PYTH PYTH / INDEX Crypto vs REQ REQ / USD 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 / INDEXREQ / USD

📈 Performance Metrics

Start Price 0.140.09

End Price 0.130.13

Price Change % -4.13%+37.76%

Period High 0.190.16

Period Low 0.080.09

Price Range % 149.2%83.8%

🏆 All-Time Records

All-Time High 0.190.16

Days Since ATH 48 days157 days

Distance From ATH % -33.0%-18.0%

All-Time Low 0.080.09

Distance From ATL % +66.8%+50.6%

New ATHs Hit 7 times16 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.80%2.61%

Biggest Jump (1 Day) % +0.10+0.02

Biggest Drop (1 Day) % -0.03-0.03

Days Above Avg % 38.6%48.3%

Extreme Moves days 8 (2.3%)14 (4.1%)

Stability Score % 0.0%0.0%

Trend Strength % 49.9%55.1%

Recent Momentum (10-day) % -8.17%-1.85%

📊 Statistical Measures

Average Price 0.110.13

Median Price 0.100.13

Price Std Deviation 0.020.02

🚀 Returns & Growth

CAGR % -4.42%+40.62%

Annualized Return % -4.42%+40.62%

Total Return % -4.13%+37.76%

⚠️ Risk & Volatility

Daily Volatility % 8.58%3.88%

Annualized Volatility % 163.87%74.19%

Max Drawdown % -49.42%-44.78%

Sharpe Ratio 0.0340.044

Sortino Ratio 0.0450.040

Calmar Ratio -0.0890.907

Ulcer Index 32.2721.24

📅 Daily Performance

Win Rate % 50.1%56.1%

Positive Days 171189

Negative Days 170148

Best Day % +109.39%+17.98%

Worst Day % -25.78%-19.63%

Avg Gain (Up Days) % +5.08%+2.58%

Avg Loss (Down Days) % -4.53%-2.90%

Profit Factor 1.131.14

🔥 Streaks & Patterns

Longest Win Streak days 611

Longest Loss Streak days 66

💹 Trading Metrics

Omega Ratio 1.1271.136

Expectancy % +0.29%+0.17%

Kelly Criterion % 1.25%2.31%

📅 Weekly Performance

Best Week % +65.86%+18.96%

Worst Week % -31.91%-18.42%

Weekly Win Rate % 55.8%59.6%

📆 Monthly Performance

Best Month % +79.83%+33.19%

Worst Month % -27.90%-6.91%

Monthly Win Rate % 53.8%69.2%

🔧 Technical Indicators

RSI (14-period) 42.1651.58

Price vs 50-Day MA % -8.16%+2.76%

Price vs 200-Day MA % +18.36%-2.79%

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 REQ (REQ):	-0.078 (Weak)

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
REQ: Kraken