PYTH PYTH / REPV2 Crypto vs PYTH PYTH / REPV2 Crypto

Stats Comprehensive Analytics for the Selected Time Period

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

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🤖 AI Analysis

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Asset PYTH / REPV2PYTH / REPV2

📈 Performance Metrics

Start Price 0.750.75

End Price 0.060.06

Price Change % -91.81%-91.81%

Period High 0.770.77

Period Low 0.050.05

Price Range % 1,371.6%1,371.6%

🏆 All-Time Records

All-Time High 0.770.77

Days Since ATH 341 days341 days

Distance From ATH % -92.0%-92.0%

All-Time Low 0.050.05

Distance From ATL % +18.0%+18.0%

New ATHs Hit 1 times1 times

📌 Easy-to-Understand Stats

Avg Daily Change % 5.79%5.79%

Biggest Jump (1 Day) % +0.11+0.11

Biggest Drop (1 Day) % -0.24-0.24

Days Above Avg % 28.5%28.5%

Extreme Moves days 9 (2.6%)9 (2.6%)

Stability Score % 0.0%0.0%

Trend Strength % 53.6%53.6%

Recent Momentum (10-day) % +4.94%+4.94%

📊 Statistical Measures

Average Price 0.240.24

Median Price 0.160.16

Price Std Deviation 0.180.18

🚀 Returns & Growth

CAGR % -93.02%-93.02%

Annualized Return % -93.02%-93.02%

Total Return % -91.81%-91.81%

⚠️ Risk & Volatility

Daily Volatility % 9.93%9.93%

Annualized Volatility % 189.63%189.63%

Max Drawdown % -93.20%-93.20%

Sharpe Ratio -0.026-0.026

Sortino Ratio -0.029-0.029

Calmar Ratio -0.998-0.998

Ulcer Index 72.6072.60

📅 Daily Performance

Win Rate % 46.4%46.4%

Positive Days 159159

Negative Days 184184

Best Day % +111.19%+111.19%

Worst Day % -60.12%-60.12%

Avg Gain (Up Days) % +5.67%+5.67%

Avg Loss (Down Days) % -5.37%-5.37%

Profit Factor 0.910.91

🔥 Streaks & Patterns

Longest Win Streak days 55

Longest Loss Streak days 77

💹 Trading Metrics

Omega Ratio 0.9120.912

Expectancy % -0.25%-0.25%

Kelly Criterion % 0.00%0.00%

📅 Weekly Performance

Best Week % +61.28%+61.28%

Worst Week % -41.51%-41.51%

Weekly Win Rate % 46.2%46.2%

📆 Monthly Performance

Best Month % +23.18%+23.18%

Worst Month % -44.11%-44.11%

Monthly Win Rate % 38.5%38.5%

🔧 Technical Indicators

RSI (14-period) 58.9558.95

Price vs 50-Day MA % -28.86%-28.86%

Price vs 200-Day MA % -53.93%-53.93%

💰 Volume Analysis

Avg Volume 2,172,7292,172,729

Total Volume 747,418,848747,418,848

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 PYTH (PYTH):	1.000 (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
PYTH: Kraken