PYTH PYTH / MDAO Crypto vs SHPING SHPING / USD Crypto

Stats Comprehensive Analytics for the Selected Time Period

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

Settings

Asset PYTH / MDAOSHPING / USD
📈 Performance Metrics
Start Price 5.350.00
End Price 5.620.00
Price Change % +5.05%-7.57%
Period High 8.610.01
Period Low 2.880.00
Price Range % 198.8%220.0%
🏆 All-Time Records
All-Time High 8.610.01
Days Since ATH 312 days310 days
Distance From ATH % -34.6%-67.5%
All-Time Low 2.880.00
Distance From ATL % +95.3%+4.1%
New ATHs Hit 18 times13 times
📌 Easy-to-Understand Stats
Avg Daily Change % 4.88%3.71%
Biggest Jump (1 Day) % +2.18+0.00
Biggest Drop (1 Day) % -1.820.00
Days Above Avg % 48.7%33.8%
Extreme Moves days 12 (3.5%)8 (2.3%)
Stability Score % 0.0%0.0%
Trend Strength % 54.1%55.6%
Recent Momentum (10-day) % +8.82%+1.11%
📊 Statistical Measures
Average Price 5.280.01
Median Price 5.220.01
Price Std Deviation 1.180.00
🚀 Returns & Growth
CAGR % +5.40%-8.06%
Annualized Return % +5.40%-8.06%
Total Return % +5.05%-7.57%
⚠️ Risk & Volatility
Daily Volatility % 7.29%5.87%
Annualized Volatility % 139.32%112.09%
Max Drawdown % -66.53%-68.75%
Sharpe Ratio 0.0370.023
Sortino Ratio 0.0390.032
Calmar Ratio 0.081-0.117
Ulcer Index 40.2350.00
📅 Daily Performance
Win Rate % 54.1%44.3%
Positive Days 185151
Negative Days 157190
Best Day % +58.79%+52.25%
Worst Day % -32.55%-18.25%
Avg Gain (Up Days) % +4.85%+4.10%
Avg Loss (Down Days) % -5.12%-3.02%
Profit Factor 1.121.08
🔥 Streaks & Patterns
Longest Win Streak days 96
Longest Loss Streak days 86
💹 Trading Metrics
Omega Ratio 1.1161.079
Expectancy % +0.27%+0.13%
Kelly Criterion % 1.10%1.07%
📅 Weekly Performance
Best Week % +37.96%+41.87%
Worst Week % -21.65%-27.19%
Weekly Win Rate % 56.9%51.0%
📆 Monthly Performance
Best Month % +59.28%+76.34%
Worst Month % -28.23%-29.15%
Monthly Win Rate % 50.0%41.7%
🔧 Technical Indicators
RSI (14-period) 64.0858.80
Price vs 50-Day MA % +36.54%-7.92%
Price vs 200-Day MA % +18.67%-20.96%
💰 Volume Analysis
Avg Volume 51,739,11762,450,926
Total Volume 17,746,517,28721,420,667,590

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 SHPING (SHPING): 0.582 (Moderate 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
SHPING: Coinbase
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