PYTH PYTH / GSWIFT Crypto vs MDAO MDAO / GSWIFT Crypto

Stats Comprehensive Analytics for the Selected Time Period

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

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Asset PYTH / GSWIFTMDAO / GSWIFT
📈 Performance Metrics
Start Price 4.640.55
End Price 62.635.29
Price Change % +1,248.61%+856.76%
Period High 62.638.95
Period Low 3.100.42
Price Range % 1,918.1%2,011.6%
🏆 All-Time Records
All-Time High 62.638.95
Days Since ATH 0 days41 days
Distance From ATH % +0.0%-40.9%
All-Time Low 3.100.42
Distance From ATL % +1,918.1%+1,147.6%
New ATHs Hit 33 times53 times
📌 Easy-to-Understand Stats
Avg Daily Change % 5.51%5.98%
Biggest Jump (1 Day) % +16.74+2.37
Biggest Drop (1 Day) % -3.33-2.44
Days Above Avg % 36.7%38.4%
Extreme Moves days 10 (3.1%)18 (5.6%)
Stability Score % 34.0%0.0%
Trend Strength % 56.0%57.1%
Recent Momentum (10-day) % +38.98%-13.95%
📊 Statistical Measures
Average Price 13.782.95
Median Price 11.132.12
Price Std Deviation 9.172.17
🚀 Returns & Growth
CAGR % +1,880.99%+1,225.05%
Annualized Return % +1,880.99%+1,225.05%
Total Return % +1,248.61%+856.76%
⚠️ Risk & Volatility
Daily Volatility % 9.10%8.44%
Annualized Volatility % 173.87%161.20%
Max Drawdown % -33.17%-45.15%
Sharpe Ratio 0.1290.126
Sortino Ratio 0.1710.131
Calmar Ratio 56.70027.135
Ulcer Index 16.1321.85
📅 Daily Performance
Win Rate % 56.0%57.1%
Positive Days 178182
Negative Days 140137
Best Day % +96.03%+44.97%
Worst Day % -26.77%-32.07%
Avg Gain (Up Days) % +6.00%+6.24%
Avg Loss (Down Days) % -4.95%-5.81%
Profit Factor 1.541.43
🔥 Streaks & Patterns
Longest Win Streak days 611
Longest Loss Streak days 55
💹 Trading Metrics
Omega Ratio 1.5401.427
Expectancy % +1.18%+1.06%
Kelly Criterion % 3.97%2.94%
📅 Weekly Performance
Best Week % +65.04%+42.79%
Worst Week % -27.43%-24.16%
Weekly Win Rate % 72.9%45.8%
📆 Monthly Performance
Best Month % +94.65%+79.01%
Worst Month % -5.72%-26.32%
Monthly Win Rate % 83.3%66.7%
🔧 Technical Indicators
RSI (14-period) 84.4642.66
Price vs 50-Day MA % +97.41%-24.86%
Price vs 200-Day MA % +247.64%+32.19%
💰 Volume Analysis
Avg Volume 233,238,957163,088,772
Total Volume 74,403,227,28552,188,407,142

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 MDAO (MDAO): 0.878 (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
MDAO: Bybit