Back to COT Dashboard
Market Sentiment
Neutral (Overbought)
Based on the latest 13 weeks of non-commercial positioning data. ℹ️

ERCOT.HB_NORTH_month_7x8_rtp (Non-Commercial)

13-Wk Max 8,500 0 600 0 8,500
13-Wk Min 7,350 0 0 0 7,350
13-Wk Avg 7,764 0 192 0 7,764
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 8,500 0 0 0 8,500 0.00% 38,390
May 6, 2025 8,500 0 550 0 8,500 6.92% 38,490
April 29, 2025 7,950 0 600 0 7,950 8.16% 40,515
April 22, 2025 7,350 0 0 0 7,350 0.00% 39,215
April 15, 2025 7,350 0 0 0 7,350 0.00% 39,215
April 8, 2025 7,350 0 0 0 7,350 0.00% 38,615
April 1, 2025 7,350 0 0 0 7,350 0.00% 39,805

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

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

🧠 How It Works
  • Recent Trend Detection: Tracks net position and rate of change (ROC) over the last 13 weeks.
  • Overbought/Oversold Check: Compares current net positions to a 1-year range using percentiles.
  • Strength Confirmation: Validates if long or short positions are dominant enough for a signal.
✅ Signal Criteria
Condition Signal
Net ↑ for 13+ weeks AND ROC ↑ for 13+ weeks AND strong long dominance Buy
Net ↓ for 13+ weeks AND ROC ↓ for 13+ weeks AND strong short dominance Sell
Net in top 20% of 1-year range AND net uptrend ≥ 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.

Trading Strategy for ERCOT.HB_NORTH_month_7x8_rtp Electricity Futures (NODX) Based on COT Report Analysis

This trading strategy outlines how a retail trader or market investor can leverage the Commitment of Traders (COT) report to inform trading decisions in the ERCOT.HB_NORTH_month_7x8_rtp electricity futures contract (NODX) traded on the Nodal Exchange. It's crucial to remember that electricity prices are highly volatile and sensitive to weather patterns, grid reliability, and regulatory changes. This strategy should be used as a component of a broader, well-researched trading plan.

I. Understanding the Fundamentals of ERCOT and the 7x8 Contract:

  • ERCOT (Electric Reliability Council of Texas): ERCOT is the independent system operator (ISO) for the Texas Interconnection, managing the flow of electricity to more than 26 million Texas customers – representing about 90 percent of the state's electric load. Understanding ERCOT's market dynamics, grid congestion patterns, and real-time electricity prices is crucial.
  • HB_NORTH (Houston Hub): HB_NORTH is a specific hub within ERCOT's grid. Location matters because of congestion and transmission constraints. Prices at different hubs can diverge due to these constraints.
  • month_7x8: This indicates a monthly contract that covers the 7x8 hours. This signifies the peak load hours, typically weekdays (Monday-Friday) from 7:00 AM to 10:00 PM. Understanding the historical price action and expected demand during these hours for the specified month is critical.
  • RTP (Real-Time Price): This contract is based on the real-time prices at the HB_NORTH node. This means the contract settles based on the average real-time price of electricity during the defined hours.

II. Understanding the Commitment of Traders (COT) Report:

The COT report provides a breakdown of positions held by different trader classifications in futures markets. The key categories for our strategy are:

  • Commercial Traders (Hedgers): Primarily electricity generators, retailers, and large consumers who use futures to hedge their physical electricity positions. Their primary motivation is to mitigate price risk, not speculative profit.
  • Non-Commercial Traders (Large Speculators): These are typically hedge funds, commodity trading advisors (CTAs), and other large investors who trade futures for profit.
  • Non-Reportable Positions (Small Speculators): Smaller traders whose positions are below the reporting threshold. While we don't have specific data on them, large shifts in this category can sometimes indicate a growing trend among retail traders.

III. Data Sources and Tools:

  • CFTC Website: The official source for the COT report. Downloadable data is available in various formats (e.g., Excel).
  • Nodal Exchange Website: Information on contract specifications, real-time prices, and historical data.
  • ERCOT Website: Access to grid conditions, load forecasts, outage information, and market reports.
  • Trading Platform: A reliable trading platform with access to electricity futures and charting tools.
  • Spreadsheet Software (Excel, Google Sheets): Essential for analyzing COT data and creating charts.

IV. Trading Strategy Based on COT Report Analysis:

This strategy focuses on identifying potential shifts in sentiment among commercial and non-commercial traders. Electricity is fundamentally different from many other commodities. Seasonality and short-term weather forecasts heavily impact price action. Therefore, combine COT analysis with a robust understanding of weather patterns and ERCOT grid conditions.

A. Key COT Ratios and Indicators:

  1. Commercial Net Position:

    • Interpretation: A large net short position among commercial traders suggests they are hedging against potentially lower electricity prices (e.g., anticipating abundant generation or lower demand). A large net long position suggests they are hedging against potentially higher electricity prices (e.g., anticipating generation shortages or higher demand).
    • Trading Signal: Consider fading the trend. If commercials are heavily short, look for potential buying opportunities. If they are heavily long, consider potential selling opportunities. This is based on the premise that commercial traders are often right in the long run, and speculative trends can be overextended.

  2. Non-Commercial Net Position:

    • Interpretation: A large net long position among non-commercial traders suggests they are bullish on electricity prices. A large net short position suggests they are bearish.
    • Trading Signal: Look for confirmation with other indicators. If non-commercials are strongly bullish and the market is overbought (RSI > 70), consider taking profits or shorting. If they are strongly bearish and the market is oversold (RSI < 30), consider covering shorts or going long.

  3. Changes in Net Positions (Week-over-Week):

    • Interpretation: A significant increase in the net long position of non-commercials can signal growing bullish sentiment. A significant increase in the net short position can signal growing bearish sentiment. Look for divergences: if price is rising, but non-commercials are decreasing their long position, it could signal a weakening uptrend.
    • Trading Signal: Use this to identify potential trend reversals or accelerations. A sharp increase in commercial shorts alongside a price rally could be a bearish signal.

  4. Commercial Hedgers vs. Speculators - The "Smart Money" Divergence: Compare the positioning of commercial hedgers against the positioning of large speculators. If the two groups are moving in opposite directions, it can signal a potential shift in the market's direction. For example, if speculators are heavily long while hedgers are heavily short, it suggests the hedgers are anticipating prices to fall, and speculators may be in for a correction.

B. Trading Rules and Entry/Exit Points:

  • Trend Identification: Use moving averages (e.g., 50-day, 200-day) to determine the overall trend. Only take long positions when the price is above the moving average and short positions when it is below.
  • Entry Signal: Combine COT signals with technical indicators. For example:
    • Long Entry: Commercial traders decreasing their net short position (becoming less bearish), price above the 50-day moving average, and RSI below 40 (oversold).
    • Short Entry: Commercial traders increasing their net short position (becoming more bearish), price below the 50-day moving average, and RSI above 60 (overbought).
  • Stop-Loss Orders: Place stop-loss orders below the recent swing low for long positions and above the recent swing high for short positions. Electricity is very volatile; consider wider stops. A percentage-based stop is also a good choice, such as 1% or 2% of account equity.
  • Profit Targets: Use Fibonacci retracement levels or previous support/resistance levels to set profit targets. Consider a trailing stop to protect profits as the market moves in your favor.

C. Risk Management:

  • Position Sizing: Never risk more than 1-2% of your trading capital on any single trade. Electricity is volatile and unexpected outages or extreme weather events can cause significant price swings.
  • Diversification: Don't put all your eggs in one basket. Diversify your trading portfolio across different asset classes and commodities.
  • Leverage: Use leverage cautiously. Electricity futures can be highly leveraged, which can amplify both profits and losses.
  • Stay Informed: Continuously monitor ERCOT grid conditions, weather forecasts, and regulatory changes. These factors can have a significant impact on electricity prices.

V. Example Trade Scenario:

Let's say it's June, and you're analyzing the COT report for the ERCOT.HB_NORTH_July_7x8_rtp contract.

  • COT Report Data:
    • Commercial Traders: Net short position is significantly higher than the historical average.
    • Non-Commercial Traders: Net long position is also high, but slightly decreasing week-over-week.
  • Technical Analysis: The price is trading below the 50-day moving average, and the RSI is at 65.
  • Fundamental Analysis: Weather forecasts predict moderate temperatures for July, suggesting lower electricity demand than initially expected.
  • Trading Decision: This combination of factors suggests a potential short opportunity. The commercials are heavily short (expecting lower prices), speculators are starting to reduce their long positions, technical analysis indicates a downtrend, and the fundamental outlook is bearish.
  • Entry: Enter a short position when the price breaks below a recent swing low, with a stop-loss order placed above the swing high.
  • Exit: Set a profit target at a Fibonacci retracement level or a previous support level.

VI. Important Considerations:

  • Data Lag: The COT report is released with a delay (usually on Friday for the data ending the previous Tuesday). Market conditions can change significantly in the interim.
  • Market Manipulation: While less common, large players could potentially manipulate the market, causing temporary distortions in price and COT data.
  • Black Swan Events: Unexpected events, such as major grid outages, extreme weather events, or significant regulatory changes, can invalidate any trading strategy. Be prepared to adjust your positions quickly.
  • Cost of Carry: Consider storage costs and the cost of financing when analyzing electricity futures.
  • Liquidity: Ensure the contract you're trading has sufficient liquidity to enter and exit positions efficiently. Low liquidity can lead to slippage.
  • Seasonality: Electricity demand and prices are heavily influenced by seasonality. For example, prices are typically higher in the summer due to increased air conditioning demand.

VII. Refining the Strategy:

  • Backtesting: Test your trading strategy on historical data to evaluate its performance.
  • Paper Trading: Practice your strategy with simulated trading before risking real capital.
  • Continuous Learning: Stay up-to-date on ERCOT market dynamics, regulatory changes, and advancements in trading technology.

VIII. Disclaimer:

This trading strategy is for informational purposes only and should not be considered financial advice. Trading electricity futures involves significant risks, and you could lose money. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions. The electricity market is particularly complex, and the information provided here should be viewed as a starting point for further investigation.