PYTH PYTH / MDAO Crypto vs USUAL USUAL / 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 / MDAOUSUAL / USD
📈 Performance Metrics
Start Price 5.910.29
End Price 7.000.03
Price Change % +18.48%-88.46%
Period High 12.710.45
Period Low 2.880.03
Price Range % 341.4%1,556.7%
🏆 All-Time Records
All-Time High 12.710.45
Days Since ATH 6 days266 days
Distance From ATH % -45.0%-92.4%
All-Time Low 2.880.03
Distance From ATL % +143.0%+25.2%
New ATHs Hit 16 times1 times
📌 Easy-to-Understand Stats
Avg Daily Change % 5.62%6.33%
Biggest Jump (1 Day) % +2.88+0.15
Biggest Drop (1 Day) % -6.09-0.07
Days Above Avg % 47.1%42.9%
Extreme Moves days 13 (3.8%)12 (4.5%)
Stability Score % 0.0%0.0%
Trend Strength % 54.2%54.7%
Recent Momentum (10-day) % +47.05%-24.00%
📊 Statistical Measures
Average Price 5.380.12
Median Price 5.280.10
Price Std Deviation 1.360.07
🚀 Returns & Growth
CAGR % +19.78%-94.78%
Annualized Return % +19.78%-94.78%
Total Return % +18.48%-88.46%
⚠️ Risk & Volatility
Daily Volatility % 8.44%8.18%
Annualized Volatility % 161.33%156.31%
Max Drawdown % -66.53%-93.96%
Sharpe Ratio 0.048-0.058
Sortino Ratio 0.051-0.064
Calmar Ratio 0.297-1.009
Ulcer Index 40.6375.30
📅 Daily Performance
Win Rate % 54.2%45.1%
Positive Days 186120
Negative Days 157146
Best Day % +58.79%+52.66%
Worst Day % -47.91%-40.61%
Avg Gain (Up Days) % +5.39%+5.80%
Avg Loss (Down Days) % -5.50%-5.64%
Profit Factor 1.160.85
🔥 Streaks & Patterns
Longest Win Streak days 97
Longest Loss Streak days 812
💹 Trading Metrics
Omega Ratio 1.1610.845
Expectancy % +0.41%-0.48%
Kelly Criterion % 1.37%0.00%
📅 Weekly Performance
Best Week % +37.96%+56.22%
Worst Week % -21.65%-29.92%
Weekly Win Rate % 59.6%45.0%
📆 Monthly Performance
Best Month % +44.37%+31.64%
Worst Month % -28.23%-45.24%
Monthly Win Rate % 46.2%36.4%
🔧 Technical Indicators
RSI (14-period) 63.1937.80
Price vs 50-Day MA % +33.34%-34.46%
Price vs 200-Day MA % +41.87%-61.50%
💰 Volume Analysis
Avg Volume 58,544,439430,451
Total Volume 20,139,287,134115,360,753

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 USUAL (USUAL): 0.191 (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
USUAL: Kraken