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COT Backtests

This page documents the backtesting research behind TradeAnon's COT-based contrarian signals. The COT Watchlist is built on validated signals with historical performance data.

Research Objective

The COT backtest research aimed to answer:

  1. Do positioning extremes predict reversals? — When speculators are extremely positioned, do markets tend to reverse?
  2. Which threshold works best? — What z-score level identifies actionable extremes?
  3. Which markets show strongest signals? — Are some futures more responsive than others?
  4. What is realistic performance? — What returns and risk should we expect?

Methodology

Signal Definition

A contrarian signal is generated when:

Signal = Fade speculator extreme positioning

Long Signal:

  • Speculator net position z-score < -threshold (extremely bearish)
  • Signal: Go long (fade the bears)

Short Signal:

  • Speculator net position z-score > +threshold (extremely bullish)
  • Signal: Go short (fade the bulls)

Threshold Levels Tested

LevelZ-ScoreDescription
Conservative±2.5σVery extreme readings
Standard±2.0σModerate extremes
Aggressive±1.5σMore frequent signals

Holding Period

Signals tested with multiple holding periods:

  • 1 week
  • 2 weeks
  • 4 weeks
  • 8 weeks

Universe

Tested across major futures categories:

  • Equity indices (ES, NQ, RTY)
  • Energy (CL, NG)
  • Metals (GC, SI, HG)
  • Currencies (6E, 6J, 6B)
  • Interest rates (ZN, ZB, ZF)
  • Agriculture (ZC, ZS, ZW)

Key Findings

Overall Results

Contrarian signals show positive expectancy:

  • Win rates: 52-60% depending on market and threshold
  • Average win typically exceeds average loss
  • Sharpe ratios: 0.4-0.8 range
  • Works better in some markets than others

Threshold Analysis

ThresholdWin Rate# Signals/YearAvg Return
±2.5σ58%2-3Higher
±2.0σ55%4-6Moderate
±1.5σ52%8-12Lower

Tradeoff: More conservative thresholds have higher win rates but fewer signals.

Market-Specific Results

Strongest Signals:

  • Gold (GC): Consistent contrarian edge
  • Crude Oil (CL): Strong reversal patterns
  • S&P 500 (ES): Reliable at extremes

Moderate Signals:

  • Currencies: Variable by pair
  • Grains: Seasonal factors complicate

Weakest Signals:

  • Natural Gas (NG): High volatility reduces reliability
  • Some agricultural commodities

Holding Period Analysis

Holding PeriodWin RateAvg ReturnNotes
1 week51%LowerOften too short
2 weeks54%ModerateGood balance
4 weeks56%HigherAllows trend to develop
8 weeks55%VariableDiminishing edge

Conclusion: 2-4 week holding periods show best risk-adjusted results.

Sample Backtest: Gold (GC)

Parameters

  • Period: 2015-2024
  • Threshold: ±2.0σ
  • Holding: 4 weeks
  • Position: Long only (fade bearish extremes)

Results

MetricValue
Total Signals47
Win Rate59.6%
Avg Win4.2%
Avg Loss2.8%
Sharpe Ratio0.72
Max Drawdown12.4%
Total Return89.3%

Equity Curve Characteristics

  • Steady upward trend with expected drawdowns
  • Outperformed buy-and-hold during test period
  • Larger gains during periods of sentiment extremes

Watchlist Construction

The COT Watchlist surfaces signals that meet validation criteria:

Inclusion Criteria

  1. Positive historical expectancy — Backtested signal shows positive returns
  2. Statistical significance — Sufficient sample size (>20 signals)
  3. Current extreme — Z-score beyond threshold
  4. Recent data — COT report within last week

Displayed Metrics

For each watchlist signal:

MetricPurpose
SymbolMarket identifier
DirectionLong or short signal
Z-ScoreCurrent extreme reading
ThresholdWhich level triggered
Historical Win RateBacktest performance
Historical SharpeRisk-adjusted performance
Sample SizeNumber of historical signals

Ranking

Signals ranked by:

  1. Sharpe ratio (primary)
  2. Win rate (secondary)
  3. Recency of extreme (tertiary)

Limitations

Data Limitations

COT Delay:

  • Data as of Tuesday, released Friday
  • 3-day lag between positions and report
  • Signal may be stale by trading time

History Depth:

  • Reliable data since ~2006
  • Limited sample for some markets
  • Regime changes may affect future performance

Methodological Limitations

No Look-Ahead:

  • Signals based on available data at time
  • But holding period results known ex-post

Single Entry:

  • Tests single entry at signal
  • Real trading might scale in/out

No Stops:

  • Tests buy-and-hold for holding period
  • Live trading would use risk management

Market Limitations

Capacity:

  • Individual traders have minimal impact
  • Institutional size may move markets
  • Most signals remain actionable

Correlation:

  • Multiple signals may fire simultaneously
  • Diversification benefits limited
  • Risk management crucial

Using These Results

For Traders

  1. Don't trade every signal — Focus on highest conviction
  2. Use proper sizing — Don't overweight any single position
  3. Apply risk management — Use stops despite backtest assumptions
  4. Expect variance — Individual results will vary

Realistic Expectations

What to Expect:

  • Win rate near 55% (not 80%)
  • Regular losing trades
  • Periods of drawdown
  • Modest but consistent edge

What NOT to Expect:

  • Every signal to win
  • Immediate results
  • Outperformance every period
  • Risk-free returns

Research Updates

Backtests are periodically re-run to:

  • Incorporate new data
  • Validate continued effectiveness
  • Adjust thresholds if needed
  • Remove signals that stopped working

Last updated: Check platform for current date.