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

PJM TRI-RECs CLASS 1 Vin 2021 (Non-Commercial)

13-Wk Max 12,364 3,750 100 0 8,614
13-Wk Min 7,833 3,750 -3,220 0 4,083
13-Wk Avg 9,134 3,750 -433 0 5,384
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 28, 2019 8,033 3,750 100 0 4,283 2.39% 26,325
May 21, 2019 7,933 3,750 0 0 4,183 0.00% 25,325
May 14, 2019 7,933 3,750 100 0 4,183 2.45% 25,325
May 7, 2019 7,833 3,750 -461 0 4,083 -10.15% 25,175
April 30, 2019 8,294 3,750 0 0 4,544 0.00% 26,823
April 23, 2019 8,294 3,750 -850 0 4,544 -15.76% 26,723
April 16, 2019 9,144 3,750 0 0 5,394 0.00% 25,623
April 9, 2019 9,144 3,750 -3,220 0 5,394 -37.38% 25,623
April 2, 2019 12,364 3,750 0 0 8,614 0.00% 28,843
March 26, 2019 12,364 3,750 0 0 8,614 0.00% 28,693

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for POLLUTION

Comprehensive Guide to COT Reports for Commodity Natural Resources Markets

1. Introduction to COT Reports

What are COT Reports?

The Commitments of Traders (COT) reports are weekly publications released by the U.S. Commodity Futures Trading Commission (CFTC) that show the positions of different types of traders in U.S. futures markets, including natural resources commodities such as oil, natural gas, gold, silver, and agricultural products.

Historical Context

COT reports have been published since the 1920s, but the modern format began in 1962. Over the decades, the reports have evolved to provide more detailed information about market participants and their positions.

Importance for Natural Resource Investors

COT reports are particularly valuable for natural resource investors and traders because they:

  • Provide transparency into who holds positions in commodity markets
  • Help identify potential price trends based on positioning changes
  • Show how different market participants are reacting to fundamental developments
  • Serve as a sentiment indicator for commodity markets

Publication Schedule

COT reports are released every Friday at 3:30 p.m. Eastern Time, showing positions as of the preceding Tuesday. During weeks with federal holidays, the release may be delayed until Monday.

2. Understanding COT Report Structure

Types of COT Reports

The CFTC publishes several types of reports:

  1. Legacy COT Report: The original format classifying traders as Commercial, Non-Commercial, and Non-Reportable.
  2. Disaggregated COT Report: Offers more detailed breakdowns, separating commercials into producers/merchants and swap dealers, and non-commercials into managed money and other reportables.
  3. Supplemental COT Report: Focuses on 13 select agricultural commodities with additional index trader classifications.
  4. Traders in Financial Futures (TFF): Covers financial futures markets.

For natural resource investors, the Disaggregated COT Report generally provides the most useful information.

Data Elements in COT Reports

Each report contains:

  • Open Interest: Total number of outstanding contracts for each commodity
  • Long and Short Positions: Broken down by trader category
  • Spreading: Positions held by traders who are both long and short in different contract months
  • Changes: Net changes from the previous reporting period
  • Percentages: Proportion of open interest held by each trader group
  • Number of Traders: Count of traders in each category

3. Trader Classifications

Legacy Report Classifications

  1. Commercial Traders ("Hedgers"):
    • Primary business involves the physical commodity
    • Use futures to hedge price risk
    • Include producers, processors, and merchants
    • Example: Oil companies hedging future production
  2. Non-Commercial Traders ("Speculators"):
    • Do not have business interests in the physical commodity
    • Trade for investment or speculative purposes
    • Include hedge funds, CTAs, and individual traders
    • Example: Hedge funds taking positions based on oil price forecasts
  3. Non-Reportable Positions ("Small Traders"):
    • Positions too small to meet reporting thresholds
    • Typically represent retail traders and smaller entities
    • Considered "noise traders" by some analysts

Disaggregated Report Classifications

  1. Producer/Merchant/Processor/User:
    • Entities that produce, process, pack, or handle the physical commodity
    • Use futures markets primarily for hedging
    • Example: Gold miners, oil producers, refineries
  2. Swap Dealers:
    • Entities dealing primarily in swaps for commodities
    • Hedging swap exposures with futures contracts
    • Often represent positions of institutional investors
  3. Money Managers:
    • Professional traders managing client assets
    • Include CPOs, CTAs, hedge funds
    • Primarily speculative motives
    • Often trend followers or momentum traders
  4. Other Reportables:
    • Reportable traders not in above categories
    • Example: Trading companies without physical operations
  5. Non-Reportable Positions:
    • Same as in the Legacy report
    • Small positions held by retail traders

Significance of Each Classification

Understanding the motivations and behaviors of each trader category helps interpret their position changes:

  • Producers/Merchants: React to supply/demand fundamentals and often trade counter-trend
  • Swap Dealers: Often reflect institutional flows and longer-term structural positions
  • Money Managers: Tend to be trend followers and can amplify price movements
  • Non-Reportables: Sometimes used as a contrarian indicator (small traders often wrong at extremes)

4. Key Natural Resource Commodities

Energy Commodities

  1. Crude Oil (WTI and Brent)
    • Reporting codes: CL (NYMEX), CB (ICE)
    • Key considerations: Seasonal patterns, refinery demand, geopolitical factors
    • Notable COT patterns: Producer hedging often increases after price rallies
  2. Natural Gas
    • Reporting code: NG (NYMEX)
    • Key considerations: Extreme seasonality, weather sensitivity, storage reports
    • Notable COT patterns: Commercials often build hedges before winter season
  3. Heating Oil and Gasoline
    • Reporting codes: HO, RB (NYMEX)
    • Key considerations: Seasonal demand patterns, refinery throughput
    • Notable COT patterns: Refiners adjust hedge positions around maintenance periods

Precious Metals

  1. Gold
    • Reporting code: GC (COMEX)
    • Key considerations: Inflation expectations, currency movements, central bank buying
    • Notable COT patterns: Commercial shorts often peak during price rallies
  2. Silver
    • Reporting code: SI (COMEX)
    • Key considerations: Industrial vs. investment demand, gold ratio
    • Notable COT patterns: More volatile positioning than gold, managed money swings
  3. Platinum and Palladium
    • Reporting codes: PL, PA (NYMEX)
    • Key considerations: Auto catalyst demand, supply constraints
    • Notable COT patterns: Smaller markets with potentially more concentrated positions

Base Metals

  1. Copper
    • Reporting code: HG (COMEX)
    • Key considerations: Global economic growth indicator, construction demand
    • Notable COT patterns: Producer hedging often increases during supply surpluses
  2. Aluminum, Nickel, Zinc (COMEX/LME)
    • Note: CFTC reports cover U.S. exchanges only
    • Key considerations: Manufacturing demand, energy costs for production
    • Notable COT patterns: Limited compared to LME positioning data

Agricultural Resources

  1. Lumber
    • Reporting code: LB (CME)
    • Key considerations: Housing starts, construction activity
    • Notable COT patterns: Producer hedging increases during price spikes
  2. Cotton
    • Reporting code: CT (ICE)
    • Key considerations: Global textile demand, seasonal growing patterns
    • Notable COT patterns: Merchant hedging follows harvest cycles

5. Reading and Interpreting COT Data

Key Metrics to Monitor

  1. Net Positions
    • Definition: Long positions minus short positions for each trader category
    • Calculation: Net Position = Long Positions - Short Positions
    • Significance: Shows overall directional bias of each group
  2. Position Changes
    • Definition: Week-over-week changes in positions
    • Calculation: Current Net Position - Previous Net Position
    • Significance: Identifies new money flows and sentiment shifts
  3. Concentration Ratios
    • Definition: Percentage of open interest held by largest traders
    • Significance: Indicates potential market dominance or vulnerability
  4. Commercial/Non-Commercial Ratio
    • Definition: Ratio of commercial to non-commercial positions
    • Calculation: Commercial Net Position / Non-Commercial Net Position
    • Significance: Highlights potential divergence between hedgers and speculators
  5. Historical Percentiles
    • Definition: Current positions compared to historical ranges
    • Calculation: Typically 1-3 year lookback periods
    • Significance: Identifies extreme positioning relative to history

Basic Interpretation Approaches

  1. Trend Following with Managed Money
    • Premise: Follow the trend of managed money positions
    • Implementation: Go long when managed money increases net long positions
    • Rationale: Managed money often drives momentum in commodity markets
  2. Commercial Hedging Analysis
    • Premise: Commercials are "smart money" with fundamental insight
    • Implementation: Look for divergences between price and commercial positioning
    • Rationale: Commercials often take counter-trend positions at market extremes
  3. Extreme Positioning Identification
    • Premise: Extreme positions often precede market reversals
    • Implementation: Identify when any group reaches historical extremes (90th+ percentile)
    • Rationale: Crowded trades must eventually unwind
  4. Divergence Analysis
    • Premise: Divergences between trader groups signal potential turning points
    • Implementation: Watch when commercials and managed money move in opposite directions
    • Rationale: Opposing forces creating potential market friction

Visual Analysis Examples

Typical patterns to watch for:

  1. Bull Market Setup:
    • Managed money net long positions increasing
    • Commercial short positions increasing (hedging against higher prices)
    • Price making higher highs and higher lows
  2. Bear Market Setup:
    • Managed money net short positions increasing
    • Commercial long positions increasing (hedging against lower prices)
    • Price making lower highs and lower lows
  3. Potential Reversal Pattern:
    • Price making new highs/lows
    • Position extremes across multiple trader categories
    • Changes in positioning not confirming price moves (divergence)

6. Using COT Reports in Trading Strategies

Fundamental Integration Strategies

  1. Supply/Demand Confirmation
    • Approach: Use COT data to confirm fundamental analysis
    • Implementation: Check if commercials' positions align with known supply/demand changes
    • Example: Increasing commercial shorts in natural gas despite falling inventories could signal hidden supply
  2. Commercial Hedging Cycle Analysis
    • Approach: Track seasonal hedging patterns of producers
    • Implementation: Create yearly overlay charts of producer positions
    • Example: Oil producers historically increase hedging in Q2, potentially pressuring prices
  3. Index Roll Impact Assessment
    • Approach: Monitor position changes during index fund roll periods
    • Implementation: Track swap dealer positions before/after rolls
    • Example: Energy contracts often see price pressure during standard roll periods

Technical Integration Strategies

  1. COT Confirmation of Technical Patterns
    • Approach: Use COT data to validate chart patterns
    • Implementation: Confirm breakouts with appropriate positioning changes
    • Example: Gold breakout with increasing managed money longs has higher probability
  2. COT-Based Support/Resistance Levels
    • Approach: Identify price levels where significant position changes occurred
    • Implementation: Mark price points of major position accumulation
    • Example: Price levels where commercials accumulated large positions often act as support
  3. Sentiment Extremes as Contrarian Signals
    • Approach: Use extreme positioning as contrarian indicators
    • Implementation: Enter counter-trend when positions reach historical extremes (90th+ percentile)
    • Example: Enter long gold when managed money short positioning reaches 95th percentile historically

Market-Specific Strategies

  1. Energy Market Strategies
    • Crude Oil: Monitor producer hedging relative to current term structure
    • Natural Gas: Analyze commercial positioning ahead of storage injection/withdrawal seasons
    • Refined Products: Track seasonal changes in dealer/refiner positioning
  2. Precious Metals Strategies
    • Gold: Monitor swap dealer positioning as proxy for institutional sentiment
    • Silver: Watch commercial/managed money ratio for potential squeeze setups
    • PGMs: Analyze producer hedging for supply insights
  3. Base Metals Strategies
    • Copper: Track managed money positioning relative to global growth metrics
    • Aluminum/Nickel: Monitor producer hedging for production cost signals

Strategy Implementation Framework

  1. Data Collection and Processing
    • Download weekly COT data from CFTC website
    • Calculate derived metrics (net positions, changes, ratios)
    • Normalize data using Z-scores or percentile ranks
  2. Signal Generation
    • Define position thresholds for each trader category
    • Establish change-rate triggers
    • Create composite indicators combining multiple COT signals
  3. Trade Setup
    • Entry rules based on COT signals
    • Position sizing based on signal strength
    • Risk management parameters
  4. Performance Tracking
    • Track hit rate of COT-based signals
    • Monitor lead/lag relationship between positions and price
    • Regularly recalibrate thresholds based on performance

7. Advanced COT Analysis Techniques

Statistical Analysis Methods

  1. Z-Score Analysis
    • Definition: Standardized measure of position extremes
    • Calculation: Z-score = (Current Net Position - Average Net Position) / Standard Deviation
    • Application: Identify positions that are statistically extreme
    • Example: Gold commercials with Z-score below -2.0 often mark potential bottoms
  2. Percentile Ranking
    • Definition: Position ranking relative to historical range
    • Calculation: Current position's percentile within 1-3 year history
    • Application: More robust than Z-scores for non-normal distributions
    • Example: Natural gas managed money in 90th+ percentile often precedes price reversals
  3. Rate-of-Change Analysis
    • Definition: Speed of position changes rather than absolute levels
    • Calculation: Weekly RoC = (Current Position - Previous Position) / Previous Position
    • Application: Identify unusual accumulation or liquidation
    • Example: Crude oil swap dealers increasing positions by >10% in a week often signals institutional flows

Multi-Market Analysis

  1. Intermarket COT Correlations
    • Approach: Analyze relationships between related commodity positions
    • Implementation: Create correlation matrices of trader positions across markets
    • Example: Gold/silver commercial positioning correlation breakdown can signal sector rotation
  2. Currency Impact Assessment
    • Approach: Analyze COT data in currency futures alongside commodities
    • Implementation: Track correlations between USD positioning and commodity positioning
    • Example: Extreme USD short positioning often coincides with commodity long positioning
  3. Cross-Asset Confirmation
    • Approach: Verify commodity COT signals with related equity or bond positioning
    • Implementation: Compare energy COT data with energy equity positioning
    • Example: Divergence between oil futures positioning and energy equity positioning can signal sector disconnects

Machine Learning Applications

  1. Pattern Recognition Models
    • Approach: Train models to identify historical COT patterns preceding price moves
    • Implementation: Use classification algorithms to categorize current positioning
    • Example: Random forest models predicting 4-week price direction based on COT features
  2. Clustering Analysis
    • Approach: Group historical COT data to identify common positioning regimes
    • Implementation: K-means clustering of multi-dimensional COT data
    • Example: Identifying whether current gold positioning resembles bull or bear market regimes
  3. Predictive Modeling
    • Approach: Create forecasting models for future price movements
    • Implementation: Regression models using COT variables as features
    • Example: LSTM networks predicting natural gas price volatility from COT positioning trends

Advanced Visualization Techniques

  1. COT Heat Maps
    • Description: Color-coded visualization of position extremes across markets
    • Application: Quickly identify markets with extreme positioning
    • Example: Heat map showing all commodity markets with positioning in 90th+ percentile
  2. Positioning Clock
    • Description: Circular visualization showing position cycle status
    • Application: Track position cycles within commodities
    • Example: Natural gas positioning clock showing seasonal accumulation patterns
  3. 3D Surface Charts
    • Description: Three-dimensional view of positions, price, and time
    • Application: Identify complex patterns not visible in 2D
    • Example: Surface chart showing commercial crude oil hedger response to price changes over time

8. Limitations and Considerations

Reporting Limitations

  1. Timing Delays
    • Issue: Data reflects positions as of Tuesday, released Friday
    • Impact: Significant market moves can occur between reporting and release
    • Mitigation: Combine with real-time market indicators
  2. Classification Ambiguities
    • Issue: Some traders could fit in multiple categories
    • Impact: Classification may not perfectly reflect true market structure
    • Mitigation: Focus on trends rather than absolute values
  3. Threshold Limitations
    • Issue: Only positions above reporting thresholds are included
    • Impact: Incomplete picture of market, especially for smaller commodities
    • Mitigation: Consider non-reportable positions as context

Interpretational Challenges

  1. Correlation vs. Causation
    • Issue: Position changes may reflect rather than cause price moves
    • Impact: Following positioning blindly can lead to false signals
    • Mitigation: Use COT as confirmation rather than primary signal
  2. Structural Market Changes
    • Issue: Market participant behavior evolves over time
    • Impact: Historical relationships may break down
    • Mitigation: Use adaptive lookback periods and recalibrate regularly
  3. Options Positions Not Included
    • Issue: Standard COT reports exclude options positions
    • Impact: Incomplete view of market exposure, especially for hedgers
    • Mitigation: Consider using COT-CIT Supplemental reports for context
  4. Exchange-Specific Coverage
    • Issue: Reports cover only U.S. exchanges
    • Impact: Incomplete picture for globally traded commodities
    • Mitigation: Consider parallel data from other exchanges where available

Common Misinterpretations

  1. Assuming Commercials Are Always Right
    • Misconception: Commercial positions always lead price
    • Reality: Commercials can be wrong on timing and magnitude
    • Better approach: Look for confirmation across multiple signals
  2. Ignoring Position Size Context
    • Misconception: Absolute position changes are what matter
    • Reality: Position changes relative to open interest provide better context
    • Better approach: Normalize position changes by total open interest
  3. Over-Relying on Historical Patterns
    • Misconception: Historical extremes will always work the same way
    • Reality: Market regimes change, affecting positioning impact
    • Better approach: Adjust expectations based on current volatility regime
  4. Neglecting Fundamental Context
    • Misconception: COT data is sufficient standalone
    • Reality: Positioning often responds to fundamental catalysts
    • Better approach: Integrate COT analysis with supply/demand factors

Integration into Trading Workflow

  1. Weekly Analysis Routine
    • Friday: Review new COT data upon release
    • Weekend: Comprehensive analysis and strategy adjustments
    • Monday: Implement new positions based on findings
  2. Framework for Position Decisions
    • Primary signal: Identify extremes in relevant trader categories
    • Confirmation: Check for divergences with price action
    • Context: Consider fundamental backdrop
    • Execution: Define entry, target, and stop parameters
  3. Documentation Process
    • Track all COT-based signals in trading journal
    • Record hit/miss rate and profitability
    • Note market conditions where signals work best/worst
  4. Continuous Improvement
    • Regular backtest of signal performance
    • Adjustment of thresholds based on market conditions
    • Integration of new data sources as available

Case Studies: Practical Applications

  1. Natural Gas Winter Strategy
    • Setup: Monitor commercial positioning ahead of withdrawal season
    • Signal: Commercial net long position > 70th percentile
    • Implementation: Long exposure with technical price confirmation
    • Historical performance: Positive expectancy during 2015-2023 period
  2. Gold Price Reversal Strategy
    • Setup: Watch for extreme managed money positioning
    • Signal: Managed money net short position > 85th percentile historically
    • Implementation: Contrarian long position with tiered entry
    • Risk management: Stop loss at recent swing point
  3. Crude Oil Price Collapse Warning System
    • Setup: Monitor producer hedging acceleration
    • Signal: Producer short positions increasing by >10% over 4 weeks
    • Implementation: Reduce long exposure or implement hedging strategies
    • Application: Successfully flagged risk periods in 2014, 2018, and 2022

By utilizing these resources and implementing the strategies outlined in this guide, natural resource investors and traders can gain valuable insights from COT data to enhance their market analysis and decision-making processes.

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

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

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

Okay, let's break down a trading strategy for PJM TRI-RECs CLASS 1 Vin 2021 futures based on the Commitment of Traders (COT) report. Given the specific details, we'll need to make some generalizations since real-time, historical COT data for this specific contract and year is not publicly accessible to me. The general principles, however, remain the same.

Disclaimer: This is for informational purposes only and does not constitute financial advice. Trading futures carries significant risk, and you can lose money. Always conduct your own due diligence and consult with a qualified financial advisor before making any investment decisions.

I. Understanding the Basics

  • Commodity: Pollution (Represented by RECs): TRI-RECs (Tier 1 Renewable Energy Certificates) are tradable instruments representing the environmental benefits of renewable energy generation. They are bought by entities needing to meet renewable energy portfolio standards (RPS) or to voluntarily offset their carbon footprint.
  • Contract Unit: 100 MWh: Each contract represents 100 Megawatt-hours of renewable energy generation.
  • CFTC Market Code: IFED: This code helps identify the specific contract within the reporting requirements.
  • Market Exchange: ICE Futures Energy Division: The contract trades on ICE (Intercontinental Exchange).
  • PJM: PJM Interconnection The area is the geographical area where the renewable energy was generated and is eligible for use for compliance or voluntary purposes.
  • Vin 2021: Vintage Year 2021: This indicates the RECs were generated in the year 2021. RECs typically have a shelf life, and the vintage year impacts their usability and, therefore, their value.
  • COT Report: The COT report, published weekly by the CFTC (Commodity Futures Trading Commission), breaks down the open interest (total number of outstanding contracts) in the futures market by various trader classifications. The primary classifications are:
    • Commercial Traders (Hedgers): These are entities directly involved in the underlying physical market (e.g., renewable energy generators, utilities). They use futures to hedge price risk.
    • Non-Commercial Traders (Large Speculators): These are primarily hedge funds, commodity trading advisors (CTAs), and other large institutional investors trading for profit.
    • Non-Reportable Positions (Small Speculators): This category includes retail traders and smaller entities whose positions are below the reporting threshold. Their data is not individually broken out in the COT report.

II. Trading Strategy: COT-Based Analysis for PJM TRI-RECs CLASS 1 Vin 2021

This strategy is based on the assumption that commercial hedgers (renewable energy generators and users) have better insight into the fundamental supply and demand dynamics of RECs than speculators. We will use the difference between the net positions of the commercial hedgers and those of large speculators as an indicator of the likely direction of prices.

1. Data Acquisition:

  • Ideally, you would download historical COT reports from the CFTC website. Unfortunately, getting highly granular, historical COT data for this specific contract and year requires potentially paying for data feeds or using specialized financial data services.
  • Since the contract is for 2021, there is little that can be done with COT analysis. However, this does not change the strategy.
  • Publicly Available Data: Look for any articles or reports on the REC market that may provide summary data on commercial vs. non-commercial positioning.

2. Key COT Report Metrics to Monitor:

  • Commercial Traders' Net Position: Calculate the net position of commercial traders (long positions minus short positions). A large net short position indicates that commercial hedgers are selling, likely anticipating lower prices or hedging existing REC production. A large net long position suggests they are buying, potentially anticipating higher prices or needing to fulfill their REC obligations.
  • Non-Commercial Traders' Net Position: Calculate the net position of large speculators (long positions minus short positions). A large net long position indicates that large speculators are bullish. A large net short position indicates that they are bearish.
  • Changes in Open Interest: Rising open interest generally confirms the strength of a trend. Falling open interest can signal that a trend is weakening.
  • Percentage of Open Interest: Express the net positions of commercials and non-commercials as a percentage of total open interest. This helps normalize the data and compare positions across different time periods.

3. Trading Signals (General Guidelines):

  • Commercials Net Short & Increasing: Potential Bearish Signal. If commercial traders are net short and increasing their short positions, it may indicate they expect REC prices to decline (e.g., due to increased renewable energy generation, lower compliance targets, or a change in market conditions). Consider a short position.
  • Commercials Net Long & Increasing: Potential Bullish Signal. If commercial traders are net long and increasing their long positions, it may indicate they expect REC prices to rise (e.g., due to increased demand, tighter compliance targets, or supply constraints). Consider a long position.
  • Divergence between Commercials and Non-Commercials: Stronger Signal. Look for situations where commercials and non-commercials have significantly opposing positions. For example:
    • Commercials are net short and non-commercials are net long: Stronger bearish signal.
    • Commercials are net long and non-commercials are net short: Stronger bullish signal.
  • Extreme Positioning: Identify historically extreme net long or net short positions by either group. These can be good indicators that a market correction is due. Look for potential trend reversals.

4. Entry and Exit Strategies:

  • Entry:
    • Confirmation: Don't rely solely on the COT report. Use it in conjunction with other technical indicators (e.g., moving averages, trendlines, RSI, MACD) and/or fundamental analysis of the REC market (e.g., RPS targets, regulatory changes, renewable energy capacity additions).
    • Candlestick Patterns: Look for candlestick patterns that confirm the COT signal.
    • Volume: Confirm the signal with increasing volume in the direction of the trade.
  • Exit (Risk Management):
    • Stop-Loss Orders: Always use stop-loss orders to limit potential losses. Place stop-loss orders based on volatility and your risk tolerance. A good strategy is to place the stop-loss order just below a recent swing low (for long positions) or just above a recent swing high (for short positions).
    • Profit Targets: Set profit targets based on technical analysis (e.g., resistance levels, Fibonacci extensions) or fundamental targets (e.g., anticipated REC price levels).
    • Trailing Stops: Consider using trailing stops to lock in profits as the market moves in your favor.
    • COT Report Changes: Monitor the COT report each week. If the commercial traders' positioning changes significantly, it may be a signal to adjust your position or exit the trade.

5. Example Scenario:

Let's say the COT report shows the following:

  • Commercial traders: Net short 1,000 contracts (increasing their short position).
  • Non-commercial traders: Net long 1,500 contracts.
  • Open interest: 5,000 contracts.

This suggests that commercial hedgers are bearish on REC prices, while large speculators are bullish. This divergence could signal a potential shorting opportunity. However, you would need to confirm this signal with other forms of technical and fundamental analysis before entering a trade.

6. Important Considerations and Limitations:

  • Lagging Indicator: The COT report is released with a delay (usually on Fridays for the previous Tuesday's data). This means the information is not real-time. Market conditions can change significantly between the reporting date and the time you act on the information.
  • Commercial Trader Motivation: The motivation of commercial traders can be complex. They may be hedging anticipated production, locking in profits, or fulfilling regulatory obligations. Their net positions may not always be a direct reflection of their price expectations.
  • Market Sentiment: The COT report doesn't capture overall market sentiment or news events that can impact REC prices.
  • Specific Contract Dynamics: The specific dynamics of the PJM TRI-RECs market (e.g., regulatory changes, supply constraints, demand fluctuations) can have a significant impact on prices, regardless of the COT report.
  • Liquidity: This specific futures contract for 2021 has little to no liquidity. COT data is not of any use.

7. Risk Management is Important.

Do not trade without a stop loss order.

Conclusion:

Using the COT report to trade PJM TRI-RECs futures can be a valuable tool, but it should not be used in isolation. It's crucial to combine COT analysis with technical analysis, fundamental analysis, and sound risk management principles. Remember that the COT report is a lagging indicator and that market conditions can change quickly. Due diligence and a well-defined trading plan are essential for success. Also, due to the contracts being for 2021, this data is not of use for future price discovery.

Good luck with your trading!