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

PJM.PSEG_month_off_dap (Non-Commercial)

13-Wk Max 9,426 4,440 180 2,540 8,385
13-Wk Min 8,780 470 -536 -1,995 4,395
13-Wk Avg 8,983 2,285 -40 73 6,699
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 8,835 4,440 50 800 4,395 -14.58% 80,556
May 6, 2025 8,785 3,640 -45 -260 5,145 4.36% 78,760
April 29, 2025 8,830 3,900 25 540 4,930 -9.46% 81,109
April 22, 2025 8,805 3,360 0 350 5,445 -6.04% 79,935
April 15, 2025 8,805 3,010 25 2,540 5,795 -30.26% 78,360
April 8, 2025 8,780 470 -390 -315 8,310 -0.89% 74,152
April 1, 2025 9,170 785 100 -180 8,385 3.45% 76,438
March 25, 2025 9,070 965 0 -110 8,105 1.38% 76,850
March 18, 2025 9,070 1,075 180 -50 7,995 2.96% 77,886
March 11, 2025 8,890 1,125 0 180 7,765 -2.27% 77,002
March 4, 2025 8,890 945 -536 -1,050 7,945 6.92% 76,847
February 25, 2025 9,426 1,995 0 -1,995 7,431 36.70% 79,430
February 18, 2025 9,426 3,990 75 500 5,436 -7.25% 76,120

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 COT-based trading strategy for PJM.PSEG_month_off_peak electricity futures (NODX) specifically tailored for retail traders and market investors. This strategy will incorporate insights from the Commitment of Traders (COT) report and consider the unique characteristics of the electricity market.

I. Understanding the PJM.PSEG_month_off_dap Electricity Market and its Drivers

Before diving into the COT-based strategy, it's crucial to understand the fundamentals driving PJM.PSEG_month_off_peak electricity prices.

  • PJM Interconnection: PJM is a Regional Transmission Organization (RTO) that coordinates the movement of wholesale electricity in all or parts of 13 states and the District of Columbia. It's one of the largest electricity markets in the world.
  • PSEG: Public Service Enterprise Group is a major energy company that operates within the PJM footprint. The PSEG zone is thus a part of the PJM footprint.
  • Nodal Pricing (Locational Marginal Pricing - LMP): PJM uses nodal pricing, meaning that electricity prices vary based on location due to transmission constraints, congestion, and local supply/demand dynamics. "DAP" typically refers to Day-Ahead Pricing.
  • Off-Peak: This refers to electricity delivered during hours of lower demand, typically overnight, weekends, and holidays. Off-peak prices are generally lower than on-peak prices. The 'month' aspect signifies that the futures contract covers a specific month of off-peak electricity delivery.
  • Key Price Drivers:
    • Natural Gas Prices: Natural gas is a primary fuel source for electricity generation in the PJM region. Gas prices have a strong correlation with electricity prices.
    • Weather: Extreme temperatures (heatwaves or cold snaps) increase electricity demand for cooling or heating, impacting prices. Weather forecasts are crucial.
    • Nuclear Power Outages: Unplanned outages at nuclear power plants can reduce electricity supply and push prices higher.
    • Renewable Energy Output: The amount of electricity generated by wind and solar power can affect prices, especially during off-peak hours when demand is lower.
    • Transmission Constraints: Bottlenecks in the transmission grid can limit the flow of electricity and create price differences between locations.
    • Demand Forecasts: PJM publishes demand forecasts that can influence market sentiment.

II. The Commitment of Traders (COT) Report

The COT report, published weekly by the CFTC, provides a breakdown of open interest (outstanding futures contracts) held by different categories of traders:

  • Commercial Traders (Hedgers): These are entities that use the futures market to hedge their exposure to price fluctuations. In the electricity market, this includes power generators, utilities, and large industrial consumers. They are generally considered to be well-informed about fundamental market conditions.
  • Non-Commercial Traders (Speculators): This category includes large speculators like hedge funds and commodity trading advisors (CTAs). They trade futures contracts for profit and are not directly involved in the physical commodity.
  • Non-Reportable Positions: These are small traders whose positions are below the reporting threshold.

III. COT-Based Trading Strategy for PJM.PSEG_month_off_dap (NODX)

Here's a strategy that combines COT data with fundamental analysis:

A. Data Collection and Analysis:

  1. COT Report Retrieval: Download the weekly COT report from the CFTC website. Specifically, look for the data on NODX (PJM.PSEG_month_off_dap).
  2. COT Data Tracking: Create a spreadsheet or use a charting platform to track the following COT data over time:
    • Net positions of Commercial Traders.
    • Net positions of Non-Commercial Traders.
    • Total Open Interest.
  3. COT Data Interpretation:
    • Commercial Traders' Sentiment: Pay close attention to the net position of commercial traders.
      • Large Net Short Position: Indicates commercial traders are hedging against lower prices. This could suggest that fundamental factors are pointing towards a potential price decline.
      • Large Net Long Position: Indicates commercial traders are hedging against higher prices. This could suggest that fundamental factors are pointing towards a potential price increase.
    • Non-Commercial Traders' Sentiment: Monitor the net position of non-commercial traders.
      • Large Net Long Position: Indicates speculators are bullish on electricity prices. This can amplify price trends but can also be a sign of overbought conditions.
      • Large Net Short Position: Indicates speculators are bearish on electricity prices. This can amplify price trends but can also be a sign of oversold conditions.
    • Open Interest:
      • Rising Open Interest: Confirms the strength of the current price trend. If prices are rising and open interest is also rising, it suggests that more participants are entering the market, reinforcing the upward trend.
      • Falling Open Interest: Suggests a weakening price trend. If prices are rising but open interest is falling, it could be a sign that the rally is losing steam.
      • Divergence: COT signals should be taken more seriously if they're supported by the movement of open interest (e.g. a big position combined with a trend of rising open interest)
  4. Historical Data: Pull historical price data for the NODX contract. Compare these price trends to the historical COT data to see if you can identify trends and correlations.
  5. Spreadsheets Create a custom spreadsheet that contains:
    • Historical Price of NODX contract
    • Commercial Trader Net Position
    • Non-Commercial Trader Net Position
    • Open Interest
    • 5-day, 10-day, and 20-day Moving Averages
  6. Correlation Use excel to create a correlation matrix between the Commercial Trader Net Position, Non-Commercial Trader Net Position, and Open Interest. This helps establish if there is a relationship to historical prices.

B. Fundamental Analysis:

  1. Natural Gas Prices: Track natural gas prices (e.g., Henry Hub) and analyze their impact on electricity prices. Look for correlations between gas price movements and NODX price movements.
  2. Weather Forecasts: Monitor weather forecasts for the PJM region (especially the PSEG zone). Pay attention to temperature predictions, especially extreme temperatures. Use weather data providers.
  3. PJM System Operations Data: Review PJM's website for real-time system information, including:
    • Total system demand.
    • Available generation capacity.
    • Transmission constraints.
    • Outages of generating units.
  4. News and Announcements: Stay informed about news events that could impact the electricity market, such as:
    • Regulatory changes.
    • New power plant construction.
    • Environmental regulations.
    • Geopolitical events affecting energy markets.

C. Trading Signals and Rules:

  1. Confirmation: Never rely solely on the COT report. Use it as a confirmation signal in conjunction with fundamental analysis and technical analysis (price charts, moving averages, etc.).
  2. Commercial Trader Confirmation:
    • Bullish Signal: If commercial traders are building a net long position, and the fundamentals (e.g., rising natural gas prices, hot weather forecast) also point towards higher electricity prices, consider a long (buy) position in NODX.
    • Bearish Signal: If commercial traders are building a net short position, and the fundamentals (e.g., falling natural gas prices, mild weather forecast) also point towards lower electricity prices, consider a short (sell) position in NODX.
  3. Speculative Sentiment Extremes:
    • Contrarian Indicator: When speculators are heavily net long (overbought), it could be a signal that a correction is coming, especially if the fundamentals are not supportive. Consider a short position.
    • Contrarian Indicator: When speculators are heavily net short (oversold), it could be a signal that a rally is coming, especially if the fundamentals are improving. Consider a long position.
  4. Trend Following: If the COT data and fundamentals align with an established price trend, consider trading in the direction of the trend. For example, if prices are rising, commercial traders are net long, and the fundamentals are bullish, consider adding to your long position.
  5. COT Divergence: Be wary of divergences between price action and the COT report. For example, if prices are rising but commercial traders are reducing their net long positions, it could be a sign that the rally is unsustainable.

D. Risk Management:

  1. Position Sizing: Never risk more than a small percentage of your trading capital on any single trade (e.g., 1-2%).
  2. Stop-Loss Orders: Always use stop-loss orders to limit your potential losses. Place stop-loss orders based on technical analysis (e.g., below a support level or above a resistance level) or a percentage of your entry price.
  3. Profit Targets: Set realistic profit targets based on technical analysis or fundamental price projections.
  4. Volatility: Electricity markets can be volatile. Be aware of the potential for large price swings and adjust your position size accordingly.
  5. Time Decay: Futures contracts have an expiration date. Be mindful of the time decay as the contract approaches expiration. Consider rolling your position to the next contract month to avoid being forced to take delivery of the physical commodity.
  6. Liquidity: Electricity futures markets may have lower liquidity than other commodity markets, especially during off-peak hours. Use limit orders to ensure that you get the price you want.

E. Trading Plan Example

|Step| Action| Description| |-----|-----|-----| |1|COT Report|The most recent COT report shows that Commercial Traders have significantly increased their net short positions on PJM.PSEG_month_off_peak| |2|Fundamental Analysis|A cold front is forecasted to pass through the PJM PSEG area in a few days which will increase demand for electricity| |3|Technical Analysis|Price has been consistently trading in a channel and has reached the upper resistance| |4|Entry |Open a small short position on NODX contracts| |5|Stop Loss|Place stop loss at 5% premium than open position price| |6|Take Profit| Place take profit at lower trend channel| |7|Monitor |Monitor electricity demand numbers, weather forecast, and NODX future prices throughout the trade |

IV. Important Considerations for Retail Traders and Market Investors:

  • Capital Requirements: Trading commodity futures requires a significant amount of capital due to margin requirements. Make sure you understand the margin requirements for NODX contracts before you start trading.
  • Market Knowledge: A thorough understanding of the electricity market fundamentals, PJM operations, and nodal pricing is essential for success.
  • Time Commitment: Monitoring the electricity market, COT reports, and news events requires a significant time commitment.
  • Risk Tolerance: Commodity futures trading is inherently risky. Only trade with capital you can afford to lose.
  • Education: Continuously educate yourself about the electricity market and trading strategies.
  • Simulation/Paper Trading: Before risking real money, practice your trading strategy using a demo account or paper trading platform.
  • Professional Advice: Consider consulting with a financial advisor or experienced commodity trader for personalized advice.

V. Limitations:

  • COT Data is Lagging: The COT report is released weekly, so the data is already a few days old by the time it's available. Market conditions can change rapidly.
  • Correlation is Not Causation: Just because the COT data correlates with price movements does not mean that the COT data is causing the price movements.
  • Market Complexity: The electricity market is complex and influenced by numerous factors. The COT report is just one piece of the puzzle.

VI. Disclaimer:

This trading strategy is for educational purposes only and should not be considered financial advice. Trading commodity futures involves substantial risk of loss. You are solely responsible for your trading decisions. Consult with a qualified financial advisor before making any investment decisions.

By combining the COT report with sound fundamental analysis, risk management, and a deep understanding of the electricity market, retail traders and market investors can potentially improve their trading outcomes in the PJM.PSEG_month_off_peak electricity futures market. However, always remember that there are no guarantees of success, and risk management is paramount.