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

NAT GASLNE OPIS MT B NONTET FP (Non-Commercial)

13-Wk Max 68 2,794 62 1,299 -487
13-Wk Min 0 549 -62 -968 -2,794
13-Wk Avg 15 1,803 -1 -55 -1,788
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 62 549 62 -503 -487 53.71% 15,794
May 6, 2025 0 1,052 0 -264 -1,052 20.06% 14,373
April 29, 2025 0 1,316 0 -175 -1,316 11.74% 16,463
April 22, 2025 0 1,491 0 -355 -1,491 19.23% 14,874
April 15, 2025 0 1,846 0 325 -1,846 -21.37% 14,167
April 8, 2025 0 1,521 0 -968 -1,521 38.89% 13,692
April 1, 2025 0 2,489 0 -305 -2,489 10.92% 15,328
March 25, 2025 0 2,794 0 350 -2,794 -14.32% 14,309
March 18, 2025 0 2,444 -6 -121 -2,444 4.49% 12,627
March 11, 2025 6 2,565 0 -111 -2,559 4.16% 11,478
March 4, 2025 6 2,676 -62 1,299 -2,670 -103.97% 10,611
February 25, 2025 68 1,377 13 60 -1,309 -3.72% 13,318
February 18, 2025 55 1,317 -20 55 -1,262 -6.32% 12,856

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for NATURAL GAS LIQUIDS

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 break down how to develop a trading strategy for Natural Gas Liquids (NGLs) based on the Commitments of Traders (COT) report, tailored for retail traders and market investors specifically focusing on the NAT GASLNE OPIS MT B NONTET FP contract traded on the ICE Futures Energy Division.

Understanding the Context

  • Commodity: Natural Gas Liquids (NGLs). These are a group of hydrocarbons including ethane, propane, butane, isobutane, and natural gasoline. They are valuable for petrochemical feedstock, heating, and blending into gasoline.
  • Contract: 42,000 Gallons (1,000 Barrels). This represents the standard trading size.
  • CFTC Market Code: IFED. Used for identifying this specific contract in CFTC data.
  • Exchange: NAT GASLNE OPIS MT B NONTET FP - ICE FUTURES ENERGY DIV. This clarifies the contract traded on the Intercontinental Exchange (ICE), utilizing the OPIS (Oil Price Information Service) index for pricing and settled financially ("FP" means financially priced). "NONTET" likely relates to a specific component or specification of the NGL mix.
  • COT Report: The Commitments of Traders report is a weekly publication by the CFTC (Commodity Futures Trading Commission) that shows the positions held by different groups of traders in the futures market. It is a vital tool for understanding market sentiment and potential price movements.

I. Core Principles of a COT-Based NGL Trading Strategy

  1. COT Report Basics:

    • Commercial Traders (Hedgers): These are companies that produce, process, or consume NGLs. They use futures to hedge price risk associated with their physical business. They are considered "informed" traders because they have a deep understanding of supply and demand fundamentals.
    • Non-Commercial Traders (Speculators): These are large entities like hedge funds, commodity trading advisors (CTAs), and other institutions that trade futures for profit. They are often trend-following and can amplify price movements.
    • Retail Traders (Small Speculators): These are individual traders with smaller positions. Their collective behavior can contribute to overall market sentiment, but they typically follow the lead of larger players.
    • Reported Positions: The COT report breaks down the open interest (total number of outstanding contracts) into Long and Short positions for each of these groups.

  2. Key COT Data Points to Monitor:

    • Net Positions: The difference between Long and Short positions for each trader category. Focus on the Net Positions of Commercial Traders and Non-Commercial Traders.
    • Changes in Positions (Delta): How positions are changing week-over-week. This shows whether traders are becoming more bullish or bearish.
    • Open Interest: Total number of outstanding contracts. Increasing Open Interest alongside rising prices can confirm an uptrend. Declining Open Interest with falling prices can confirm a downtrend.
    • Percentage of Open Interest: Expressing each group's position as a percentage of the total open interest gives you a relative view of their influence.
    • Historical Context: Compare current COT data to historical data (e.g., 1-year, 3-year, 5-year) to identify extreme levels. For example, if Commercial Traders have a historically large Net Short position, it might suggest they believe prices are too high and are hedging against a potential decline.

  3. Interpreting COT Data:

    • Commercial Traders as a Leading Indicator: Many traders believe that Commercial Traders are often "right" in the long run because of their market knowledge. Look for divergences between Commercial Trader positioning and price.
    • Non-Commercial Traders and Trends: Non-Commercial Traders often follow trends. Their large positions can exacerbate price swings. Monitor their behavior to confirm or question the sustainability of a trend.
    • Extreme Positioning: When Commercial Traders have a very large Net Short position and Non-Commercial Traders have a very large Net Long position, it can signal a potential trend reversal. However, extreme positioning can persist for a while, so don't rely on it solely for timing.

II. Developing the NGL Trading Strategy (Retail & Market Investor)

Here's a structured approach:

  1. Fundamental Analysis (Background):

    • Understand NGL Fundamentals: Before diving into COT data, get a basic understanding of NGL supply, demand, and storage. Factors influencing NGL prices include:
      • Natural Gas Production: NGLs are produced as a byproduct of natural gas processing. Increased natural gas production generally leads to increased NGL supply.
      • Petrochemical Demand: NGLs are used as feedstock in the petrochemical industry (plastics, etc.).
      • Heating Demand: Propane is used for heating in some regions.
      • Export Markets: NGL exports, particularly to Asia, can significantly impact prices.
      • Storage Levels: Track NGL storage levels (EIA data) to gauge supply and demand balance.
    • Follow Relevant News: Stay up-to-date on news related to NGL production, consumption, regulations, and global trade.

  2. COT Data Acquisition and Processing:

    • CFTC Website: Download the weekly COT report from the CFTC website (www.cftc.gov). Look for the "Supplemental" or "Disaggregated" reports. Choose the correct report type, which will likely be legacy.
    • Data Providers: Consider using a financial data provider (e.g., Bloomberg, Refinitiv, TradingView) that automatically downloads and charts COT data.
    • Spreadsheet (Excel/Google Sheets): Organize the COT data in a spreadsheet. Calculate Net Positions, Changes in Positions, and Percentage of Open Interest.
    • Charting: Create charts of:
      • NGL Price (NAT GASLNE OPIS MT B NONTET FP - ICE FUTURES ENERGY DIV)
      • Commercial Trader Net Positions
      • Non-Commercial Trader Net Positions
      • Open Interest

  3. Strategy Rules (Entry & Exit):

    • Base Case (Trend Following with COT Confirmation):
      • Uptrend: If the NGL price is in a confirmed uptrend (e.g., price above a moving average, higher highs and higher lows), AND Non-Commercial Traders are increasing their Net Long positions, consider a Long entry.
      • Downtrend: If the NGL price is in a confirmed downtrend, AND Non-Commercial Traders are increasing their Net Short positions, consider a Short entry.
      • Stop-Loss: Place a stop-loss order below a recent swing low (for Long positions) or above a recent swing high (for Short positions). Adjust the stop-loss as the trade moves in your favor.
      • Profit Target: Set a profit target based on technical analysis (e.g., Fibonacci retracement levels, resistance levels) or a multiple of your risk (e.g., 2:1 risk-reward ratio).
      • COT Exit Signal: If Non-Commercial Traders start to significantly reduce their Net Long positions in an uptrend (or reduce their Net Short positions in a downtrend), consider exiting the trade. This could signal a weakening trend.
    • Counter-Trend Strategy (More Advanced):
      • Extreme Commercial Positioning: If Commercial Traders reach a historically high Net Short position, AND the NGL price shows signs of exhaustion (e.g., overbought conditions, bearish candlestick patterns), consider a Long entry. This is a bet that Commercial Traders are anticipating a price decline that hasn't happened yet.
      • Extreme Non-Commercial Positioning: If Non-Commercial Traders reach a historically high Net Long position, AND the NGL price shows signs of overbought conditions, consider a Short entry. This is a bet that the trend has become unsustainable.
      • Stop-Loss: Place a stop-loss order above a recent swing high (for Short positions) or below a recent swing low (for Long positions). Counter-trend trading is riskier, so use tighter stop-losses.
      • Profit Target: Set a profit target based on technical analysis or a reversal pattern.
      • COT Confirmation: Watch for Commercial Traders to start covering their short positions as confirmation that the price is likely to reverse.
    • Using Moving Averages: Combine COT signals with moving averages (e.g., 50-day, 200-day) to define the overall trend. Only take long trades if the price is above the moving average and short trades if it is below.

  4. Risk Management:

    • Position Sizing: Never risk more than 1-2% of your trading capital on a single trade. Calculate your position size based on your stop-loss distance and your risk tolerance.
    • Stop-Loss Orders: Always use stop-loss orders to limit your potential losses.
    • Diversification: Don't put all your eggs in one basket. Diversify your trading portfolio across different commodities or asset classes.
    • Leverage: Be very cautious with leverage. It can amplify both your profits and your losses.

  5. Backtesting and Optimization:

    • Historical Data: Test your trading strategy on historical NGL price and COT data. This will give you an idea of its potential performance.
    • Paper Trading: Before risking real money, practice your strategy in a demo account or paper trading environment.
    • Optimization: Adjust your strategy rules (entry/exit signals, stop-loss levels, profit targets) based on your backtesting and paper trading results.

  6. Ongoing Monitoring and Adjustment:

    • Regularly Review: Review your trading strategy's performance on a regular basis (e.g., weekly, monthly).
    • Market Conditions: Be prepared to adjust your strategy based on changing market conditions and NGL fundamentals.
    • COT Thresholds: Recalibrate extreme COT levels periodically as market dynamics evolve.

III. Specific Considerations for NAT GASLNE OPIS MT B NONTET FP

  • OPIS Index: Understand how the OPIS index is calculated. It's based on transaction data from the physical NGL market. This means it's a good reflection of real-world supply and demand.
  • "NONTET" Specification: Research the specific requirements implied by the "NONTET" designation. This could be related to the specific NGL mix, vapor pressure, or other quality characteristics.
  • ICE Futures Energy Division: Familiarize yourself with the ICE's rules and regulations for trading NGL futures.
  • Basis Risk: If you are involved in the physical NGL market, be aware of basis risk, which is the difference between the futures price and the spot price in your local market. Basis risk can be influenced by transportation costs, storage costs, and local supply and demand conditions.

IV. Example Scenario

  1. Scenario: Natural gas production is increasing significantly, leading to a glut of NGLs.
  2. Expected Impact: Potentially lower NGL prices.
  3. COT Analysis:
    • Commercial Traders are starting to build up a large Net Short position in NAT GASLNE OPIS MT B NONTET FP futures, indicating they are hedging against lower prices.
    • Non-Commercial Traders are still Net Long, but their positions are starting to decrease.
  4. Trading Strategy: Consider a Short entry, following the lead of Commercial Traders. Place a stop-loss order above a recent swing high. Set a profit target based on technical analysis or a risk-reward ratio.

V. Important Notes for Retail Traders & Market Investors

  • Education is Key: Trading commodities involves significant risk. Thoroughly educate yourself about NGL markets, futures trading, and risk management before risking any capital.
  • Start Small: Begin with small positions and gradually increase your trading size as you gain experience and confidence.
  • Be Patient: COT-based trading is not a get-rich-quick scheme. It requires patience, discipline, and a long-term perspective.
  • Professional Advice: Consider consulting with a financial advisor or commodity trading advisor before making any trading decisions.
  • Data Quality: Ensure the quality of your COT data and pricing data. Errors in data can lead to incorrect trading signals.

VI. Disclaimer

  • This information is for educational purposes only and should not be considered investment advice. Trading commodities involves substantial risk of loss. You are solely responsible for your trading decisions.

By following these guidelines, you can develop a comprehensive trading strategy for Natural Gas Liquids based on the COT report and navigate the complexities of this market with a more informed and disciplined approach. Remember to always prioritize risk management and continuous learning. Good luck!