PYTH PYTH / INDEX Crypto vs PYTH PYTH / INDEX 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 / INDEXPYTH / INDEX

📈 Performance Metrics

Start Price 0.140.14

End Price 0.120.12

Price Change % -12.45%-12.45%

Period High 0.190.19

Period Low 0.080.08

Price Range % 149.2%149.2%

🏆 All-Time Records

All-Time High 0.190.19

Days Since ATH 67 days67 days

Distance From ATH % -36.0%-36.0%

All-Time Low 0.080.08

Distance From ATL % +59.5%+59.5%

New ATHs Hit 4 times4 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.82%4.82%

Biggest Jump (1 Day) % +0.10+0.10

Biggest Drop (1 Day) % -0.03-0.03

Days Above Avg % 38.9%38.9%

Extreme Moves days 7 (2.1%)7 (2.1%)

Stability Score % 0.0%0.0%

Trend Strength % 51.0%51.0%

Recent Momentum (10-day) % -3.99%-3.99%

📊 Statistical Measures

Average Price 0.110.11

Median Price 0.100.10

Price Std Deviation 0.020.02

🚀 Returns & Growth

CAGR % -13.27%-13.27%

Annualized Return % -13.27%-13.27%

Total Return % -12.45%-12.45%

⚠️ Risk & Volatility

Daily Volatility % 8.54%8.54%

Annualized Volatility % 163.23%163.23%

Max Drawdown % -49.42%-49.42%

Sharpe Ratio 0.0300.030

Sortino Ratio 0.0420.042

Calmar Ratio -0.268-0.268

Ulcer Index 33.4633.46

📅 Daily Performance

Win Rate % 49.0%49.0%

Positive Days 167167

Negative Days 174174

Best Day % +109.39%+109.39%

Worst Day % -25.78%-25.78%

Avg Gain (Up Days) % +5.18%+5.18%

Avg Loss (Down Days) % -4.46%-4.46%

Profit Factor 1.111.11

🔥 Streaks & Patterns

Longest Win Streak days 66

Longest Loss Streak days 66

💹 Trading Metrics

Omega Ratio 1.1131.113

Expectancy % +0.26%+0.26%

Kelly Criterion % 1.12%1.12%

📅 Weekly Performance

Best Week % +65.86%+65.86%

Worst Week % -31.91%-31.91%

Weekly Win Rate % 57.7%57.7%

📆 Monthly Performance

Best Month % +79.83%+79.83%

Worst Month % -27.90%-27.90%

Monthly Win Rate % 38.5%38.5%

🔧 Technical Indicators

RSI (14-period) 50.9750.97

Price vs 50-Day MA % -5.79%-5.79%

Price vs 200-Day MA % +11.39%+11.39%

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