PYTH PYTH / DUCK Crypto vs TRAC TRAC / DUCK Crypto

Stats Comprehensive Analytics for the Selected Time Period

Detailed statistical analysis including performance metrics, risk indicators, technical analysis, and advanced ratios.

Settings

🤖 AI Analysis

Ask me anything about the statistics below. I can help explain metrics, identify patterns, or answer specific questions.
Asset PYTH / DUCKTRAC / DUCK
📈 Performance Metrics
Start Price 33.4490.01
End Price 63.07371.52
Price Change % +88.61%+312.76%
Period High 72.89382.63
Period Low 18.4442.21
Price Range % 295.2%806.4%
🏆 All-Time Records
All-Time High 72.89382.63
Days Since ATH 2 days2 days
Distance From ATH % -13.5%-2.9%
All-Time Low 18.4442.21
Distance From ATL % +242.0%+780.1%
New ATHs Hit 15 times19 times
📌 Easy-to-Understand Stats
Avg Daily Change % 6.80%6.87%
Biggest Jump (1 Day) % +21.58+152.88
Biggest Drop (1 Day) % -17.88-37.42
Days Above Avg % 49.3%44.5%
Extreme Moves days 4 (1.9%)6 (2.9%)
Stability Score % 69.3%90.3%
Trend Strength % 51.9%49.5%
Recent Momentum (10-day) % +9.27%+92.62%
📊 Statistical Measures
Average Price 42.11124.23
Median Price 41.81114.53
Price Std Deviation 14.7351.14
🚀 Returns & Growth
CAGR % +204.47%+1,103.44%
Annualized Return % +204.47%+1,103.44%
Total Return % +88.61%+312.76%
⚠️ Risk & Volatility
Daily Volatility % 12.92%11.99%
Annualized Volatility % 246.75%229.09%
Max Drawdown % -74.22%-78.92%
Sharpe Ratio 0.0790.110
Sortino Ratio 0.1060.152
Calmar Ratio 2.75513.982
Ulcer Index 44.0041.28
📅 Daily Performance
Win Rate % 51.9%49.8%
Positive Days 108103
Negative Days 100104
Best Day % +96.79%+87.87%
Worst Day % -49.22%-46.99%
Avg Gain (Up Days) % +8.15%+8.54%
Avg Loss (Down Days) % -6.68%-5.81%
Profit Factor 1.321.45
🔥 Streaks & Patterns
Longest Win Streak days 55
Longest Loss Streak days 77
💹 Trading Metrics
Omega Ratio 1.3181.455
Expectancy % +1.02%+1.33%
Kelly Criterion % 1.87%2.68%
📅 Weekly Performance
Best Week % +74.38%+56.42%
Worst Week % -30.82%-31.69%
Weekly Win Rate % 62.5%43.8%
📆 Monthly Performance
Best Month % +87.76%+87.62%
Worst Month % -34.22%-43.89%
Monthly Win Rate % 55.6%66.7%
🔧 Technical Indicators
RSI (14-period) 54.9989.68
Price vs 50-Day MA % +32.90%+186.29%
Price vs 200-Day MA % +49.86%+197.37%

Performance Metrics: Shows the price at the start and end of the period, total change, and the highest/lowest prices reached during this time frame. | All-Time Records: All-time records show the highest and lowest prices ever reached during this period, how far the current price is from those extremes, and how long ago they occurred. | Easy-to-Understand Stats: Easy-to-understand metrics including typical daily price movements, biggest single-day gains/losses, how often price stayed above average, stability measures, and short-term momentum trends. | Returns & Growth: CAGR (Compound Annual Growth Rate) shows the annualized return rate if this growth continued consistently, while annualized and total returns show performance scaled to different time periods. | Risk & Volatility: Risk metrics show price volatility (daily and annualized), maximum drawdown (worst peak-to-trough decline), and various ratios (Sharpe, Sortino, Calmar, Treynor, Information) that measure risk-adjusted returns. | Daily Performance: Daily performance shows positive vs negative days, win rate, best and worst single days, average gains/losses on up/down days, gain/loss ratio, and profit factor (total gains divided by total losses). | Trading Metrics: Trading metrics include Omega ratio (probability-weighted gains vs losses), payoff ratio (avg win/avg loss), expectancy (expected return per trade), Kelly Criterion (optimal position sizing %), and price efficiency (trending vs choppy).

📊 Asset Correlations

Correlation coefficient ranges from -1 (perfectly inverse) to +1 (perfectly correlated).

PYTH (PYTH) vs TRAC (TRAC): 0.772 (Strong positive)

Correlation shows how closely asset prices move together: +1.0 means perfect positive correlation (move in sync), 0 means no relationship, -1.0 means perfect negative correlation (move opposite). Lower correlation can help with portfolio diversification.

Data sources

PYTH: Kraken
TRAC: Kraken