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Based on the latest 13 weeks of non-commercial positioning data. ℹī¸

MISO INDIANA HUB RT PEAK (Non-Commercial)

13-Wk Max 2,758 11,741 100 471 -8,454
13-Wk Min 2,000 10,554 -440 -746 -9,123
13-Wk Avg 2,392 11,106 -53 -30 -8,714
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹī¸ Open Int.
April 29, 2025 2,025 11,052 -125 321 -9,027 -5.20% 37,076
April 22, 2025 2,150 10,731 50 177 -8,581 -1.50% 36,936
April 15, 2025 2,100 10,554 100 -124 -8,454 2.58% 36,503
April 8, 2025 2,000 10,678 -440 -458 -8,678 0.21% 35,635
April 1, 2025 2,440 11,136 -30 125 -8,696 -1.81% 36,886
March 25, 2025 2,470 11,011 32 15 -8,541 0.20% 36,873
March 18, 2025 2,438 10,996 13 44 -8,558 -0.36% 36,680
March 11, 2025 2,425 10,952 -150 -746 -8,527 6.53% 36,111
March 4, 2025 2,575 11,698 -18 471 -9,123 -5.66% 37,842
February 25, 2025 2,593 11,227 31 -224 -8,634 2.87% 37,829
February 18, 2025 2,562 11,451 -4 294 -8,889 -3.47% 37,373
February 11, 2025 2,566 11,157 -192 -584 -8,591 4.36% 38,140
February 4, 2025 2,758 11,741 50 305 -8,983 -2.92% 39,673

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 â‰Ĩ 3 Neutral (Overbought)
Net in bottom 20% of 1-year range AND net downtrend â‰Ĩ 3 Neutral (Oversold)
None of the above conditions met Neutral
🧭 Trader Tips
  • Trend traders: Follow Buy/Sell signals when all trend and strength conditions align.
  • Contrarian traders: Use Neutral (Overbought/Oversold) flags to anticipate reversals.
  • Swing traders: Use sentiment as a filter to increase trade confidence.
Example:
Net positions rising, strong long dominance, in top 20% of historical range.
Result: Neutral (Overbought) — uptrend may be too crowded.
  • COT data is delayed (released on Friday, based on Tuesday's positions) - it's not real-time.
  • Combine with price action, FVG, liquidity, or technical indicators for best results.
  • Use percentile filters to avoid buying at extreme highs or selling at extreme lows.

Trading Strategy for MISO Indiana Hub RT Peak Electricity Futures (IFED) based on COT Report Analysis

This strategy outlines how a retail trader and market investor can leverage the Commitments of Traders (COT) report for trading MISO Indiana Hub RT Peak electricity futures (IFED) on the ICE Futures Energy Division.

Disclaimer: Trading electricity futures involves significant risk. This strategy is for educational purposes only and should not be considered financial advice. Conduct thorough research and consult with a financial professional before making any trading decisions.

I. Understanding the Market and the COT Report

  • MISO Indiana Hub RT Peak: This market represents the real-time, on-peak (typically daytime hours) electricity prices at the MISO Indiana Hub. Price volatility can be significant, influenced by factors like weather, demand, and power plant availability.

  • CFTC Market Code: IFED: Identifies the specific contract being traded.

  • COT Report: The COT report, published weekly by the CFTC, breaks down the open interest in futures and options contracts into different trader categories:

    • Commercial Traders (Hedgers): Entities that use the futures market to hedge against price risk associated with their underlying business (e.g., power generators, utilities).
    • Non-Commercial Traders (Large Speculators): Typically hedge funds, commodity trading advisors (CTAs), and other large institutional investors who trade for profit.
    • Small Speculators (Retail): Smaller traders who trade for profit, often less informed than the other groups. * Swap Dealers: Entities that facilitate commodity derivatives trading for clients. Their positioning can reflect client activity but is often a risk management hedge for their exposure.

  • Types of COT Reports:

    • Legacy Report: Shows long and short positions for Commercial and Non-Commercial traders.
    • Disaggregated Report: Breaks down Non-Commercial traders into "Managed Money" (hedge funds) and "Other Reportables". This is generally considered more informative.

II. Data Sources and Tools

  • CFTC Website: The official source for COT reports (cftc.gov). Downloadable in various formats.
  • Trading Platform with COT Charting: Many trading platforms offer tools to directly plot COT data alongside price charts.
  • Spreadsheet Software (e.g., Excel): Necessary for analyzing and visualizing COT data.
  • Reliable Source for Market News: Staying informed about factors affecting electricity prices (weather forecasts, power plant outages, etc.) is crucial.

III. Trading Strategy based on COT Report Analysis

This strategy focuses on identifying potential trend changes and confirmations based on the positioning of Commercial and Non-Commercial traders.

A. Trend Identification

  1. Price Trend: Establish the current price trend of the IFED futures contract using technical analysis (e.g., moving averages, trendlines, price patterns).

  2. Commercial Trader Positioning:

    • Strong Uptrend: Commercial traders generally increase their short positions (hedging against higher prices) in an uptrend. This is their normal behavior. However, a decrease in short positions may signal they believe the uptrend is nearing its end.
    • Strong Downtrend: Commercial traders generally increase their long positions (hedging against lower prices) in a downtrend. A decrease in long positions may indicate the downtrend is nearing its end.
    • Extreme Net Short Position (Commercials): When Commercials are historically net short, it could be an indicator that they are unwilling to short the market any further, signifying that the market is undervalued or near a bottom.
    • Extreme Net Long Position (Commercials): The opposite: When Commercials are historically net long, they may be unwilling to buy more, indicating an overvalued or near a top.

  3. Non-Commercial Trader Positioning:

    • Trend Following: Non-Commercial traders tend to follow the price trend. They typically increase their long positions in an uptrend and increase their short positions in a downtrend.
    • Changes in Positioning: Significant changes in Non-Commercial positioning against the prevailing trend can be a potential sign of a trend reversal.

B. Trade Signals

Important: Confirm all signals with other technical indicators and fundamental analysis.

  1. Trend Confirmation Signal:

    • Uptrend: Price makes new highs, Non-Commercial traders increase long positions, Commercial traders increase short positions (or decrease short positions at a slower rate than the price increase).
    • Downtrend: Price makes new lows, Non-Commercial traders increase short positions, Commercial traders increase long positions (or decrease long positions at a slower rate than the price decrease).
    • Action: Continue riding the trend with appropriate risk management (stop-loss orders).

  2. Potential Reversal Signal (Caution Required):

    • Uptrend Reversal: Price stalls or shows weakness (e.g., bearish price patterns), Non-Commercial traders decrease long positions, Commercial traders decrease short positions significantly. Look for divergence (price making new highs while Non-Commercial longs are decreasing).
    • Downtrend Reversal: Price shows signs of strength (e.g., bullish price patterns), Non-Commercial traders decrease short positions, Commercial traders decrease long positions significantly. Look for divergence (price making new lows while Non-Commercial shorts are decreasing).
    • Action: Exercise extreme caution. Consider reducing existing long positions or opening small short positions with tight stop-loss orders. Wait for further confirmation of the reversal.

  3. Commercials as an Oscillator (for range bound trading, less effective in strong trending markets):

    • Commercials Net Short Peak: Assuming relatively stable price conditions, When Commercials are at or near the maximum net short over the last 12 to 24 months it could signal that the price is near the upper end of a defined range. Sell strategy to take advantage of a price decline.
    • Commercials Net Long Peak: Assuming relatively stable price conditions, when Commercials are at or near the maximum net long over the last 12 to 24 months it could signal that the price is near the bottom end of a defined range. Buy strategy to take advantage of a price increase.

C. Risk Management

  • Stop-Loss Orders: Absolutely essential. Place stop-loss orders to limit potential losses. Base stop-loss placement on technical levels (e.g., support/resistance, recent swing lows/highs) and your risk tolerance.
  • Position Sizing: Never risk more than a small percentage of your trading capital on any single trade (e.g., 1-2%). Adjust position size based on volatility.
  • Diversification: Don't put all your eggs in one basket. Diversify your portfolio across different markets.
  • Stay Informed: Monitor market news, weather forecasts, and other factors that can affect electricity prices.
  • Leverage: Use leverage carefully. High leverage can amplify both profits and losses.

IV. Refining the Strategy (Advanced Considerations)

  • Disaggregated Report Analysis: Pay attention to the "Managed Money" (hedge fund) category in the Disaggregated Report. They often drive price trends. Analyze their positioning separately from "Other Reportables."
  • COT Index: Calculate a COT index for both Commercial and Non-Commercial traders. This normalizes the data over a specific period (e.g., 52 weeks) to identify extremes more easily. A COT index near 100 indicates a large net long position, while an index near 0 indicates a large net short position.
  • Commitment Change: Track the week-over-week changes in Commercial and Non-Commercial positions. Significant changes can be more informative than absolute levels.
  • Open Interest: Pay attention to open interest. A rising open interest generally confirms a trend, while a falling open interest may suggest weakening conviction.
  • Seasonality: Electricity prices often exhibit seasonal patterns (higher in summer due to increased demand for cooling). Consider seasonality when analyzing COT data.
  • Correlation with Natural Gas: Electricity prices are often correlated with natural gas prices, as natural gas is a primary fuel source for power generation. Monitor natural gas COT reports and prices as well.

V. Retail Trader vs. Market Investor Application

  • Retail Trader (Short-Term Focus):
    • Focus on shorter-term price trends and COT signals (days to weeks).
    • Use smaller position sizes and tighter stop-loss orders.
    • Actively monitor the market and be prepared to adjust positions quickly.
  • Market Investor (Long-Term Focus):
    • Focus on longer-term price trends and COT signals (weeks to months).
    • Use larger position sizes (proportionally smaller within a larger portfolio) and wider stop-loss orders.
    • Less frequent monitoring and adjustments to positions. May be more focused on capturing larger, longer-term trends.

VI. Important Considerations:

  • Lagging Indicator: The COT report is a lagging indicator. It reflects positions as of the previous Tuesday and is released on Friday. Price action may have already changed since the report was compiled.
  • Not a Crystal Ball: The COT report is just one tool. It should be used in conjunction with other technical and fundamental analysis.
  • Market Manipulation: While less likely than in smaller markets, it's important to be aware that large traders could potentially manipulate the market.
  • Data Accuracy: While CFTC aims for accuracy, errors can occur.

VII. Example Trade Scenario:

Let's say the IFED futures are in a confirmed uptrend. The price is consistently making higher highs, and managed money is significantly increasing their long position, while the commercials are maintaining a manageable short position. A strong cold front is expected across the MISO Indiana Hub region in the next week, suggesting increased demand.

  • Potential Trade: Long position.
  • Entry: Buy the IFED futures contract on a pullback to a support level identified using technical analysis.
  • Stop-Loss: Place a stop-loss order below the support level.
  • Target: Identify a potential profit target based on technical resistance levels or the expected impact of the cold front.
  • Monitoring: Continuously monitor the weather forecasts, news regarding power plant availability, and the COT report to assess if the conditions supporting the uptrend are still valid. If the managed money starts to sell-off on the increase, it might be time to reassess the trade.

In summary, this trading strategy uses COT report analysis to understand the positioning of different trader categories in the MISO Indiana Hub RT Peak electricity futures market. By combining COT data with technical and fundamental analysis, retail traders and market investors can gain valuable insights and make more informed trading decisions. Always remember to prioritize risk management and stay informed about market developments. Good luck!