PYTH PYTH / MEMEFI Crypto vs RENDER RENDER / USD Crypto

Stats Comprehensive Analytics for the Selected Time Period

Detailed statistical analysis including performance metrics, risk indicators, technical analysis, and advanced ratios.

Settings

Asset PYTH / MEMEFIRENDER / USD
📈 Performance Metrics
Start Price 72.204.70
End Price 127.833.35
Price Change % +77.05%-28.64%
Period High 210.4310.49
Period Low 23.162.73
Price Range % 808.5%284.1%
🏆 All-Time Records
All-Time High 210.4310.49
Days Since ATH 175 days307 days
Distance From ATH % -39.3%-68.1%
All-Time Low 23.162.73
Distance From ATL % +451.9%+22.7%
New ATHs Hit 17 times14 times
📌 Easy-to-Understand Stats
Avg Daily Change % 6.05%4.17%
Biggest Jump (1 Day) % +66.67+1.42
Biggest Drop (1 Day) % -89.05-1.35
Days Above Avg % 41.0%28.3%
Extreme Moves days 11 (3.4%)14 (4.1%)
Stability Score % 85.6%0.0%
Trend Strength % 52.6%51.2%
Recent Momentum (10-day) % +11.01%-2.87%
📊 Statistical Measures
Average Price 105.014.80
Median Price 94.864.06
Price Std Deviation 40.511.78
🚀 Returns & Growth
CAGR % +91.47%-30.24%
Annualized Return % +91.47%-30.24%
Total Return % +77.05%-28.64%
⚠️ Risk & Volatility
Daily Volatility % 15.11%5.34%
Annualized Volatility % 288.67%101.99%
Max Drawdown % -88.99%-73.97%
Sharpe Ratio 0.0740.008
Sortino Ratio 0.1030.008
Calmar Ratio 1.028-0.409
Ulcer Index 44.9255.60
📅 Daily Performance
Win Rate % 52.6%48.8%
Positive Days 169167
Negative Days 152175
Best Day % +172.62%+23.05%
Worst Day % -60.43%-16.14%
Avg Gain (Up Days) % +7.69%+4.26%
Avg Loss (Down Days) % -6.18%-3.99%
Profit Factor 1.381.02
🔥 Streaks & Patterns
Longest Win Streak days 87
Longest Loss Streak days 76
💹 Trading Metrics
Omega Ratio 1.3821.021
Expectancy % +1.12%+0.04%
Kelly Criterion % 2.36%0.25%
📅 Weekly Performance
Best Week % +223.47%+34.12%
Worst Week % -75.31%-24.59%
Weekly Win Rate % 62.5%54.9%
📆 Monthly Performance
Best Month % +138.02%+89.35%
Worst Month % -74.69%-29.02%
Monthly Win Rate % 58.3%33.3%
🔧 Technical Indicators
RSI (14-period) 81.6251.64
Price vs 50-Day MA % +19.43%-7.58%
Price vs 200-Day MA % +27.65%-12.80%
💰 Volume Analysis
Avg Volume 1,170,213,818280,549
Total Volume 376,808,849,44696,228,192

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 RENDER (RENDER): -0.383 (Moderate negative)

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
RENDER: Kraken