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

PJM.PSEG_month_on_dap (Non-Commercial)

13-Wk Max 10,316 4,950 180 2,540 8,631
13-Wk Min 9,543 1,055 -580 -1,995 4,643
13-Wk Avg 9,823 2,851 -50 69 6,972
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 9,593 4,950 50 730 4,643 -12.77% 84,518
May 6, 2025 9,543 4,220 -135 -265 5,323 2.50% 82,862
April 29, 2025 9,678 4,485 25 540 5,193 -9.02% 85,590
April 22, 2025 9,653 3,945 0 350 5,708 -5.78% 84,720
April 15, 2025 9,653 3,595 25 2,540 6,058 -29.34% 83,245
April 8, 2025 9,628 1,055 -388 -330 8,573 -0.67% 78,613
April 1, 2025 10,016 1,385 100 -130 8,631 2.74% 81,088
March 25, 2025 9,916 1,515 0 -110 8,401 1.33% 81,360
March 18, 2025 9,916 1,625 180 -50 8,291 2.85% 82,186
March 11, 2025 9,736 1,675 0 180 8,061 -2.18% 81,263
March 4, 2025 9,736 1,495 -580 -1,065 8,241 6.25% 81,008
February 25, 2025 10,316 2,560 0 -1,995 7,756 34.63% 84,098
February 18, 2025 10,316 4,555 75 500 5,761 -6.87% 81,099

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for ELECTRICITY

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 Sell
Based on the latest 13 weeks of non-commercial positioning data.
📊 COT Sentiment Analysis Guide

This guide helps traders understand how to interpret Commitments of Traders (COT) reports to generate potential Buy, Sell, or Neutral signals using market positioning data.

🧠 How It Works
  • Recent Trend Detection: Tracks net position and rate of change (ROC) over the last 13 weeks.
  • Overbought/Oversold Check: Compares current net positions to a 1-year range using percentiles.
  • Strength Confirmation: Validates if long or short positions are dominant enough for a signal.
✅ Signal Criteria
Condition Signal
Net ↑ for 13+ weeks AND ROC ↑ for 13+ weeks AND strong long dominance Buy
Net ↓ for 13+ weeks AND ROC ↓ for 13+ weeks AND strong short dominance Sell
Net in top 20% of 1-year range AND net uptrend ≥ 3 Neutral (Overbought)
Net in bottom 20% of 1-year range AND net downtrend ≥ 3 Neutral (Oversold)
None of the above conditions met Neutral
🧭 Trader Tips
  • Trend traders: Follow Buy/Sell signals when all trend and strength conditions align.
  • Contrarian traders: Use Neutral (Overbought/Oversold) flags to anticipate reversals.
  • Swing traders: Use sentiment as a filter to increase trade confidence.
Example:
Net positions rising, strong long dominance, in top 20% of historical range.
Result: Neutral (Overbought) — uptrend may be too crowded.
  • COT data is delayed (released on Friday, based on Tuesday's positions) - it's not real-time.
  • Combine with price action, FVG, liquidity, or technical indicators for best results.
  • Use percentile filters to avoid buying at extreme highs or selling at extreme lows.

Okay, let's craft a comprehensive trading strategy based on the Commitments of Traders (COT) report for the PJM.PSEG_month_on_dap electricity contract (traded on Nodal Exchange), geared towards retail traders and market investors. This will involve understanding the COT report, its application to electricity markets, and formulating a practical strategy with risk management.

I. Understanding the COT Report & Electricity Markets

  • What is the COT Report? The COT report, released weekly by the CFTC (Commodity Futures Trading Commission), breaks down the open interest in futures markets by the types of traders:

    • Commercial Traders (Hedgers): These are companies that use futures to hedge their underlying business activities. In electricity, this includes power generators, utilities, and large consumers. Their primary goal is risk management, not speculation.
    • Non-Commercial Traders (Speculators): These are large institutional investors (hedge funds, money managers, etc.) that trade futures for profit based on market trends.
    • Non-Reportable Positions: Small traders that do not meet the reporting thresholds.
    • Supplemental Breakdown (Sometimes Available): Managed Money and other categories may provide more granular insights.

  • Relevance to Electricity: The COT report can be valuable in electricity markets because:

    • Hedging Activity: Understanding how commercial traders are positioning themselves can reveal insights into their expectations about future electricity prices. For example, a large increase in short positions (selling) by commercial traders might suggest they anticipate lower prices in the future.
    • Speculative Influence: The positioning of non-commercial traders can indicate the strength and direction of current market trends. Large net long positions (buying) suggest bullish sentiment, while net short positions indicate bearish sentiment.
    • Seasonality: Electricity prices are highly seasonal, driven by weather, demand, and generation patterns. You need to interpret the COT report in the context of the time of year and prevailing market conditions.
    • Nodal Pricing: The PJM.PSEG_month_on_dap is a specific location-based (nodal) contract. Nodal pricing is very sensitive to local congestion and grid conditions, making interpretation a bit more complex than broad regional or national electricity benchmarks.

  • Key COT Data Points:

    • Net Positions: This is the most critical metric. It's the difference between long positions (contracts bought) and short positions (contracts sold) for each trader category. Focus on the change in net positions over time.
    • Open Interest: The total number of outstanding contracts. Increasing open interest often validates a trend, while declining open interest may signal a weakening trend.
    • Percentage of Open Interest: The percentage of open interest held by each group can highlight dominance and potential impact on the market.

II. Trading Strategy Formulation

This strategy is based on the idea of identifying divergences between the actions of commercial traders (hedgers) and the prevailing market trend, as driven by speculators. It also incorporates risk management and acknowledgement of market complexities.

  • Assumptions:

    • You have a funded brokerage account that allows trading electricity futures on the Nodal Exchange.
    • You have access to historical COT data and price charts for PJM.PSEG_month_on_dap. (Often available through your broker or specialized financial data providers).
    • You understand the risks of trading electricity futures, including high volatility and potential for significant losses.

  • Strategy Name: "Hedge-Spec Divergence Play"

  • Core Principle: Fade speculative extremes by trading in the direction of commercial hedging activity when it diverges from the prevailing market sentiment.

  • Steps:

    1. Data Gathering:

      • Obtain weekly COT reports for NODX (PJM.PSEG_month_on_dap). Download historical data to create charts of net positions for commercial and non-commercial traders.
      • Obtain historical price data for the PJM.PSEG_month_on_dap contract.
      • Monitor weather forecasts and grid conditions within the PJM region (particularly around PSEG, Public Service Enterprise Group). This will help to validate the analysis of the COT report.

    2. COT Analysis:

      • Identify Divergences: Look for instances where commercial traders are increasing their short positions (hedging against price decreases) while non-commercial traders are increasing their long positions (betting on price increases), or vice versa. A large divergence in net positions between the two is the key signal.
      • Confirm with Open Interest: Rising open interest alongside the divergence strengthens the signal. If open interest is declining, the signal is weaker.
      • Contextualize: Consider the time of year and weather patterns. For example, an increase in commercial short positions before the peak summer demand period might be a stronger signal than during the off-peak season.
      • Commercial Dominance: Observe if commercial traders are accounting for a large percentage of total open interest. If they hold a major position, that lends more importance to their sentiment.

    3. Entry Signal:

      • Bearish Scenario: If commercial traders are increasing short positions significantly, and non-commercial traders are increasing long positions, this suggests an overbought market. Look for a price reversal confirmation (e.g., a bearish candlestick pattern or a break below a short-term moving average) to initiate a short position (sell the futures contract).
      • Bullish Scenario: If commercial traders are increasing long positions significantly, and non-commercial traders are increasing short positions, this suggests an oversold market. Look for a price reversal confirmation (e.g., a bullish candlestick pattern or a break above a short-term moving average) to initiate a long position (buy the futures contract).

    4. Stop-Loss Order:

      • Crucially Important! Place a stop-loss order to limit potential losses. The stop-loss should be placed above a recent high (for short positions) or below a recent low (for long positions). A common approach is to use a multiple of the Average True Range (ATR) to determine stop-loss placement. ATR helps measure market volatility.
      • Example: If you're shorting, and the recent high is $50/MWh, and the ATR is $2/MWh, place your stop-loss at $52/MWh or higher.

    5. Take-Profit Order:

      • Set a take-profit order based on a realistic target. Consider:
        • Technical Levels: Look for support and resistance levels on the price chart.
        • ATR Multiple: Use a multiple of the ATR to project a profit target. For example, a take-profit at 2x the ATR.
        • Hedger's Target: Estimate a reasonable price based on the hedger's position. If hedgers are significantly increasing short positions at a level, that may be a level they see value in selling.

    6. Position Sizing:

      • Risk Management: Never risk more than 1-2% of your total trading capital on a single trade. This means calculating the maximum potential loss (stop-loss level minus entry price) and adjusting your contract size accordingly.
      • Example: If you have $10,000 in trading capital, you should not risk more than $100-$200 per trade. Calculate how many contracts you can trade while staying within this risk limit.

    7. Monitoring & Adjustment:

      • Track the Trade: Monitor the price action closely.
      • Adjust Stop-Loss: As the trade moves in your favor, consider moving your stop-loss to breakeven or into profit to lock in gains (trailing stop).
      • COT Updates: Monitor the weekly COT report for changes in trader positioning. If the divergence between commercials and speculators starts to narrow, it may be a sign to reduce your position or exit the trade.
      • Weather Updates: Monitor weather conditions. Extreme heat or cold in the PJM region can significantly impact demand and price.

    8. Exit Strategy:

      • Take-Profit Hit: Automatically exit the position when the take-profit order is triggered.
      • Stop-Loss Hit: Automatically exit the position when the stop-loss order is triggered.
      • Time Decay: As the expiration date of the futures contract approaches, consider exiting the position to avoid potential delivery obligations (if you don't intend to physically deliver or receive electricity).
      • COT Reversal: If the COT report indicates a reversal in the divergence between commercial and non-commercial traders, consider exiting the position, even if your take-profit or stop-loss hasn't been hit.

III. Example Scenario

Let's say it's June, and the price of PJM.PSEG_month_on_dap is trading at $45/MWh. You observe the following in the COT report:

  • Commercial traders have significantly increased their net short positions over the past few weeks, indicating they expect prices to decline.
  • Non-commercial traders have simultaneously increased their net long positions, suggesting bullish sentiment.
  • Open interest is rising.
  • Weather forecasts predict a relatively mild summer in the PJM region.

Based on this, you decide to initiate a short position (sell) at $45/MWh. You set a stop-loss order at $47/MWh (above a recent high) and a take-profit order at $42/MWh (based on support levels and the ATR). You calculate your position size to risk no more than 1% of your trading capital.

IV. Important Considerations & Risks

  • Electricity Market Complexity: Electricity markets are highly complex and influenced by numerous factors beyond the COT report (e.g., generation outages, transmission constraints, regulatory changes).
  • Nodal Specificity: The PJM.PSEG_month_on_dap contract is specific to the PSEG node. Local congestion issues and unexpected outages can significantly impact this node's price, even if the broader PJM market is stable.
  • Volatility: Electricity futures can be very volatile, leading to rapid price swings.
  • Liquidity: Liquidity can be lower than more widely traded commodities like crude oil or natural gas. This can make it more difficult to enter and exit positions at desired prices.
  • Delivery Obligations: Be aware of the delivery obligations associated with electricity futures contracts. If you hold a contract through expiration, you may be required to physically deliver or receive electricity (unless you offset the position).
  • COT Report is Lagging: The COT report is released with a delay (typically Friday for the previous Tuesday's data). The information is not real-time.
  • Commercial Trader Intent: While commercial traders are generally considered to be informed, they can still be wrong about market direction.

V. Tools and Resources

  • CFTC Website: For accessing the COT report.
  • Brokerage Platform: Your brokerage platform should provide price charts, order entry, and risk management tools.
  • Financial Data Providers: Companies like Bloomberg, Refinitiv, or others offer more in-depth COT data analysis tools and historical data.
  • Weather Services: Access reliable weather forecasts for the PJM region.
  • PJM Website: The PJM Interconnection website provides information about grid operations and market conditions.

VI. Disclaimer:

This is a sample trading strategy and should not be considered financial advice. Trading futures involves significant risk of loss. You should carefully consider your own risk tolerance and financial situation before trading. Consult with a qualified financial advisor before making any investment decisions. Always do your own research and due diligence. The information provided here is for educational purposes only.