PYTH PYTH / SIS Crypto vs MKR MKR / SIS 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 / SISMKR / SIS
📈 Performance Metrics
Start Price 4.1416,364.15
End Price 1.4121,458.86
Price Change % -65.89%+31.13%
Period High 4.1438,995.91
Period Low 1.3810,094.94
Price Range % 200.0%286.3%
🏆 All-Time Records
All-Time High 4.1438,995.91
Days Since ATH 343 days70 days
Distance From ATH % -65.9%-45.0%
All-Time Low 1.3810,094.94
Distance From ATL % +2.3%+112.6%
New ATHs Hit 0 times21 times
📌 Easy-to-Understand Stats
Avg Daily Change % 4.53%3.94%
Biggest Jump (1 Day) % +1.54+4,355.43
Biggest Drop (1 Day) % -0.71-6,603.15
Days Above Avg % 44.8%52.5%
Extreme Moves days 8 (2.3%)12 (4.3%)
Stability Score % 0.0%100.0%
Trend Strength % 53.1%49.1%
Recent Momentum (10-day) % -12.26%-20.88%
📊 Statistical Measures
Average Price 2.4223,018.87
Median Price 2.3423,849.63
Price Std Deviation 0.588,025.27
🚀 Returns & Growth
CAGR % -68.16%+42.20%
Annualized Return % -68.16%+42.20%
Total Return % -65.89%+31.13%
⚠️ Risk & Volatility
Daily Volatility % 7.53%5.35%
Annualized Volatility % 143.79%102.26%
Max Drawdown % -66.67%-44.97%
Sharpe Ratio -0.0090.045
Sortino Ratio -0.0120.047
Calmar Ratio -1.0220.938
Ulcer Index 43.8621.01
📅 Daily Performance
Win Rate % 46.8%49.1%
Positive Days 160138
Negative Days 182143
Best Day % +88.45%+21.76%
Worst Day % -19.58%-20.96%
Avg Gain (Up Days) % +4.87%+4.31%
Avg Loss (Down Days) % -4.42%-3.69%
Profit Factor 0.971.13
🔥 Streaks & Patterns
Longest Win Streak days 96
Longest Loss Streak days 77
💹 Trading Metrics
Omega Ratio 0.9701.128
Expectancy % -0.07%+0.24%
Kelly Criterion % 0.00%1.52%
📅 Weekly Performance
Best Week % +47.45%+39.79%
Worst Week % -21.19%-30.39%
Weekly Win Rate % 43.4%39.5%
📆 Monthly Performance
Best Month % +52.70%+102.05%
Worst Month % -38.78%-24.76%
Monthly Win Rate % 30.8%27.3%
🔧 Technical Indicators
RSI (14-period) 44.2127.01
Price vs 50-Day MA % -25.08%-24.28%
Price vs 200-Day MA % -32.77%-21.08%

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 MKR (MKR): -0.607 (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
MKR: Kraken