ASB Stock Analysis
Summary
Backtest Summary - ASB
Generated: 2025-09-24 06:46:40
📊 Buy & Hold Benchmark
Total Return: +960.31%
Analysis Period: Medium-term
Date Range: {‘start’: Timestamp(‘2007-10-30 00:00:00’), ’end’: Timestamp(‘2025-09-23 00:00:00’), ‘days’: 6538}
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 | ASB | 7515.55% | 8.4% | -1.2% | 39.9% | 22.5% | 6555.24% | 0.75 | -59.08% | 75 | 49.33% | $7,615,554 |
| dow_theory | ASB | 0.00% | 0.0% | 0.0% | 0.0% | 0.0% | 0.00% | 0.00 | 0.00% | 0 | 0.00% | $100,000 |
| volume_confirmation | ASB | 5744.26% | 3.5% | -2.0% | 38.8% | 18.8% | 4783.94% | 0.71 | -58.06% | 70 | 50.00% | $5,844,257 |
| bollinger_oscillators | ASB | -94.29% | 12.0% | 46.8% | 55.5% | 62.0% | -1054.60% | -0.39 | -99.02% | 71 | 49.30% | $5,711 |
| macd_divergence | ASB | 0.00% | 0.0% | 0.0% | 0.0% | 0.0% | 0.00% | 0.00 | 0.00% | 0 | 0.00% | $100,000 |
| breakout_momentum | ASB | 13743.51% | 20.7% | 10.5% | 56.5% | 19.3% | 12783.19% | 0.79 | -72.07% | 53 | 49.06% | $13,843,508 |
| mean_reversion_multi_tf | ASB | 2078.74% | 20.7% | 10.5% | 51.0% | 14.9% | 1118.42% | 0.00 | 0.00% | 1 | 0.00% | $2,178,738 |
| relative_strength_rotation | ASB | 16234.14% | 5.2% | -15.7% | 19.4% | -3.0% | 15273.83% | 0.83 | -70.90% | 58 | 50.00% | $16,334,141 |
| gap_trading | ASB | -3.30% | 0.0% | 0.0% | 0.0% | 0.0% | -963.61% | -0.01 | -78.17% | 8 | 50.00% | $96,703 |
| volatility_expansion | ASB | 533.96% | 0.0% | 0.0% | 0.0% | -0.8% | -426.35% | 0.27 | -78.75% | 8 | 50.00% | $633,961 |
| momentum_kirkpatrick | ASB | 8949.38% | 14.5% | -12.8% | 8.8% | -15.5% | 7989.07% | 0.80 | -51.92% | 213 | 49.77% | $9,049,384 |
Best Strategy: relative_strength_rotation
- Symbol: ASB
- Total Return: 16234.14%
- Sharpe Ratio: 0.83
- Max Drawdown: -70.90%
- Final Portfolio Value: $16,334,141
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 2025-08-22
- 📊 Total Confidence: 67.9%
- 🟢 Composite: 67.4%
- 🔵 Conservative: 16.1%
- 🔴 Aggressive: 88.7%
- 🟡 Institutional: 78.0%
- 🟣 Quantitative: 89.2%
🔴 Volume Confirmation: Last SELL on 2025-09-17
- 📊 Total Confidence: 58.8%
- 🟢 Composite: 57.8%
- 🔵 Conservative: 15.1%
- 🔴 Aggressive: 77.5%
- 🟡 Institutional: 67.6%
- 🟣 Quantitative: 75.8%
🟢 Bollinger Oscillators: Last BUY on 2025-09-02
- 📊 Total Confidence: 0.0%
- 🟢 Composite: 0.0%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 0.0%
- 🟡 Institutional: 0.0%
- 🟣 Quantitative: 0.0%
🟢 Breakout Momentum: Last BUY on 2025-07-22
- 📊 Total Confidence: 78.6%
- 🟢 Composite: 80.5%
- 🔵 Conservative: 16.9%
- 🔴 Aggressive: 100.0%
- 🟡 Institutional: 95.7%
- 🟣 Quantitative: 100.0%
🟢 Mean Reversion Multi Tf: Last BUY on 2020-12-14
- 📊 Total Confidence: 27.9%
- 🟢 Composite: 10.4%
- 🔵 Conservative: 18.3%
- 🔴 Aggressive: 12.5%
- 🟡 Institutional: 51.2%
- 🟣 Quantitative: 47.3%
🔴 Relative Strength Rotation: Last SELL on 2025-09-01
- 📊 Total Confidence: 80.0%
- 🟢 Composite: 81.7%
- 🔵 Conservative: 18.3%
- 🔴 Aggressive: 100.0%
- 🟡 Institutional: 100.0%
- 🟣 Quantitative: 100.0%
🔴 Gap Trading: Last SELL on 2022-01-25
- 📊 Total Confidence: 9.5%
- 🟢 Composite: 13.2%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 10.4%
- 🟡 Institutional: 13.3%
- 🟣 Quantitative: 10.8%
🔴 Volatility Expansion: Last SELL on 2024-02-05
- 📊 Total Confidence: 17.3%
- 🟢 Composite: 23.0%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 19.7%
- 🟡 Institutional: 23.5%
- 🟣 Quantitative: 20.2%
🟢 Momentum Kirkpatrick: Last BUY on 2025-09-15
- 📊 Total Confidence: 77.3%
- 🟢 Composite: 75.6%
- 🔵 Conservative: 17.4%
- 🔴 Aggressive: 98.1%
- 🟡 Institutional: 95.2%
- 🟣 Quantitative: 100.0%
📊 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
