PYTH PYTH / ALGO Crypto vs MV MV / ALGO 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 / ALGOMV / ALGO
📈 Performance Metrics
Start Price 2.270.05
End Price 0.560.02
Price Change % -75.43%-49.98%
Period High 2.270.05
Period Low 0.410.02
Price Range % 459.6%171.2%
🏆 All-Time Records
All-Time High 2.270.05
Days Since ATH 343 days338 days
Distance From ATH % -75.4%-56.3%
All-Time Low 0.410.02
Distance From ATL % +37.5%+18.6%
New ATHs Hit 0 times2 times
📌 Easy-to-Understand Stats
Avg Daily Change % 3.58%5.03%
Biggest Jump (1 Day) % +0.44+0.01
Biggest Drop (1 Day) % -0.39-0.01
Days Above Avg % 33.7%51.5%
Extreme Moves days 7 (2.0%)14 (4.1%)
Stability Score % 0.0%0.0%
Trend Strength % 53.9%50.4%
Recent Momentum (10-day) % -12.71%-18.67%
📊 Statistical Measures
Average Price 0.760.03
Median Price 0.710.03
Price Std Deviation 0.280.01
🚀 Returns & Growth
CAGR % -77.55%-52.15%
Annualized Return % -77.55%-52.15%
Total Return % -75.43%-49.98%
⚠️ Risk & Volatility
Daily Volatility % 6.84%7.12%
Annualized Volatility % 130.64%136.01%
Max Drawdown % -82.13%-63.13%
Sharpe Ratio -0.0320.007
Sortino Ratio -0.0460.007
Calmar Ratio -0.944-0.826
Ulcer Index 67.7839.78
📅 Daily Performance
Win Rate % 46.1%49.6%
Positive Days 158170
Negative Days 185173
Best Day % +94.89%+43.84%
Worst Day % -26.08%-27.20%
Avg Gain (Up Days) % +3.23%+5.08%
Avg Loss (Down Days) % -3.17%-4.90%
Profit Factor 0.871.02
🔥 Streaks & Patterns
Longest Win Streak days 66
Longest Loss Streak days 105
💹 Trading Metrics
Omega Ratio 0.8701.019
Expectancy % -0.22%+0.05%
Kelly Criterion % 0.00%0.19%
📅 Weekly Performance
Best Week % +76.23%+79.71%
Worst Week % -39.02%-40.63%
Weekly Win Rate % 50.0%53.8%
📆 Monthly Performance
Best Month % +68.82%+77.87%
Worst Month % -50.60%-51.61%
Monthly Win Rate % 30.8%46.2%
🔧 Technical Indicators
RSI (14-period) 37.3527.90
Price vs 50-Day MA % -17.03%-29.00%
Price vs 200-Day MA % -9.17%-25.92%
💰 Volume Analysis
Avg Volume 8,111,3003,292,717
Total Volume 2,790,287,2571,129,401,918

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 MV (MV): 0.461 (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
MV: Kraken