PYTH PYTH / INDEX Crypto vs XDC XDC / 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

Ask me anything about the statistics below. I can help explain metrics, identify patterns, or answer specific questions.
Asset PYTH / INDEXXDC / USD
📈 Performance Metrics
Start Price 0.130.08
End Price 0.120.05
Price Change % -13.20%-35.06%
Period High 0.190.08
Period Low 0.080.05
Price Range % 149.2%57.1%
🏆 All-Time Records
All-Time High 0.190.08
Days Since ATH 55 days49 days
Distance From ATH % -39.4%-35.8%
All-Time Low 0.080.05
Distance From ATL % +50.9%+0.9%
New ATHs Hit 7 times1 times
📌 Easy-to-Understand Stats
Avg Daily Change % 4.69%2.37%
Biggest Jump (1 Day) % +0.10+0.00
Biggest Drop (1 Day) % -0.03-0.01
Days Above Avg % 38.6%71.7%
Extreme Moves days 7 (2.1%)3 (5.8%)
Stability Score % 0.0%0.0%
Trend Strength % 50.7%51.9%
Recent Momentum (10-day) % -13.70%-13.04%
📊 Statistical Measures
Average Price 0.110.07
Median Price 0.100.07
Price Std Deviation 0.020.01
🚀 Returns & Growth
CAGR % -14.06%-95.17%
Annualized Return % -14.06%-95.17%
Total Return % -13.20%-35.06%
⚠️ Risk & Volatility
Daily Volatility % 8.47%3.80%
Annualized Volatility % 161.83%72.57%
Max Drawdown % -49.42%-36.36%
Sharpe Ratio 0.029-0.197
Sortino Ratio 0.041-0.156
Calmar Ratio -0.285-2.618
Ulcer Index 32.6617.07
📅 Daily Performance
Win Rate % 49.3%48.1%
Positive Days 16825
Negative Days 17327
Best Day % +109.39%+8.31%
Worst Day % -25.78%-18.79%
Avg Gain (Up Days) % +5.03%+1.77%
Avg Loss (Down Days) % -4.40%-3.08%
Profit Factor 1.110.53
🔥 Streaks & Patterns
Longest Win Streak days 66
Longest Loss Streak days 65
💹 Trading Metrics
Omega Ratio 1.1120.532
Expectancy % +0.25%-0.75%
Kelly Criterion % 1.13%0.00%
📅 Weekly Performance
Best Week % +65.86%+8.88%
Worst Week % -31.91%-15.12%
Weekly Win Rate % 53.8%33.3%
📆 Monthly Performance
Best Month % +79.83%+-2.03%
Worst Month % -27.90%-13.86%
Monthly Win Rate % 46.2%0.0%
🔧 Technical Indicators
RSI (14-period) 33.2536.37
Price vs 50-Day MA % -14.12%-26.26%
Price vs 200-Day MA % +6.36%N/A
💰 Volume Analysis
Avg Volume 1,414,7185,227,031
Total Volume 483,833,528277,032,627

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 XDC (XDC): 0.763 (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
XDC: Kraken