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

TRANSCO STATION 85-ZONE 4 BASI (Non-Commercial)

13-Wk Max 70,010 14,227 19,626 5,426 56,063
13-Wk Min 35,028 7,470 -5,182 -899 27,462
13-Wk Avg 52,974 11,225 2,811 908 41,749
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹī¸ Open Int.
April 29, 2025 70,010 13,947 19,626 219 56,063 52.94% 341,334
April 22, 2025 50,384 13,728 497 185 36,656 0.86% 324,780
April 15, 2025 49,887 13,543 -2,292 215 36,344 -6.45% 322,047
April 8, 2025 52,179 13,328 -2,767 -899 38,851 -4.59% 315,210
April 1, 2025 54,946 14,227 370 868 40,719 -1.21% 333,817
March 25, 2025 54,576 13,359 326 2,431 41,217 -4.86% 330,298
March 18, 2025 54,250 10,928 322 964 43,322 -1.46% 323,620
March 11, 2025 53,928 9,964 -5,182 -573 43,964 -9.49% 315,001
March 4, 2025 59,110 10,537 3,760 891 48,573 6.28% 332,295
February 25, 2025 55,350 9,646 3,841 1,962 45,704 4.29% 326,780
February 18, 2025 51,509 7,684 3,998 214 43,825 9.45% 307,355
February 11, 2025 47,511 7,470 12,483 -96 40,041 45.81% 296,458
February 4, 2025 35,028 7,566 1,555 5,426 27,462 -12.35% 263,524

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 (Overbought)
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.

Okay, let's break down a comprehensive trading strategy for Natural Gas based on the Commitment of Traders (COT) report for the TRANSCO STATION 85-ZONE 4 BASI (Basis) contract, specifically tailored for retail traders and market investors. This is a complex strategy and requires diligent monitoring and risk management.

Understanding the Landscape

  • Natural Gas Fundamentals: Before diving into the COT report, understand the basics of natural gas. Supply and demand drivers are crucial:

    • Supply: Production (domestic and imports), storage levels. Major producers (e.g., shale gas fields).
    • Demand: Weather (heating and cooling seasons drive consumption), power generation (natural gas competes with coal and renewables), industrial demand, exports (LNG).
    • Storage: The EIA (Energy Information Administration) releases weekly storage reports. These have a significant impact on prices.
    • Weather: Closely monitor weather forecasts, especially temperature outlooks for key consuming regions.

  • TRANSCO STATION 85-ZONE 4 BASI (Basis): This is a basis contract. Understanding basis is key. The basis is the difference between the price of natural gas at a specific location (TRANSCO Station 85-Zone 4) and the price of a benchmark contract (usually Henry Hub Natural Gas futures). Basis contracts reflect regional supply and demand dynamics. If supply is plentiful in the region, the basis will likely be negative (lower than Henry Hub). If demand is high in the region, the basis will likely be positive (higher than Henry Hub).

  • ICE Futures Energy Division: This is the exchange where the contract is traded.

  • CFTC Market Code: IFED: The code used by the CFTC (Commodity Futures Trading Commission) to identify this specific contract.

  • Commitment of Traders (COT) Report: The COT report is a weekly report published by the CFTC that breaks down the open interest (outstanding contracts) in futures markets by the positions held by different types of traders. The main categories are:

    • Commercial Traders (Hedgers): Entities that use futures markets to hedge their business risks (e.g., producers, consumers). They are driven by physical supply and demand.
    • Non-Commercial Traders (Large Speculators): Hedge funds, commodity trading advisors (CTAs), and other large investors who are trading for profit.
    • Nonreportable Positions (Small Speculators): Smaller traders whose positions are below the reporting threshold. Their positions are usually inferred by subtracting the positions of Commercial and Non-Commercial traders from total open interest.

Trading Strategy Based on COT Report (Retail Trader/Market Investor Focus)

This strategy uses the COT report to identify potential shifts in market sentiment and positioning related to this specific BASIS contract. This strategy is more complex as it involves assessing the supply/demand situation at TRANSCO 85-Zone 4 relative to Henry Hub.

1. Data Acquisition and Preparation:

  • COT Report Source: Obtain the COT data for "Natural Gas - TRANSCO STATION 85-ZONE 4 BASI - ICE FUTURES ENERGY DIV" (using the IFED code) from the CFTC website. You can download it in CSV format.
  • Historical Data: Collect historical price data for the TRANSCO 85-Zone 4 Basis contract. You'll need a data provider that offers this specific contract data.
  • Spreadsheet/Analysis Software: Use a spreadsheet program (Excel, Google Sheets) or a statistical software package (R, Python) for data analysis.
  • Calculate Key Metrics:
    • Net Positions: Calculate the net position for each trader category (Commercials and Non-Commercials): Net Position = Long Positions - Short Positions.
    • Changes in Net Positions: Calculate the week-over-week change in the net positions for each category.
    • Percentage of Open Interest: Express each trader category's net position as a percentage of the total open interest.
    • COT Index/Oscillator (Optional): Create a COT index or oscillator to smooth the data and identify overbought/oversold conditions. A common approach is to calculate a moving average of the net positions. A good starting point is a 52-week moving average, and then express the current net position relative to this average.
    • Basis Differential: Track the differential between the TRANSCO 85-Zone 4 price and Henry Hub price. This is fundamental to understand the BASIS contract.

2. Interpretation of COT Data (Specific to Basis Contract):

  • Commercial Traders (Hedgers):
    • Increasing Net Short Position: If Commercial traders are increasing their net short positions, it suggests they anticipate the TRANSCO 85-Zone 4 price to decline relative to Henry Hub (or increase less). This could be due to anticipating higher local supply, lower local demand, or difficulties in transporting gas out of the area.
    • Increasing Net Long Position: If Commercial traders are increasing their net long positions, it suggests they anticipate the TRANSCO 85-Zone 4 price to increase relative to Henry Hub (or decline less). This could be due to anticipating lower local supply, higher local demand, or easier transportation out of the area.
    • Focus on Changes: Pay more attention to changes in Commercial positions than the absolute level. A sudden shift indicates a change in their expectations.
  • Non-Commercial Traders (Large Speculators):
    • Following the Trend: Large speculators often follow trends established by commercial traders. A large increase in Non-Commercial net longs alongside Commercial net longs can amplify the price movement.
    • Contrarian Indicator (Sometimes): If Non-Commercials are heavily long while Commercials are heavily short, it could signal a potential reversal. However, this is not always reliable.
  • Open Interest:
    • Increasing Open Interest: Usually confirms the trend. More participants are entering the market.
    • Decreasing Open Interest: Could signal a weakening trend or a potential reversal.

3. Integrating COT Data with Fundamental Analysis:

This is where the strategy becomes more sophisticated. You must integrate the COT data with your understanding of the natural gas market specifically around TRANSCO Station 85-Zone 4. Consider:

  • Local Weather Forecasts: Is there an extreme weather event expected in the region served by TRANSCO Station 85-Zone 4? (Heating or Cooling)
  • Pipeline Capacity: Are there any pipeline maintenance issues or capacity constraints that could impact gas flow in/out of the region?
  • Local Storage Levels: Are storage levels in the region high or low relative to historical averages? This could influence basis differentials.
  • Power Plant Demand: Are there any changes in power plant demand in the region that could affect natural gas consumption?
  • Comparison to Henry Hub Drivers: How do the drivers at Transco 85-Zone 4 compare to those at Henry Hub? Is there divergence or convergence?

4. Trading Signals and Strategy:

  • Bullish Signal (Basis likely to increase relative to Henry Hub):
    • Commercial traders are significantly increasing their net long positions in the TRANSCO 85-Zone 4 Basis contract.
    • Non-Commercial traders are also increasing their net long positions (confirming the trend).
    • Open interest is increasing.
    • Fundamental analysis supports higher demand or lower supply in the TRANSCO Station 85-Zone 4 region relative to Henry Hub. This could be due to a heat wave in the region or a pipeline outage.
  • Bearish Signal (Basis likely to decrease relative to Henry Hub):
    • Commercial traders are significantly increasing their net short positions in the TRANSCO 85-Zone 4 Basis contract.
    • Non-Commercial traders are also increasing their net short positions (confirming the trend).
    • Open interest is increasing.
    • Fundamental analysis supports lower demand or higher supply in the TRANSCO Station 85-Zone 4 region relative to Henry Hub. This could be due to mild weather or increased local production.

5. Entry and Exit Points:

  • Entry:
    • Enter a long position in the TRANSCO 85-Zone 4 Basis contract when you have a confirmed bullish signal.
    • Enter a short position in the TRANSCO 85-Zone 4 Basis contract when you have a confirmed bearish signal.
  • Exit (Profit Taking):
    • Set profit targets based on technical analysis (e.g., Fibonacci levels, support/resistance) or a percentage gain.
    • Consider exiting when the COT data shows a weakening trend or a potential reversal.
  • Stop-Loss Orders:
    • Crucial! Protect your capital with stop-loss orders. Place stop-loss orders based on technical levels or a percentage loss. If the market moves against your position, the stop-loss will automatically close the trade, limiting your losses.
    • Volatility Considerations: Natural gas is volatile. Your stop-loss orders need to be wide enough to avoid being triggered by normal market fluctuations, but tight enough to protect your capital.

6. Risk Management:

  • Position Sizing: Never risk more than a small percentage of your trading capital on any single trade (e.g., 1-2%).
  • Diversification: Don't put all your eggs in one basket. Diversify your portfolio across different markets and asset classes.
  • Leverage: Be very careful with leverage. It can amplify both profits and losses.
  • Regular Review: Review your trading strategy regularly and make adjustments as needed. The natural gas market is constantly changing.

7. Tools and Resources:

  • CFTC Website: For COT reports.
  • EIA (Energy Information Administration): For natural gas storage data and market analysis.
  • Weather Services: For weather forecasts (crucial for natural gas trading).
  • Brokerage Platform: Choose a brokerage that offers access to natural gas futures and options and has good charting tools.
  • Data Provider: A data provider that offers historical and real-time data for the TRANSCO STATION 85-ZONE 4 BASI contract is essential.

Example Scenario:

Let's say the COT report shows that Commercial traders have significantly increased their net long positions in the TRANSCO 85-Zone 4 Basis contract. Non-Commercial traders are also following suit. At the same time, a heat wave is forecast for the region served by TRANSCO Station 85-Zone 4, and pipeline capacity is temporarily reduced.

This would be a bullish signal. You could enter a long position in the TRANSCO 85-Zone 4 Basis contract, expecting the price to increase relative to Henry Hub due to higher demand and constrained supply in the region. Set a profit target and a stop-loss order to manage your risk.

Important Considerations:

  • Basis Risk: Trading basis contracts involves basis risk. Even if you are correct about the overall direction of natural gas prices, the local basis can move against you.
  • Complexity: This strategy is more complex than simply trading Henry Hub futures. You need a solid understanding of regional natural gas markets.
  • Due Diligence: Thoroughly research and backtest your strategy before risking real capital.
  • Professional Advice: Consider consulting with a financial advisor or a commodity trading advisor (CTA) before implementing this strategy.
  • No Guarantees: There are no guarantees of success in trading. You can lose money.

In Summary:

This COT-based strategy for the TRANSCO STATION 85-ZONE 4 BASI contract is a powerful tool for retail traders and market investors, but it requires a significant investment of time and effort to understand the nuances of the natural gas market. By combining COT data with fundamental analysis and sound risk management, you can increase your chances of success. Remember to start small, test your strategy thoroughly, and continuously adapt to changing market conditions.