PYTH PYTH / MDAO Crypto vs PFVS PFVS / USD 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 / MDAOPFVS / USD
📈 Performance Metrics
Start Price 5.910.07
End Price 7.000.00
Price Change % +18.48%-96.26%
Period High 12.710.07
Period Low 2.880.00
Price Range % 341.4%2,572.1%
🏆 All-Time Records
All-Time High 12.710.07
Days Since ATH 6 days139 days
Distance From ATH % -45.0%-96.3%
All-Time Low 2.880.00
Distance From ATL % +143.0%+0.0%
New ATHs Hit 16 times0 times
📌 Easy-to-Understand Stats
Avg Daily Change % 5.62%6.84%
Biggest Jump (1 Day) % +2.88+0.00
Biggest Drop (1 Day) % -6.09-0.02
Days Above Avg % 47.1%32.9%
Extreme Moves days 13 (3.8%)7 (5.0%)
Stability Score % 0.0%0.0%
Trend Strength % 54.2%62.6%
Recent Momentum (10-day) % +47.05%-24.37%
📊 Statistical Measures
Average Price 5.380.01
Median Price 5.280.01
Price Std Deviation 1.360.01
🚀 Returns & Growth
CAGR % +19.78%-99.98%
Annualized Return % +19.78%-99.98%
Total Return % +18.48%-96.26%
⚠️ Risk & Volatility
Daily Volatility % 8.44%8.10%
Annualized Volatility % 161.33%154.84%
Max Drawdown % -66.53%-96.26%
Sharpe Ratio 0.048-0.243
Sortino Ratio 0.051-0.220
Calmar Ratio 0.297-1.039
Ulcer Index 40.6384.34
📅 Daily Performance
Win Rate % 54.2%37.0%
Positive Days 18651
Negative Days 15787
Best Day % +58.79%+31.83%
Worst Day % -47.91%-41.78%
Avg Gain (Up Days) % +5.39%+4.30%
Avg Loss (Down Days) % -5.50%-5.67%
Profit Factor 1.160.44
🔥 Streaks & Patterns
Longest Win Streak days 94
Longest Loss Streak days 89
💹 Trading Metrics
Omega Ratio 1.1610.445
Expectancy % +0.41%-1.99%
Kelly Criterion % 1.37%0.00%
📅 Weekly Performance
Best Week % +37.96%+13.84%
Worst Week % -21.65%-52.64%
Weekly Win Rate % 59.6%19.0%
📆 Monthly Performance
Best Month % +44.37%+-4.82%
Worst Month % -28.23%-62.77%
Monthly Win Rate % 46.2%0.0%
🔧 Technical Indicators
RSI (14-period) 63.1928.30
Price vs 50-Day MA % +33.34%-53.06%
Price vs 200-Day MA % +41.87%N/A
💰 Volume Analysis
Avg Volume 58,544,43941,907,781
Total Volume 20,139,287,1345,867,089,344

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 PFVS (PFVS): 0.278 (Weak)

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
PFVS: Bybit