ATR Stock Analysis
Summary
Backtest Summary - ATR
Generated: 2025-09-24 07:09:50
📊 Buy & Hold Benchmark
Total Return: +965.16%
Analysis Period: Medium-term
Date Range: {‘start’: Timestamp(‘2008-12-18 00:00:00’), ’end’: Timestamp(‘2025-09-23 00:00:00’), ‘days’: 6123}
This represents the return from buying at the start and holding until the end of the analysis period.
Performance Overview
| Strategy | Symbol | Total Return | 3M Return | 6M Return | 12M Return | 24M Return | Excess Return | Sharpe Ratio | Max Drawdown | Trades | Win Rate | Final Value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| trend_momentum | ATR | 658.91% | 53.1% | 139.0% | 337.5% | 519.6% | -306.25% | 0.41 | -76.10% | 77 | 49.35% | $758,915 |
| dow_theory | ATR | 0.00% | 0.0% | 0.0% | 0.0% | 0.0% | 0.00% | 0.00 | 0.00% | 0 | 0.00% | $100,000 |
| volume_confirmation | ATR | 561.18% | 53.1% | 99.1% | 263.0% | 414.7% | -403.98% | 0.39 | -72.82% | 71 | 49.30% | $661,180 |
| bollinger_oscillators | ATR | 65.78% | 0.0% | 15.7% | 23.7% | 74.2% | -899.38% | 0.08 | -90.80% | 72 | 50.00% | $165,779 |
| macd_divergence | ATR | 0.00% | 0.0% | 0.0% | 0.0% | 0.0% | 0.00% | 0.00 | 0.00% | 0 | 0.00% | $100,000 |
| breakout_momentum | ATR | 2968.71% | 24.9% | 71.1% | 196.7% | 433.3% | 2003.55% | 0.60 | -57.60% | 45 | 48.89% | $3,068,714 |
| mean_reversion_multi_tf | ATR | 0.00% | 0.0% | 0.0% | 0.0% | 0.0% | 0.00% | 0.00 | 0.00% | 0 | 0.00% | $100,000 |
| relative_strength_rotation | ATR | 1956.54% | 24.9% | 94.9% | 286.5% | 625.1% | 991.38% | 0.55 | -67.29% | 57 | 49.12% | $2,056,542 |
| gap_trading | ATR | 271.98% | 53.1% | 139.0% | 373.8% | 761.6% | -693.19% | 0.21 | -89.10% | 9 | 44.44% | $371,977 |
| volatility_expansion | ATR | 1085.18% | 53.1% | 139.0% | 373.8% | 816.2% | 120.02% | 0.36 | -85.51% | 11 | 45.45% | $1,185,181 |
| momentum_kirkpatrick | ATR | 546.11% | 46.7% | 85.2% | 146.4% | 207.5% | -419.06% | 0.34 | -66.38% | 187 | 49.73% | $646,106 |
Best Strategy: breakout_momentum
- Symbol: ATR
- Total Return: 2968.71%
- Sharpe Ratio: 0.60
- Max Drawdown: -57.60%
- Final Portfolio Value: $3,068,714
Key Metrics
- Initial Capital: $100,000
- Analysis Date: 2025-09-24
- Portfolio Manager: Active (Extreme returns fix applied)
Period Analysis
This report includes period-based return analysis for the following timeframes:
- 3M Return: Performance over the last 3 months
- 6M Return: Performance over the last 6 months
- 12M Return: Performance over the last 12 months
- 24M Return: Performance over the last 24 months
Period-based analysis helps identify strategy behavior across different market conditions and time horizons.
Recent Trading Signals
📊 Today’s Signals (2025-09-24)
⚪ No new trading signals detected in today’s analysis.
📈 Most Recent Signals by Strategy
🟢 Trend Momentum: Last BUY on 2025-09-17
- 📊 Total Confidence: 23.3%
- 🟢 Composite: 26.3%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 22.4%
- 🟡 Institutional: 32.1%
- 🟣 Quantitative: 35.7%
🟢 Volume Confirmation: Last BUY on 2025-09-23
- 📊 Total Confidence: 22.5%
- 🟢 Composite: 25.3%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 21.5%
- 🟡 Institutional: 31.1%
- 🟣 Quantitative: 34.8%
🔴 Bollinger Oscillators: Last SELL on 2025-09-23
- 📊 Total Confidence: 47.2%
- 🟢 Composite: 49.5%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 73.2%
- 🟡 Institutional: 52.4%
- 🟣 Quantitative: 60.7%
🟢 Breakout Momentum: Last BUY on 2025-09-23
- 📊 Total Confidence: 36.3%
- 🟢 Composite: 41.5%
- 🔵 Conservative: 3.9%
- 🔴 Aggressive: 39.0%
- 🟡 Institutional: 44.5%
- 🟣 Quantitative: 52.7%
🔴 Mean Reversion Multi Tf: Last SELL on 2021-11-12
- 📊 Total Confidence: 2.0%
- 🟢 Composite: 0.0%
- 🔵 Conservative: 10.0%
- 🔴 Aggressive: 0.0%
- 🟡 Institutional: 0.0%
- 🟣 Quantitative: 0.0%
🟢 Relative Strength Rotation: Last BUY on 2025-09-19
- 📊 Total Confidence: 30.8%
- 🟢 Composite: 35.5%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 32.2%
- 🟡 Institutional: 42.0%
- 🟣 Quantitative: 44.2%
🟢 Gap Trading: Last BUY on 2024-12-11
- 📊 Total Confidence: 14.1%
- 🟢 Composite: 18.9%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 15.9%
- 🟡 Institutional: 19.3%
- 🟣 Quantitative: 16.5%
🟢 Volatility Expansion: Last BUY on 2025-05-26
- 📊 Total Confidence: 20.3%
- 🟢 Composite: 26.3%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 23.3%
- 🟡 Institutional: 26.8%
- 🟣 Quantitative: 24.9%
🟢 Momentum Kirkpatrick: Last BUY on 2025-09-23
- 📊 Total Confidence: 24.3%
- 🟢 Composite: 24.5%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 20.9%
- 🟡 Institutional: 35.4%
- 🟣 Quantitative: 40.8%
📊 How Confidence Is Calculated
Confidence percentages tell you how much to trust a trading signal based on the strategy’s historical performance.
🎯 Current Method: Composite (Balanced)
- Sharpe Ratio: Up to 20 points (risk-adjusted returns)
- Win Rate: Up to 30 points (percentage of profitable trades)
- Total Return: Up to 50 points (overall profitability)
📈 Available Confidence Methods:
- 🟢 Composite (Balanced): Current method - balanced approach for most traders
- 🔵 Conservative (Risk-Averse): Emphasizes safety and downside protection
- 🔴 Aggressive (Growth-Focused): Prioritizes high returns over risk
- 🟡 Institutional (Modern Portfolio Theory): Professional fund management approach
- 🟣 Quantitative (Statistical): Mathematical and statistical measures
🎯 Confidence Levels:
- 70%+: Strong performer - trust this signal more
- 50-70%: Decent performer - moderate trust
- 30-50%: Weak performer - be cautious
- <30%: Poor performer - low trust
💡 Signal Interpretation
- 🟢 BUY signals: Suggest potential upward price movement
- 🔴 SELL signals: Suggest potential downward price movement
- ⚪ HOLD signals: Suggest maintaining current position
- 📊 Confidence: Higher percentages indicate stronger signal conviction
- 🎯 CONSENSUS: Overall recommendation based on multiple strategy agreement
📚 Detailed Confidence Method Explanations
🟢 Composite (Balanced) - Current Method
Formula: (Sharpe×20) + (WinRate×30) + (Return×50)
Used by: Individual traders, retail investors
Why: Balanced approach that considers risk, consistency, and returns equally. Good for most trading styles.
Example: Strategy with 0.4 Sharpe, 60% win rate, 80% return = (0.4×20) + (0.6×30) + (0.8×50) = 66% confidence
🔵 Conservative (Risk-Averse)
Formula: (Sharpe×25) + (WinRate×35) + (Return×40) - DrawdownPenalty + SafetyBonus
Used by: Pension funds, insurance companies, risk-averse investors
Why: Prioritizes capital preservation over growth. Heavily penalizes strategies with large drawdowns.
Key Features:
- Higher weight on consistency (win rate)
- Penalty for drawdowns >5%
- Bonus for low-risk strategies
- Caps returns at 50% to avoid overvaluing risky strategies
🔴 Aggressive (Growth-Focused)
Formula: (Return×60) + (Sharpe×15) + (WinRate×25) + HighReturnBonus
Used by: Hedge funds, growth investors, aggressive traders
Why: Maximizes returns regardless of risk. Suitable for investors who can tolerate volatility.
Key Features:
- 60% weight on raw returns
- Lower weight on risk adjustment
- Bonus for strategies with >50% returns
- Allows returns up to 200% contribution
🟡 Institutional (Modern Portfolio Theory)
Formula: InfoRatio + Consistency + RiskAdjustedReturn + ReturnComponent + SignificanceBonus
Used by: Mutual funds, pension funds, institutional investors
Why: Based on academic finance theory and institutional requirements. Emphasizes statistical significance.
Key Features:
- Information ratio (like Sharpe but more robust)
- Return-to-drawdown ratio
- Bonus for statistically significant results (>100 trades)
- Follows modern portfolio theory principles
🟣 Quantitative (Statistical)
Formula: CalmarRatio + SterlingRatio + WinRate + Return + SampleSize + StatisticalSignificance
Used by: Quantitative funds, algorithmic trading systems, research institutions
Why: Uses advanced statistical measures and mathematical optimization. Most rigorous approach.
Key Features:
- Calmar ratio (return/max drawdown)
- Sterling ratio (similar to Calmar)
- Sample size adjustment for statistical validity
- T-statistic proxy for significance testing
- Mathematical optimization of weights
🏛️ Financial Industry Context
Goldman Sachs: Uses similar multi-factor scoring for strategy selection
Renaissance Technologies: Employs statistical significance testing like our Quantitative method
Bridgewater: Emphasizes risk parity similar to our Conservative approach
AQR: Uses academic factors like our Institutional method
Two Sigma: Applies quantitative methods similar to our Statistical approach
