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

EMINI RUSSELL 1000 VALUE INDEX (Non-Commercial)

13-Wk Max 4,066 14,610 1,381 234 -10,300
13-Wk Min 2,527 14,366 -1,116 -244 -12,083
13-Wk Avg 3,010 14,470 -15 18 -11,461
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 2,887 14,600 -1,116 0 -11,713 -10.53% 28,212
May 6, 2025 4,003 14,600 -63 234 -10,597 -2.88% 28,764
April 29, 2025 4,066 14,366 1,381 0 -10,300 11.82% 28,602
April 22, 2025 2,685 14,366 -18 0 -11,681 -0.15% 27,698
April 15, 2025 2,703 14,366 -59 0 -11,663 -0.51% 28,028
April 8, 2025 2,762 14,366 12 -244 -11,604 2.16% 27,899
April 1, 2025 2,750 14,610 223 0 -11,860 1.85% 28,156
March 25, 2025 2,527 14,610 0 0 -12,083 0.00% 30,597
March 18, 2025 2,527 14,610 -345 86 -12,083 -3.70% 42,124
March 11, 2025 2,872 14,524 56 158 -11,652 -0.88% 32,171
March 4, 2025 2,816 14,366 -326 0 -11,550 -2.90% 30,789
February 25, 2025 3,142 14,366 -243 0 -11,224 -2.21% 29,414
February 18, 2025 3,385 14,366 305 0 -10,981 2.70% 29,071

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for RUSSELL INDEX

Comprehensive Guide to COT Reports for Financial Instruments

Table of Contents

Introduction

The Commitment of Traders (COT) reports for financial instruments provide critical insights into positioning across currency, interest rate, and equity index futures markets. These markets differ significantly from commodity markets in terms of participant behavior, market drivers, and interpretation methodology.

Financial futures markets are characterized by institutional dominance, central bank influence, global economic sensitivity, and high levels of leverage. Understanding how different market participants position themselves in these markets can provide valuable information for both traders and investors seeking to anticipate potential market movements.

This guide focuses specifically on analyzing and applying COT data to financial futures markets, with specialized approaches for currencies, interest rates, and equity indices.

The Traders in Financial Futures (TFF) Report

The Traders in Financial Futures (TFF) report is a specialized COT report format introduced by the CFTC in 2009 specifically for financial markets. This report provides more detailed categorization of traders than the Legacy COT report, making it particularly valuable for financial futures analysis.

Key Features of the TFF Report

Enhanced Trader Categories:

  • Dealer/Intermediary: Typically large banks and broker-dealers
  • Asset Manager/Institutional: Pension funds, insurance companies, mutual funds
  • Leveraged Funds: Hedge funds and other speculative money managers
  • Other Reportables: Other traders with reportable positions
  • Non-Reportable Positions: Smaller traders below reporting thresholds

Advantages Over Legacy Report:

  • Separates true hedging activity from speculative positioning
  • Distinguishes between different types of institutional investors
  • Provides clearer signals about smart money vs. speculative money flows
  • Better reflects the actual market structure of financial futures

Coverage:

  • Currency futures and options
  • Interest rate futures and options
  • Stock index futures and options
  • U.S. Treasury futures and options

Financial Markets Covered

Currency Futures

  • Euro FX (CME)
  • Japanese Yen (CME)
  • British Pound (CME)
  • Swiss Franc (CME)
  • Canadian Dollar (CME)
  • Australian Dollar (CME)
  • Mexican Peso (CME)
  • New Zealand Dollar (CME)
  • Russian Ruble (CME)
  • Brazilian Real (CME)

Interest Rate Futures

  • Eurodollar (CME)
  • 30-Year U.S. Treasury Bonds (CBOT)
  • 10-Year U.S. Treasury Notes (CBOT)
  • 5-Year U.S. Treasury Notes (CBOT)
  • 2-Year U.S. Treasury Notes (CBOT)
  • Federal Funds (CBOT)
  • Euribor (ICE)
  • Short Sterling (ICE)

Stock Index Futures

  • S&P 500 E-mini (CME)
  • Nasdaq-100 E-mini (CME)
  • Dow Jones E-mini (CBOT)
  • Russell 2000 E-mini (CME)
  • Nikkei 225 (CME)
  • FTSE 100 (ICE)

Unique Characteristics of Financial COT Data

  1. Central Bank Influence

    Central bank policy decisions have outsized impact on financial futures

    Positioning often reflects anticipation of monetary policy shifts

    Large position changes may precede or follow central bank announcements

  2. Global Macro Sensitivity

    Financial futures positioning responds quickly to global economic developments

    Geopolitical events cause rapid position adjustments

    Economic data releases drive significant repositioning

  3. Intermarket Relationships

    Currency futures positions often correlate with interest rate futures

    Stock index futures positioning may reflect risk appetite across markets

    Cross-market analysis provides more comprehensive signals

  4. Leverage Considerations

    Financial futures markets typically involve higher leverage than commodities

    Position sizes can change rapidly in response to market conditions

    Margin requirements influence positioning decisions

  5. Institutional Dominance

    Financial futures markets have higher institutional participation

    Retail trader influence is typically lower than in commodity markets

    Professional trading desks manage significant portions of open interest

Understanding Trader Categories in Financial Markets

Dealer/Intermediary

Who they are: Major banks, broker-dealers, FCMs

Trading behavior:

  • Often take the opposite side of client transactions
  • May hold positions as part of market-making activities
  • Frequently use futures for hedging swap books and other OTC products

Interpretation keys:

  • Position changes may reflect client order flow rather than directional views
  • Extreme positions can indicate market imbalances
  • Often positioned against prevailing market sentiment

Asset Manager/Institutional

Who they are: Pension funds, insurance companies, mutual funds, endowments

Trading behavior:

  • Typically use futures for portfolio hedging or asset allocation
  • Often hold longer-term positions
  • Position changes may reflect broader investment flows

Interpretation keys:

  • Significant position changes can signal shifts in institutional outlook
  • Often represent "smart money" longer-term positioning
  • Less reactive to short-term market moves than other categories

Leveraged Funds

Who they are: Hedge funds, CTAs, proprietary trading firms

Trading behavior:

  • Primarily speculative positioning
  • Typically more active, with higher turnover
  • Often employ trend-following or technical strategies

Interpretation keys:

  • Extreme positions frequently signal potential market turning points
  • Rapid position changes may precede significant price movements
  • Often positioned with the prevailing trend

Interpreting Financial COT Data

1. Net Positioning Analysis

  • Net Long/Short Calculation: (Long Positions - Short Positions)
  • Percentile Ranking: Compare current positioning to historical range
  • Standard Deviation Measures: Identify statistical extremes in positioning

2. Position Change Analysis

  • Week-over-Week Changes: Identify rapid shifts in sentiment
  • Rate of Change: Measure acceleration or deceleration in position building
  • Rolling Averages: Compare current positioning to medium-term trends

3. Category Comparison Analysis

  • Dealer vs. Leverage Funds: Often positioned opposite each other
  • Asset Manager vs. Leveraged Funds: Can reveal institutional vs. speculative divergence
  • Category Ratio Analysis: Compare relative positioning between categories

4. Concentration Analysis

  • Concentration Ratios: Percentage of open interest held by largest traders
  • Dispersion Metrics: How widely positions are distributed among participants
  • Concentration Trends: Changes in market concentration over time

Currency Futures: COT Analysis Strategies

  1. Central Bank Divergence Strategy

    Setup: Identify diverging monetary policy expectations between currency pairs

    COT Signal: Leveraged funds increasing positions in the direction of policy divergence

    Confirmation: Asset managers beginning to align with the same directional bias

    Markets: Most effective in major currency pairs (EUR/USD, USD/JPY, GBP/USD)

  2. Extreme Positioning Reversal

    Setup: Identify historically extreme net positioning by leveraged funds

    COT Signal: When leveraged fund positioning reaches 90th+ percentile extremes

    Confirmation: Dealers positioning in the opposite direction

    Markets: Particularly effective in trending currency markets approaching exhaustion

  3. Dealer Positioning Strategy

    Setup: Monitor dealer positioning changes across currency markets

    COT Signal: Significant changes in dealer net positioning against prevailing trend

    Confirmation: Price action showing signs of reversal

    Markets: Works across most major and minor currency pairs

  4. Cross-Currency Analysis

    Setup: Compare positioning across related currency pairs

    COT Signal: Divergences in positioning between correlated currencies

    Confirmation: Fundamentals supporting the divergence

    Markets: Currency pairs with common risk factors or regional relationships

Interest Rate Futures: COT Analysis Strategies

  1. Yield Curve Positioning Strategy

    Setup: Analyze positioning across different maturity Treasuries

    COT Signal: Divergent positioning between short-term and long-term instruments

    Confirmation: Economic data supporting yield curve steepening/flattening

    Markets: Treasury futures across different maturities (2Y, 5Y, 10Y, 30Y)

  2. Fed Policy Anticipation Strategy

    Setup: Monitor asset manager positioning ahead of FOMC meetings

    COT Signal: Significant shifts in asset manager positioning in rate-sensitive futures

    Confirmation: Fed funds futures pricing aligning with the positioning shift

    Markets: Particularly effective in Eurodollar and short-term Treasury futures

  3. Inflation Expectation Strategy

    Setup: Track leveraged fund positioning in longer-dated Treasuries

    COT Signal: Major shifts in positioning following inflation data releases

    Confirmation: TIPS (Treasury Inflation-Protected Securities) market movements

    Markets: Most effective in 10Y and 30Y Treasury futures

  4. Risk Sentiment Analysis

    Setup: Compare positioning in safe-haven Treasuries vs. risk assets

    COT Signal: Divergences between bond positioning and stock index positioning

    Confirmation: Credit spread movements aligning with the positioning shifts

    Markets: Treasury futures and equity index futures compared

Stock Index Futures: COT Analysis Strategies

  1. Smart Money Divergence Strategy

    Setup: Compare asset manager positioning with leveraged fund positioning

    COT Signal: Asset managers and leveraged funds moving in opposite directions

    Confirmation: Market internals showing signs of potential reversal

    Markets: Particularly effective in S&P 500 and Nasdaq futures

  2. Sector Rotation Strategy

    Setup: Analyze positioning differences between various index futures

    COT Signal: Divergences between small cap (Russell 2000) and large cap (S&P 500) positioning

    Confirmation: Sector ETF flows aligning with the positioning shifts

    Markets: Works across various index futures (S&P 500, Nasdaq, Russell, Dow)

  3. Institutional Hedging Strategy

    Setup: Monitor asset manager short positioning in equity index futures

    COT Signal: Significant increases in short hedging during market rallies

    Confirmation: Put/call ratios or VIX movements supporting hedging activity

    Markets: Most liquid index futures (particularly S&P 500 E-mini)

  4. Equity Market Sentiment Strategy

    Setup: Track leveraged fund net positioning as a sentiment indicator

    COT Signal: Extreme net long or short positions relative to historical norms

    Confirmation: Traditional sentiment indicators aligning with positioning extremes

    Markets: Works across all major equity index futures

Intermarket Analysis Using Financial COT Data

  1. Currency-Interest Rate Correlation

    Analysis: Compare positioning in currency futures with related interest rate futures

    Signal Interpretation: Divergences between related markets may signal trading opportunities

    Example: EUR futures positioning vs. Eurodollar futures positioning

  2. Risk-On/Risk-Off Flows

    Analysis: Analyze positioning across equity indices, Treasuries, and safe-haven currencies

    Signal Interpretation: Coordinated movements across asset classes signal significant macro shifts

    Example: S&P 500 futures vs. Japanese Yen futures vs. 10-Year Treasury futures

  3. Commodity Currency Analysis

    Analysis: Compare positioning in commodity currencies with related commodity futures

    Signal Interpretation: Divergences may signal upcoming realignment

    Example: Australian Dollar futures vs. gold futures positioning

  4. Cross-Asset Volatility Signals

    Analysis: Monitor positioning changes during periods of heightened volatility

    Signal Interpretation: Identify which trader categories add/reduce risk in volatile periods

    Example: VIX futures positioning vs. S&P 500 futures positioning

Combining COT Data with Macroeconomic Indicators

Economic Data Releases

  • Compare COT positioning changes before and after major economic reports
  • Identify which trader categories respond most strongly to specific data points
  • Economic indicators to monitor:
    • Employment reports (Non-Farm Payrolls)
    • Inflation data (CPI, PCE)
    • GDP reports
    • Manufacturing and services PMIs
    • Retail sales

Central Bank Policy

  • Analyze positioning shifts around central bank meetings
  • Identify anticipatory positioning ahead of policy decisions
  • Monitor position adjustments following policy surprises
  • Key central bank events to track:
    • Federal Reserve FOMC meetings
    • European Central Bank policy announcements
    • Bank of Japan interventions
    • Bank of England decisions

Global Risk Events

  • Track positioning changes during geopolitical crises
  • Identify safe-haven flows across asset classes
  • Monitor unwinding of positions as risk events resolve

Market Liquidity Conditions

  • Analyze positioning shifts during periods of changing liquidity
  • Monitor quarter-end and year-end position adjustments
  • Track positioning during funding stress periods

Case Studies: Major Financial Futures Markets

Euro FX Futures

Typical Positioning Patterns:

  • Leveraged funds often drive trend-following moves
  • Asset managers typically position around long-term economic fundamentals
  • Dealers frequently positioned against extreme speculative sentiment

Key COT Signals:

  • Extreme leveraged fund positioning often precedes significant reversals
  • Asset manager position changes can signal longer-term trend shifts
  • Dealer positioning often provides contrarian signals at market extremes

10-Year Treasury Note Futures

Typical Positioning Patterns:

  • Asset managers use for portfolio hedging and duration management
  • Leveraged funds react to economic data and Fed policy expectations
  • Dealers often serve as liquidity providers across various yield curve points

Key COT Signals:

  • Asset manager positioning shifts often precede significant yield movements
  • Leveraged fund positioning extremes frequently signal potential turning points
  • Dealer positioning changes can indicate institutional order flow shifts

S&P 500 E-mini Futures

Typical Positioning Patterns:

  • Asset managers use for hedging equity exposure and risk management
  • Leveraged funds engage in directional speculation and volatility strategies
  • Dealers often manage complex option-related exposures

Key COT Signals:

  • Asset manager short positioning often increases during strong rallies (hedging)
  • Leveraged fund positioning extremes typically signal potential reversals
  • Dealer positioning often reflects institutional client flows and market-making needs

Advanced Strategies for Financial Markets

  1. Multi-Timeframe COT Analysis

    Implementation:

    • Analyze weekly position changes for short-term signals
    • Track 4-week position trends for medium-term bias
    • Monitor 13-week position changes for longer-term signals

    Benefits:

    • Reduces noise from single-week fluctuations
    • Provides context for short-term moves
    • Identifies persistent institutional positioning trends
  2. COT Momentum Strategy

    Implementation:

    • Calculate rate of change in positioning for each trader category
    • Identify acceleration or deceleration in position building
    • Enter positions when rate of change reaches extremes

    Benefits:

    • Captures early stages of position building
    • Identifies exhaustion in existing trends
    • Works across multiple financial futures markets
  3. COT Divergence Strategy

    Implementation:

    • Identify divergences between price action and positioning
    • Look for situations where prices make new highs/lows but positions don't confirm
    • Enter counter-trend positions when divergences appear at extremes

    Benefits:

    • Catches major turning points in financial markets
    • Provides higher probability entry points
    • Often precedes significant market reversals
  4. COT Spread Strategy

    Implementation:

    • Analyze relative positioning between related markets
    • Identify unusual divergences in correlated instruments
    • Establish spread positions when divergences reach extremes

    Benefits:

    • Reduces directional market risk
    • Capitalizes on relative value opportunities
    • Often offers better risk-adjusted returns than outright positions

Common Pitfalls in Financial COT Analysis

  1. Ignoring Market Context

    Pitfall: Interpreting COT data in isolation without considering market environment

    Solution: Always evaluate positioning within broader market context

    Example: Leveraged fund short positions during a bull market correction vs. during a bear market

  2. Misinterpreting Hedging Activity

    Pitfall: Confusing hedging-related positioning with directional views

    Solution: Understand the typical hedging patterns in each market

    Example: Asset manager short positions in S&P futures often increase during rallies due to portfolio hedging

  3. Overlooking Contract Roll Impacts

    Pitfall: Misinterpreting position changes during contract roll periods

    Solution: Be aware of standard roll schedules for major contracts

    Example: Apparent position shifts during quarterly IMM dates in currency and interest rate futures

  4. Overemphasizing Single Data Points

    Pitfall: Making decisions based on a single week's position changes

    Solution: Focus on multi-week trends and significant position extremes

    Example: Temporary positioning adjustments vs. sustained directional shifts

  5. Neglecting Regulatory Changes

    Pitfall: Failing to account for changes in reporting requirements or regulations

    Solution: Stay informed about CFTC reporting methodology changes

    Example: Impact of Dodd-Frank rules on swap dealer classifications and reporting

Educational Resources

  • "Sentiment in the Forex Market" by Jamie Saettele
  • "Trading the Fixed Income, Inflation and Credit Markets" by Neil Schofield
  • "Inside the Currency Market" by Brian Twomey

Institutional Research

  • Bank Research Reports: Often include COT data analysis in market commentary
  • Investment Bank Strategy Notes: Frequently reference COT positioning in market outlooks
  • Hedge Fund Research: Sometimes available through prime brokerage relationships

© 2025 - This guide is for educational purposes only and does not constitute financial advice. Financial futures markets involve significant risk, and positions should be managed according to individual risk tolerance and objectives.

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.

Trading Strategy for E-mini Russell 1000 Value Index (ERFV) based on COT Report Analysis

This strategy outlines how retail traders and market investors can leverage the Commitment of Traders (COT) report to inform their trading decisions on the E-mini Russell 1000 Value Index (ERFV) futures contract.

Understanding the E-mini Russell 1000 Value Index (ERFV) Contract:

  • Commodity Name: RUSSELL INDEX
  • Contract Units: (RUSSELL 1000 VALUE INDEX x $50)
  • CFTC Market Code: CME (Chicago Mercantile Exchange)
  • Market Exchange Name: EMINI RUSSELL 1000 VALUE INDEX - CHICAGO MERCANTILE EXCHANGE
  • Tick Size & Value: Refer to the CME Group's website for the most up-to-date tick size and value information.
  • Contract Months: Check the CME Group's website for the available contract months.

Understanding the COT Report:

The COT report, released weekly by the CFTC (Commodity Futures Trading Commission), details the aggregate positions held by different trader categories in the futures markets. For ERFV, the key categories are:

  • Commercials (Hedgers): Entities that use the futures market to hedge their underlying business risks (e.g., investment firms hedging equity exposure).
  • Non-Commercials (Large Speculators): Large institutional investors, hedge funds, and commodity trading advisors (CTAs) who trade for profit and are not hedging. They are the most followed group in the COT report.
  • Small Speculators (Retail): Smaller traders including retail investors. This group often trades based on news or in the same direction as the large speculators.

Key COT Data Points to Analyze:

  • Net Positions: The difference between the long and short positions of each trader category. This is the most critical data point.
  • Changes in Net Positions: The week-over-week change in net positions. This indicates the direction and strength of the traders' convictions.
  • Historical Context: Comparing current COT data to historical data to identify extremes and potential turning points.

Trading Strategy Framework:

This strategy is based on the premise that large speculators (Non-Commercials) are often the most informed traders, and their positioning can provide valuable insights. The strategy is contrarian in nature, looking for potential overbought or oversold conditions indicated by extreme positioning. It should be combined with technical analysis and fundamental research.

I. Core Strategy: Tracking Large Speculator Positioning

  1. Data Acquisition: Download the Legacy COT report from the CFTC website or use a reputable data provider that offers COT data.

  2. Focus on Non-Commercials: Primarily analyze the net positions and changes in net positions of the Non-Commercials (Large Speculators) for the ERFV contract.

  3. Identify Extremes:

    • Long Extremes: When Non-Commercials have a very large net long position relative to their historical average, it suggests potential overbought conditions. This could signal a potential price pullback or correction.
    • Short Extremes: When Non-Commercials have a very large net short position relative to their historical average, it suggests potential oversold conditions. This could signal a potential price rally or bounce.

  4. Confirming with Changes:

    • Increasing Longs at Long Extreme: If Non-Commercials are already at a long extreme and continue to increase their long positions, it could be a sign of further upside potential in the short term, but also a building case for a future reversal.
    • Increasing Shorts at Short Extreme: If Non-Commercials are already at a short extreme and continue to increase their short positions, it could be a sign of further downside potential in the short term, but also a building case for a future reversal.
    • Decreasing Longs at Long Extreme: This is a stronger reversal signal, suggesting that large speculators may be closing their long positions, potentially leading to price declines.
    • Decreasing Shorts at Short Extreme: This is a stronger reversal signal, suggesting that large speculators may be closing their short positions, potentially leading to price increases.

  5. Entry and Exit Signals (Combine with Technicals):

    • Long Entry:
      • Non-Commercials are at a historically high net short position.
      • Non-Commercials have started decreasing their net short position (covering shorts).
      • Technical confirmation: Look for bullish reversal patterns on the ERFV chart (e.g., double bottom, bullish engulfing) or a break above a key resistance level. Consider using an oscillator such as RSI reaching the oversold range.
    • Short Entry:
      • Non-Commercials are at a historically high net long position.
      • Non-Commercials have started decreasing their net long position (liquidating longs).
      • Technical confirmation: Look for bearish reversal patterns on the ERFV chart (e.g., double top, bearish engulfing) or a break below a key support level. Consider using an oscillator such as RSI reaching the overbought range.
    • Stop-Loss Placement: Place stop-loss orders strategically based on technical support/resistance levels or ATR (Average True Range) to limit potential losses.
    • Profit Targets: Determine profit targets based on technical analysis (e.g., Fibonacci levels, previous swing highs/lows) or a predetermined risk/reward ratio.

II. Supplemental Analysis: Consider Commercials (Hedgers)

  • Hedgers as a Confirmation: Commercials (Hedgers) are generally considered to be less speculative and more informed about the underlying value of the Russell 1000 Value Index. Observe their positioning to see if it aligns with the signals from the Non-Commercials.
  • Divergence as a Warning: If the Hedgers' positioning is significantly divergent from the Non-Commercials' positioning, it could be a warning sign that the Non-Commercials' position is unsustainable. For example, if Non-Commercials are heavily long while Hedgers are heavily short, it may suggest an eventual price correction.

III. Risk Management:

  • Position Sizing: Never risk more than 1-2% of your total trading capital on any single trade.
  • Stop-Loss Orders: Use stop-loss orders on every trade to limit potential losses.
  • Diversification: Don't put all your eggs in one basket. Diversify your trading portfolio across different markets and asset classes.
  • Emotional Control: Avoid making impulsive trading decisions based on fear or greed. Stick to your trading plan.

IV. Important Considerations and Caveats:

  • Lagging Indicator: The COT report is released with a delay (typically 3 business days after the reporting date). Market conditions can change significantly between the reporting date and the release date.
  • Correlation, Not Causation: The COT report provides insights into trader positioning, but it does not guarantee future price movements. It is just one tool to use in your trading strategy.
  • Market Sentiment: Consider overall market sentiment and news events, as they can override COT signals in the short term.
  • Index Rebalancing: Russell indexes are periodically rebalanced, which can impact the futures contract. Be aware of rebalancing schedules.
  • Exchange Regulations: Stay up-to-date with any changes in exchange regulations or contract specifications.
  • Brokerage Platform: Ensure your brokerage platform provides access to real-time market data, charting tools, and order execution capabilities for ERFV futures.

V. Example Scenario:

Let's say the ERFV is trading at 2000.

  1. COT Report Analysis: The latest COT report shows that Non-Commercials have a historically high net long position, indicating potential overbought conditions. Their net long position is significantly above its 5-year average. Furthermore, they have started to reduce their net long position in the latest reporting week.
  2. Technical Analysis: The ERFV chart shows a double top pattern forming near the 2050 level, which also coincides with a Fibonacci resistance level. RSI is in the overbought range.
  3. Trade Setup: Based on the COT report and technical analysis, you decide to enter a short position at 2040 with a stop-loss at 2060 (above the double top) and a profit target at 1980 (a previous swing low).
  4. Risk Management: You risk 1% of your trading capital on this trade.

VI. Continuous Improvement:

  • Backtesting: Backtest your COT-based strategy on historical data to assess its profitability and identify areas for improvement.
  • Paper Trading: Practice your strategy in a simulated trading environment before risking real capital.
  • Monitoring and Adjustment: Continuously monitor your trades and adjust your strategy as market conditions change.

Conclusion:

The COT report can be a valuable tool for trading the E-mini Russell 1000 Value Index (ERFV). By understanding the positioning of different trader categories, particularly Non-Commercials, and combining this information with technical analysis and risk management, retail traders and market investors can develop a more informed and potentially profitable trading strategy. Remember to always conduct thorough research, practice risk management, and adapt your strategy as needed. Good luck!