. Monitor weather forecasts.
    • Industrial Demand: Economic activity affects industrial consumption of natural gas.
    • Power Generation: Natural gas is a key fuel for electricity generation. Monitor coal and renewable energy competition.
  • Geopolitical Events: Events like pipeline disruptions or political instability in gas-producing regions can affect prices.

III. Technical Analysis (Fine-Tuning Entry and Exit Points):

Technical analysis helps identify specific entry and exit points within the broader trend suggested by the COT report and fundamentals.

  • Key Technical Indicators:
    • Moving Averages (MA): Identify trends (e.g., 50-day, 200-day MAs).
    • Relative Strength Index (RSI): Overbought/oversold conditions.
    • MACD (Moving Average Convergence Divergence): Momentum and potential trend changes.
    • Fibonacci Retracements: Potential support and resistance levels.
  • Chart Patterns:
    • Head and Shoulders: Potential reversal pattern.
    • Double Tops/Bottoms: Reversal patterns.
    • Triangles: Continuation or reversal patterns.

IV. Trading Strategy for the Retail Trader:

  • Investment Horizon: Short to medium-term (days to weeks). Less capital and a higher risk tolerance than the market investor.

  • Tools Used: COT data, daily/hourly charts, fundamental news feeds.

  • Strategy:

    1. Identify the Dominant Trend: Determine if the long-term trend is bullish or bearish based on fundamentals and long-term moving averages.

    2. COT Confirmation:

      • Bullish Trend: Look for increasing net long positions by Non-Commercials (large speculators) to confirm upward momentum. Commercials decreasing their short positions also indicate a potential upswing.
      • Bearish Trend: Look for increasing net short positions by Non-Commercials. Commercials reducing their long positions indicate a potential downswing.

    3. Overbought/Oversold Signals:

      • Bullish Setup: If the COT report suggests a bullish trend, wait for a temporary pullback and an oversold signal (RSI below 30) before entering a long position.
      • Bearish Setup: If the COT report suggests a bearish trend, wait for a temporary rally and an overbought signal (RSI above 70) before entering a short position.

    4. Entry Point: Use technical analysis to pinpoint your entry. Enter on a breakout above a key resistance level (for long positions) or below a key support level (for short positions).

    5. Stop-Loss Order: Place a stop-loss order below a recent swing low (for long positions) or above a recent swing high (for short positions) to limit potential losses. Adjust stop losses as the trade moves in your favor to lock in profits.

    6. Profit Target: Set a profit target based on technical analysis (e.g., Fibonacci retracements, previous resistance/support levels). Consider a risk/reward ratio of at least 1:2.

    7. Monitoring: Continuously monitor the COT report, fundamental news, and technical indicators. Be prepared to adjust your position if the market conditions change.

    Example:

    • Fundamentals: Winter is approaching, and forecasts predict a colder-than-average season, suggesting increased heating demand. Natural gas storage levels are below the 5-year average.
    • COT: Non-Commercials have been steadily increasing their net long positions over the past few weeks, indicating growing bullish sentiment. Commercials decreasing their short positions also support this.
    • Technicals: Price has pulled back to the 50-day moving average and is showing an oversold signal on the RSI.
    • Trade: Enter a long position near the 50-day MA with a stop-loss order just below the recent swing low. Set a profit target near the next Fibonacci retracement level or a previous resistance level.

V. Trading Strategy for the Market Investor:

  • Investment Horizon: Medium to long-term (months to years). Larger capital base and a focus on capturing major trend moves.

  • Tools Used: COT data, weekly/monthly charts, in-depth fundamental research.

  • Strategy:

    1. Long-Term Trend Identification: Analyze the overall trend based on long-term fundamental factors (e.g., supply/demand balance, global LNG market) and multi-year price charts.

    2. COT Confirmation of Major Trend:

      • Long-Term Bullish Trend: Confirm that Non-Commercials consistently hold a significant net long position and add to it during price dips. Also keep an eye on Commercials.
      • Long-Term Bearish Trend: Confirm that Non-Commercials consistently hold a significant net short position and add to it during price rallies. Also keep an eye on Commercials.

    3. Identify Extreme COT Readings: Look for periods where the Non-Commercials net position reaches historically high or low levels relative to past years. These extremes can signal potential trend reversals.

    4. Gradual Accumulation/Distribution: Instead of entering a large position at once, gradually accumulate or distribute positions over time to average out the entry price.

    5. Position Sizing: Use a smaller percentage of your portfolio for each trade due to the longer time horizon and potential for larger price swings.

    6. Rebalancing: Periodically rebalance your portfolio to maintain your desired asset allocation.

    7. Long-Term Options (LEAPS): Consider using long-term options (LEAPS) to control a larger position with a smaller upfront investment. This can magnify potential profits but also carries higher risk.

    Example:

    • Fundamentals: Global LNG demand is projected to increase significantly over the next decade due to the shift away from coal and increased energy consumption in developing countries.
    • COT: Non-Commercials have maintained a consistently large net long position in natural gas futures, indicating confidence in the long-term uptrend.
    • Technicals: The weekly chart shows a clear uptrend with higher highs and higher lows.
    • Trade: Gradually accumulate a long position in natural gas futures or LEAPS calls on dips. Hold the position for the long term, rebalancing periodically.

VI. Risk Management:

  • Position Sizing: Never risk more than 1-2% of your trading capital on a single trade.
  • Stop-Loss Orders: Always use stop-loss orders to limit potential losses.
  • Diversification: Do not put all your eggs in one basket. Diversify your portfolio across different asset classes.
  • Leverage: Use leverage cautiously. While it can magnify profits, it can also magnify losses.
  • Emotional Control: Avoid making impulsive trading decisions based on fear or greed. Stick to your trading plan.

VII. Important Considerations:

  • Lag Time: The COT report is released on Friday afternoons and reflects positions held as of the previous Tuesday. Market conditions may have changed significantly since then.
  • Correlation vs. Causation: The COT report can be a useful indicator, but it does not guarantee future price movements. There may be other factors at play.
  • Market Volatility: Natural gas is a volatile commodity. Be prepared for significant price swings.
  • Continuous Learning: The markets are constantly evolving. Stay informed about the latest news and developments in the natural gas market.

VIII. Disclaimer:

This strategy is for informational purposes only and should not be considered financial advice. Trading commodities involves significant risk and is not suitable for all investors. Always consult with a qualified financial advisor before making any investment decisions. Past performance is not indicative of future results.

By combining the COT report with fundamental and technical analysis, and by implementing sound risk management practices, retail traders and market investors can improve their chances of success in the natural gas market. Remember to adapt this strategy to your own risk tolerance, investment goals, and market knowledge. Good luck!