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

10 YEAR ERIS SOFR SWAP (Non-Commercial)

13-Wk Max 77,172 77,150 7,965 7,954 41
13-Wk Min 58,978 58,946 -1,680 -1,680 21
13-Wk Avg 72,156 72,127 1,265 1,265 28
Report Date Long Short Change Long Change Short Net Position Rate of Change (ROC) ℹ️ Open Int.
May 13, 2025 75,492 75,470 -1,680 -1,680 22 0.00% 117,923
May 6, 2025 77,172 77,150 2,579 2,579 22 0.00% 119,603
April 29, 2025 74,593 74,571 -1,250 -1,250 22 0.00% 117,024
April 22, 2025 75,843 75,821 802 802 22 0.00% 118,274
April 15, 2025 75,041 75,019 -340 -321 22 -46.34% 117,472
April 8, 2025 75,381 75,340 728 719 41 28.13% 117,812
April 1, 2025 74,653 74,621 -757 -757 32 0.00% 117,084
March 25, 2025 75,410 75,378 3,665 3,665 32 0.00% 117,841
March 18, 2025 71,745 71,713 1,827 1,832 32 -13.51% 115,410
March 11, 2025 69,918 69,881 -963 -968 37 15.63% 113,573
March 4, 2025 70,881 70,849 7,965 7,954 32 52.38% 114,711
February 25, 2025 62,916 62,895 3,938 3,949 21 -34.38% 106,536
February 18, 2025 58,978 58,946 -75 -75 32 0.00% 102,598

Net Position (13 Weeks) - Non-Commercial

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

COT Interpretation for 8-14-YEAR INTEREST RATE SWAPS ERIS & MAC

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 (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.

Okay, let's craft a COT-based trading strategy for retail traders and market investors using the 10-Year ERIS SOFR Swap futures contract, keeping in mind its specific characteristics.

Understanding the 10-Year ERIS SOFR Swap & COT Data

  • What it is: The ERIS (Eris Exchange) SOFR Swap futures contract is a financially settled contract designed to hedge or speculate on the spread between the fixed interest rate and the SOFR (Secured Overnight Financing Rate) floating rate for a 10-year swap. It essentially allows traders to express a view on the future direction of interest rates.

  • SOFR Importance: SOFR has replaced LIBOR as the primary benchmark interest rate for USD. Therefore, understanding market expectations surrounding SOFR is crucial.

  • Contract Size: Each contract represents a notional principal of $100,000 USD.

  • COT Report Relevance: The Commitments of Traders (COT) report provides a breakdown of the positions held by different categories of traders in the futures market. For the ERIS SOFR Swap, the key categories are:

    • Commercials (Hedgers): These are entities that use the futures market to hedge their underlying exposure to interest rate risk. They are often financial institutions with significant swap portfolios. They are more driven by price fluctuation than actual profit.

    • Non-Commercials (Speculators): These are entities that are trading to make a profit. Hedge fund, CTA firms etc.

    • Retail Traders (Non-Reportable): Small traders whose positions are below the reporting threshold, and are classified by CFTC with the lowest net position.

Trading Strategy based on COT Report (Retail Traders & Market Investors)

I. Data Acquisition & Preparation

  1. COT Report Source:

    • CFTC Website: Go to the CFTC (Commodity Futures Trading Commission) website (https://www.cftc.gov/MarketReports/CommitmentsofTraders/index.htm). Find the "Supplemental" reports (which usually include swaps). Download the "Combined" report format (Legacy format).
    • Data Vendors: Bloomberg, Refinitiv, TradingView, and other financial data providers usually offer COT data in an easily accessible format.

  2. Specific Data Points to Extract:

    • Commercial Net Position: Subtract Commercial Shorts from Commercial Longs.
    • Non-Commercial Net Position: Subtract Non-Commercial Shorts from Non-Commercial Longs.
    • Open Interest: Total number of outstanding contracts.
    • Price Data: Obtain historical price data for the 10-Year ERIS SOFR Swap futures contract (from your broker or data provider).

  3. Data Preparation:

    • Spreadsheet or Database: Organize the data in a spreadsheet (Excel, Google Sheets) or a database for analysis.
    • Calculate Net Positions: Calculate the net positions for each trader category.
    • Calculate Changes: Calculate the week-over-week changes in net positions and open interest.
    • Smoothing (Optional): Consider using a moving average (e.g., 4-week or 8-week) of the net positions to smooth out the data and identify longer-term trends.

II. COT Data Interpretation

  1. Commercial Hedgers:

    • Hedger Dominance: Pay attention to large Commercial movements. They often have the most insight into the swap market.

    • Net Short Positions: Commercials are typically net short hedgers. An increasing net short position could indicate that they expect interest rates to rise (or at least, that they are hedging against that possibility).

    • Net Long Positions: Commercials are typically net long hedgers. An increasing net long position could indicate that they expect interest rates to fall (or at least, that they are hedging against that possibility).

  2. Non-Commercial Speculators:

    • Trend Followers: Non-Commercials tend to be trend followers. A large increase in their net long positions alongside rising prices could signal a continuation of the upward trend. Conversely, a large increase in their net short positions alongside falling prices could signal a continuation of the downward trend.

    • Contrarian Indicator (Potentially): At market extremes, Non-Commercial positions can become overextended. For example, if Non-Commercials are heavily net long at a market top, it could be a contrarian signal that a reversal is imminent.

  3. Open Interest:

    • Confirmation: Increasing open interest alongside rising prices generally confirms the uptrend. Decreasing open interest alongside falling prices generally confirms the downtrend.
    • Divergence: Divergence between open interest and price can be a warning sign. For example, rising prices with declining open interest could suggest that the rally is losing momentum.

  4. Retail Traders (Non-Reportable):

    • Smallest Net Position: Retail traders (Non-Reportable) typically have the smallest net position in the market and often trade against the trends established by Commercials and Non-Commercials.
    • Contrarian Indicator: Monitoring changes in the Non-Reportable positions can provide valuable contrarian signals. If this group is heavily net long while other groups are net short, it could suggest a potential trend reversal.

III. Trading Rules & Strategy

Here's a sample strategy that blends COT analysis with basic technical analysis. Remember to adjust the parameters based on your risk tolerance and market conditions.

  1. Trend Identification (Technical Analysis):

    • Moving Averages: Use moving averages (e.g., 50-day and 200-day) to determine the overall trend. Price above both MAs suggests an uptrend; price below both suggests a downtrend.
    • Trendlines: Draw trendlines on the price chart to identify potential support and resistance levels.

  2. COT Signal Generation:

    • Commercial Hedger Signal:

      • Bullish: If the Commercial net position shifts from strongly net short to less net short (or even net long) and price is in an uptrend (as confirmed by your technical analysis), consider a long position.
      • Bearish: If the Commercial net position shifts from strongly net long to less net long (or even net short) and price is in a downtrend, consider a short position.

    • Non-Commercial Speculator Signal:

      • Trend Confirmation: If Non-Commercials are increasing their net long positions and price is rising, confirm a long position in the direction of the trend. If Non-Commercials are increasing their net short positions and price is falling, confirm a short position in the direction of the trend.
      • Contrarian Signal: If Non-Commercials are at extreme net long positions during a period of overbought conditions (as indicated by technical indicators), it could be a signal to short. If Non-Commercials are at extreme net short positions during a period of oversold conditions, it could be a signal to go long.

    • Retail Traders Confirmation:

      • Contrarian Signal: The Non-Reportable positions can serve as confirmation of potential trend reversals. If this group is heavily net long while other groups are net short, it could strengthen the bearish signal.

  3. Entry Rules:

    • Long Entry:

      • Uptrend confirmed by technical indicators.
      • Commercials are reducing their net short position (or increasing net long).
      • Price breaks above a recent resistance level.
      • Consider entering on a pullback to a support level (e.g., 50-day MA).

    • Short Entry:

      • Downtrend confirmed by technical indicators.
      • Commercials are reducing their net long position (or increasing net short).
      • Price breaks below a recent support level.
      • Consider entering on a rally to a resistance level (e.g., 50-day MA).

  4. Stop-Loss Placement:

    • Long Trade: Place the stop-loss order below a recent swing low or below a key support level.
    • Short Trade: Place the stop-loss order above a recent swing high or above a key resistance level.

  5. Take-Profit Targets:

    • Fixed Ratio: Set a target that is 2:1 or 3:1 times the risk (distance between entry and stop-loss).
    • Technical Levels: Identify potential resistance levels (for long trades) or support levels (for short trades) based on technical analysis.
    • Trailing Stop: Use a trailing stop to lock in profits as the price moves in your favor.

  6. Position Sizing:

    • Risk Management: Never risk more than 1-2% of your trading capital on any single trade.
    • Contract Calculation: Calculate the number of contracts to trade based on your risk tolerance and the potential loss per contract. Remember, each contract represents $100,000 notional.

  7. COT Signal Filters:

    • Open Interest Filter: Only take trades where open interest confirms the price trend. For example, if price is rising and Commercials are decreasing their net short position, ensure open interest is also increasing.
    • Extreme Readings: Be cautious of trades based on extreme COT readings. The market can remain overbought or oversold for extended periods. Look for additional confirmation from technical indicators.

IV. Example Trade Scenario

  1. Scenario: The 10-Year ERIS SOFR Swap futures price has been in a general uptrend, confirmed by the price trading above both the 50-day and 200-day moving averages.
  2. COT Signal: The latest COT report shows that Commercial hedgers have significantly reduced their net short positions (meaning they are less aggressively hedging against rising rates). Non-commercial speculators are increasing their net long positions.
  3. Entry: The price pulls back to the 50-day moving average, finding support.
  4. Trade: A retail trader enters a long position near the 50-day MA.
  5. Stop-Loss: The stop-loss is placed below the recent swing low.
  6. Take-Profit: The target is set at a resistance level.

V. Risk Management & Important Considerations

  • Risk Management: This is paramount. Always use stop-loss orders and never risk more than a small percentage of your capital on any one trade.
  • Leverage: Futures contracts are leveraged. Use leverage cautiously, as it can amplify both profits and losses.
  • Market Volatility: Interest rate markets can be volatile, especially during periods of economic uncertainty or central bank policy changes.
  • Fundamental Analysis: Complement your COT analysis with fundamental analysis of economic data, central bank announcements, and other factors that could influence interest rates.
  • Market Sentiment: Understand the overall market sentiment. Are traders generally bullish or bearish on interest rates?
  • Backtesting: Before trading this strategy with real money, backtest it on historical data to assess its profitability and risk characteristics.
  • Adaptability: The market is constantly changing. Be prepared to adjust your strategy as market conditions evolve.
  • Data Accuracy: Ensure that the COT data you are using is accurate and up-to-date. Always verify the data with the CFTC's official website.

VI. Continuous Improvement

  • Record Keeping: Keep detailed records of your trades, including entry and exit prices, stop-loss levels, take-profit targets, and the reasons for your decisions.
  • Trade Review: Regularly review your trades to identify what worked well and what didn't.
  • Strategy Refinement: Continuously refine your strategy based on your trading results and market conditions.
  • Education: Stay informed about the latest developments in the interest rate markets and trading strategies.

Important Disclaimer:

This trading strategy is for educational purposes only and should not be considered financial advice. Trading futures involves significant risk of loss, and you should only trade with capital you can afford to lose. Consult with a qualified financial advisor before making any trading decisions.