PKO Stock Analysis
Summary
Backtest Summary - PKO
Generated: 2025-09-24 07:05:26
📊 Buy & Hold Benchmark
Total Return: +456.44%
Analysis Period: Medium-term
Date Range: {‘start’: Timestamp(‘2004-11-10 00:00:00’), ’end’: Timestamp(‘2025-09-23 00:00:00’), ‘days’: 7622}
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 | PKO | 78.83% | -2.4% | -17.1% | 3.7% | 29.8% | -377.60% | 0.13 | -49.45% | 112 | 50.00% | $178,835 |
| dow_theory | PKO | 0.00% | 0.0% | 0.0% | 0.0% | 0.0% | 0.00% | 0.00 | 0.00% | 0 | 0.00% | $100,000 |
| volume_confirmation | PKO | 83.77% | -2.8% | -10.8% | 18.2% | 45.6% | -372.67% | 0.13 | -56.82% | 98 | 50.00% | $183,765 |
| bollinger_oscillators | PKO | 196.49% | -2.3% | 19.4% | 19.4% | 51.5% | -259.95% | 0.22 | -56.48% | 101 | 49.50% | $296,491 |
| macd_divergence | PKO | 0.00% | 0.0% | 0.0% | 0.0% | 0.0% | 0.00% | 0.00 | 0.00% | 0 | 0.00% | $100,000 |
| breakout_momentum | PKO | 86.19% | 0.0% | -16.6% | -1.4% | 43.9% | -370.25% | 0.13 | -64.41% | 66 | 50.00% | $186,190 |
| mean_reversion_multi_tf | PKO | 71.36% | 8.5% | -3.2% | 33.4% | 40.3% | -385.08% | 0.08 | -67.26% | 3 | 33.33% | $171,363 |
| relative_strength_rotation | PKO | 80.49% | 1.0% | -17.6% | -1.8% | 37.3% | -375.95% | 0.13 | -52.22% | 92 | 50.00% | $180,485 |
| gap_trading | PKO | 4.05% | 0.0% | 0.0% | 0.0% | 0.0% | -452.39% | 0.02 | -33.62% | 4 | 50.00% | $104,049 |
| volatility_expansion | PKO | 86.22% | 8.5% | -3.2% | 33.4% | 86.2% | -370.22% | 0.00 | 0.00% | 1 | 0.00% | $186,220 |
| momentum_kirkpatrick | PKO | 78.51% | 4.8% | 0.7% | -0.0% | 38.6% | -377.93% | 0.13 | -63.98% | 250 | 50.00% | $178,506 |
Best Strategy: bollinger_oscillators
- Symbol: PKO
- Total Return: 196.49%
- Sharpe Ratio: 0.22
- Max Drawdown: -56.48%
- Final Portfolio Value: $296,491
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 SELL on 2025-09-23
- 📊 Total Confidence: 61.2%
- 🟢 Composite: 56.9%
- 🔵 Conservative: 0.7%
- 🔴 Aggressive: 81.7%
- 🟡 Institutional: 75.3%
- 🟣 Quantitative: 91.3%
🔴 Volume Confirmation: Last SELL on 2025-09-23
- 📊 Total Confidence: 61.0%
- 🟢 Composite: 59.5%
- 🔵 Conservative: 0.8%
- 🔴 Aggressive: 84.7%
- 🟡 Institutional: 70.1%
- 🟣 Quantitative: 90.0%
🟢 Bollinger Oscillators: Last BUY on 2025-09-03
- 📊 Total Confidence: 74.4%
- 🟢 Composite: 69.3%
- 🔵 Conservative: 2.9%
- 🔴 Aggressive: 100.0%
- 🟡 Institutional: 100.0%
- 🟣 Quantitative: 100.0%
🔴 Breakout Momentum: Last SELL on 2025-08-22
- 📊 Total Confidence: 60.3%
- 🟢 Composite: 60.8%
- 🔵 Conservative: 0.9%
- 🔴 Aggressive: 86.2%
- 🟡 Institutional: 68.9%
- 🟣 Quantitative: 84.9%
🟢 Mean Reversion Multi Tf: Last BUY on 2024-07-16
- 📊 Total Confidence: 45.9%
- 🟢 Composite: 47.4%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 72.4%
- 🟡 Institutional: 49.2%
- 🟣 Quantitative: 60.7%
🔴 Relative Strength Rotation: Last SELL on 2025-08-26
- 📊 Total Confidence: 60.3%
- 🟢 Composite: 57.9%
- 🔵 Conservative: 0.8%
- 🔴 Aggressive: 82.8%
- 🟡 Institutional: 70.2%
- 🟣 Quantitative: 89.8%
🔴 Gap Trading: Last SELL on 2022-09-02
- 📊 Total Confidence: 13.6%
- 🟢 Composite: 17.3%
- 🔵 Conservative: 0.0%
- 🔴 Aggressive: 15.2%
- 🟡 Institutional: 18.4%
- 🟣 Quantitative: 17.3%
🟢 Volatility Expansion: Last BUY on 2023-10-18
- 📊 Total Confidence: 57.2%
- 🟢 Composite: 43.1%
- 🔵 Conservative: 30.0%
- 🔴 Aggressive: 71.7%
- 🟡 Institutional: 70.9%
- 🟣 Quantitative: 70.2%
🔴 Momentum Kirkpatrick: Last SELL on 2025-09-23
- 📊 Total Confidence: 60.1%
- 🟢 Composite: 56.9%
- 🔵 Conservative: 0.8%
- 🔴 Aggressive: 81.6%
- 🟡 Institutional: 69.9%
- 🟣 Quantitative: 91.2%
📊 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
