PYTH PYTH / TREE Crypto vs AFC AFC / TREE 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 / TREEAFC / TREE

📈 Performance Metrics

Start Price 0.190.60

End Price 0.563.10

Price Change % +203.60%+415.66%

Period High 0.693.37

Period Low 0.190.60

Price Range % 274.8%460.4%

🏆 All-Time Records

All-Time High 0.693.37

Days Since ATH 32 days8 days

Distance From ATH % -19.0%-8.0%

All-Time Low 0.190.60

Distance From ATL % +203.6%+415.7%

New ATHs Hit 25 times25 times

📌 Easy-to-Understand Stats

Avg Daily Change % 3.52%4.80%

Biggest Jump (1 Day) % +0.21+0.94

Biggest Drop (1 Day) % -0.07-0.28

Days Above Avg % 67.0%34.8%

Extreme Moves days 3 (2.7%)3 (2.7%)

Stability Score % 0.0%0.0%

Trend Strength % 59.5%55.9%

Recent Momentum (10-day) % +3.50%+12.37%

📊 Statistical Measures

Average Price 0.501.74

Median Price 0.531.33

Price Std Deviation 0.130.78

🚀 Returns & Growth

CAGR % +3,754.31%+21,901.48%

Annualized Return % +3,754.31%+21,901.48%

Total Return % +203.60%+415.66%

⚠️ Risk & Volatility

Daily Volatility % 7.08%8.62%

Annualized Volatility % 135.17%164.73%

Max Drawdown % -26.43%-26.50%

Sharpe Ratio 0.1720.210

Sortino Ratio 0.2690.327

Calmar Ratio 142.063826.388

Ulcer Index 12.388.68

📅 Daily Performance

Win Rate % 59.5%55.9%

Positive Days 6662

Negative Days 4549

Best Day % +56.29%+63.91%

Worst Day % -14.23%-21.48%

Avg Gain (Up Days) % +4.24%+6.39%

Avg Loss (Down Days) % -3.22%-3.99%

Profit Factor 1.932.03

🔥 Streaks & Patterns

Longest Win Streak days 64

Longest Loss Streak days 54

💹 Trading Metrics

Omega Ratio 1.9332.026

Expectancy % +1.22%+1.81%

Kelly Criterion % 8.91%7.08%

📅 Weekly Performance

Best Week % +43.16%+41.39%

Worst Week % -12.52%-15.09%

Weekly Win Rate % 66.7%66.7%

📆 Monthly Performance

Best Month % +144.64%+48.94%

Worst Month % -14.69%-7.99%

Monthly Win Rate % 66.7%83.3%

🔧 Technical Indicators

RSI (14-period) 65.0164.58

Price vs 50-Day MA % -5.38%+25.73%

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 AFC (AFC):	0.612 (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
AFC: Bybit