PYTH PYTH / ALGO Crypto vs VOXEL VOXEL / 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

Model:

Ask me anything about the statistics below. I can help explain metrics, identify patterns, or answer specific questions.

Asset PYTH / ALGOVOXEL / ALGO

📈 Performance Metrics

Start Price 2.951.22

End Price 0.600.23

Price Change % -79.69%-81.53%

Period High 3.251.25

Period Low 0.410.11

Price Range % 702.3%987.5%

🏆 All-Time Records

All-Time High 3.251.25

Days Since ATH 341 days342 days

Distance From ATH % -81.6%-81.9%

All-Time Low 0.410.11

Distance From ATL % +47.7%+96.4%

New ATHs Hit 2 times1 times

📌 Easy-to-Understand Stats

Avg Daily Change % 3.80%4.80%

Biggest Jump (1 Day) % +0.44+0.22

Biggest Drop (1 Day) % -0.43-0.18

Days Above Avg % 25.0%36.9%

Extreme Moves days 8 (2.3%)11 (3.2%)

Stability Score % 0.0%0.0%

Trend Strength % 53.4%57.4%

Recent Momentum (10-day) % -6.81%-5.81%

📊 Statistical Measures

Average Price 0.830.37

Median Price 0.720.33

Price Std Deviation 0.460.19

🚀 Returns & Growth

CAGR % -81.67%-83.43%

Annualized Return % -81.67%-83.43%

Total Return % -79.69%-81.53%

⚠️ Risk & Volatility

Daily Volatility % 6.92%10.46%

Annualized Volatility % 132.12%199.76%

Max Drawdown % -87.54%-90.80%

Sharpe Ratio -0.039-0.007

Sortino Ratio -0.054-0.011

Calmar Ratio -0.933-0.919

Ulcer Index 75.9572.00

📅 Daily Performance

Win Rate % 46.6%42.6%

Positive Days 160146

Negative Days 183197

Best Day % +94.89%+132.07%

Worst Day % -26.08%-39.26%

Avg Gain (Up Days) % +3.23%+5.51%

Avg Loss (Down Days) % -3.33%-4.21%

Profit Factor 0.850.97

🔥 Streaks & Patterns

Longest Win Streak days 66

Longest Loss Streak days 108

💹 Trading Metrics

Omega Ratio 0.8480.970

Expectancy % -0.27%-0.07%

Kelly Criterion % 0.00%0.00%

📅 Weekly Performance

Best Week % +76.23%+291.34%

Worst Week % -39.02%-48.95%

Weekly Win Rate % 50.0%36.5%

📆 Monthly Performance

Best Month % +68.82%+52.51%

Worst Month % -61.98%-59.70%

Monthly Win Rate % 30.8%53.8%

🔧 Technical Indicators

RSI (14-period) 25.8945.30

Price vs 50-Day MA % -14.40%-6.67%

Price vs 200-Day MA % -3.82%-15.31%

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 VOXEL (VOXEL):	0.936 (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
VOXEL: Coinbase