PYTH PYTH / TRAC Crypto vs SLF SLF / 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 / TRACSLF / USD
📈 Performance Metrics
Start Price 0.530.30
End Price 0.170.02
Price Change % -68.23%-93.02%
Period High 0.610.54
Period Low 0.150.02
Price Range % 311.0%2,478.4%
🏆 All-Time Records
All-Time High 0.610.54
Days Since ATH 56 days290 days
Distance From ATH % -72.2%-96.1%
All-Time Low 0.150.02
Distance From ATL % +14.2%+0.0%
New ATHs Hit 3 times13 times
📌 Easy-to-Understand Stats
Avg Daily Change % 4.43%4.75%
Biggest Jump (1 Day) % +0.29+0.06
Biggest Drop (1 Day) % -0.15-0.10
Days Above Avg % 56.4%54.7%
Extreme Moves days 9 (2.6%)8 (2.6%)
Stability Score % 0.0%0.0%
Trend Strength % 49.6%53.9%
Recent Momentum (10-day) % -36.38%+4.64%
📊 Statistical Measures
Average Price 0.380.20
Median Price 0.390.21
Price Std Deviation 0.090.12
🚀 Returns & Growth
CAGR % -70.48%-95.82%
Annualized Return % -70.48%-95.82%
Total Return % -68.23%-93.02%
⚠️ Risk & Volatility
Daily Volatility % 7.89%10.09%
Annualized Volatility % 150.80%192.77%
Max Drawdown % -75.67%-96.12%
Sharpe Ratio -0.008-0.044
Sortino Ratio -0.009-0.057
Calmar Ratio -0.931-0.997
Ulcer Index 36.0965.86
📅 Daily Performance
Win Rate % 50.4%45.9%
Positive Days 173140
Negative Days 170165
Best Day % +97.56%+106.67%
Worst Day % -44.40%-38.55%
Avg Gain (Up Days) % +4.31%+5.34%
Avg Loss (Down Days) % -4.50%-5.34%
Profit Factor 0.970.85
🔥 Streaks & Patterns
Longest Win Streak days 64
Longest Loss Streak days 46
💹 Trading Metrics
Omega Ratio 0.9730.847
Expectancy % -0.06%-0.44%
Kelly Criterion % 0.00%0.00%
📅 Weekly Performance
Best Week % +84.84%+144.40%
Worst Week % -20.11%-46.53%
Weekly Win Rate % 55.8%39.1%
📆 Monthly Performance
Best Month % +112.15%+70.74%
Worst Month % -27.31%-59.85%
Monthly Win Rate % 38.5%9.1%
🔧 Technical Indicators
RSI (14-period) 44.2352.30
Price vs 50-Day MA % -52.20%-62.91%
Price vs 200-Day MA % -49.45%-85.24%
💰 Volume Analysis
Avg Volume 4,422,76639,690,818
Total Volume 1,521,431,52312,185,081,221

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 SLF (SLF): 0.522 (Moderate 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
SLF: Binance