PYTH PYTH / CELR Crypto vs MDAO MDAO / 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 / CELRMDAO / USD
📈 Performance Metrics
Start Price 32.170.07
End Price 16.290.01
Price Change % -49.37%-89.02%
Period High 32.170.08
Period Low 12.580.01
Price Range % 155.7%857.7%
🏆 All-Time Records
All-Time High 32.170.08
Days Since ATH 343 days319 days
Distance From ATH % -49.4%-89.6%
All-Time Low 12.580.01
Distance From ATL % +29.5%+0.0%
New ATHs Hit 0 times2 times
📌 Easy-to-Understand Stats
Avg Daily Change % 2.97%3.08%
Biggest Jump (1 Day) % +13.63+0.01
Biggest Drop (1 Day) % -3.74-0.01
Days Above Avg % 38.4%41.2%
Extreme Moves days 6 (1.7%)18 (5.2%)
Stability Score % 63.5%0.0%
Trend Strength % 55.1%54.9%
Recent Momentum (10-day) % -10.45%-63.48%
📊 Statistical Measures
Average Price 17.510.04
Median Price 16.150.03
Price Std Deviation 3.770.02
🚀 Returns & Growth
CAGR % -51.53%-90.41%
Annualized Return % -51.53%-90.41%
Total Return % -49.37%-89.02%
⚠️ Risk & Volatility
Daily Volatility % 6.39%6.02%
Annualized Volatility % 122.02%114.94%
Max Drawdown % -60.90%-89.56%
Sharpe Ratio -0.007-0.075
Sortino Ratio -0.011-0.078
Calmar Ratio -0.846-1.009
Ulcer Index 47.0454.69
📅 Daily Performance
Win Rate % 44.9%43.1%
Positive Days 154143
Negative Days 189189
Best Day % +94.13%+44.65%
Worst Day % -16.92%-45.99%
Avg Gain (Up Days) % +3.24%+3.24%
Avg Loss (Down Days) % -2.72%-3.27%
Profit Factor 0.970.75
🔥 Streaks & Patterns
Longest Win Streak days 55
Longest Loss Streak days 710
💹 Trading Metrics
Omega Ratio 0.9720.749
Expectancy % -0.04%-0.47%
Kelly Criterion % 0.00%0.00%
📅 Weekly Performance
Best Week % +60.96%+39.72%
Worst Week % -23.40%-45.53%
Weekly Win Rate % 50.0%28.8%
📆 Monthly Performance
Best Month % +49.54%+52.04%
Worst Month % -32.10%-56.16%
Monthly Win Rate % 38.5%23.1%
🔧 Technical Indicators
RSI (14-period) 28.951.92
Price vs 50-Day MA % -20.59%-77.23%
Price vs 200-Day MA % -0.35%-72.32%
💰 Volume Analysis
Avg Volume 207,726,3921,437,546
Total Volume 71,457,878,780495,953,439

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): 0.690 (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
MDAO: Bybit