PYTH PYTH / IMX Crypto vs TREE TREE / IMX 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 / IMXTREE / IMX

📈 Performance Metrics

Start Price 0.251.22

End Price 0.230.45

Price Change % -5.62%-63.37%

Period High 0.421.22

Period Low 0.190.33

Price Range % 125.6%270.4%

🏆 All-Time Records

All-Time High 0.421.22

Days Since ATH 65 days96 days

Distance From ATH % -44.0%-63.4%

All-Time Low 0.190.33

Distance From ATL % +26.3%+35.7%

New ATHs Hit 12 times0 times

📌 Easy-to-Understand Stats

Avg Daily Change % 2.91%4.69%

Biggest Jump (1 Day) % +0.19+0.12

Biggest Drop (1 Day) % -0.05-0.24

Days Above Avg % 45.6%47.4%

Extreme Moves days 7 (2.0%)5 (5.2%)

Stability Score % 0.0%0.0%

Trend Strength % 53.4%55.2%

Recent Momentum (10-day) % -0.85%+13.39%

📊 Statistical Measures

Average Price 0.250.53

Median Price 0.250.48

Price Std Deviation 0.030.19

🚀 Returns & Growth

CAGR % -5.97%-97.80%

Annualized Return % -5.97%-97.80%

Total Return % -5.62%-63.37%

⚠️ Risk & Volatility

Daily Volatility % 6.18%6.03%

Annualized Volatility % 118.15%115.13%

Max Drawdown % -55.68%-73.00%

Sharpe Ratio 0.021-0.143

Sortino Ratio 0.036-0.141

Calmar Ratio -0.107-1.340

Ulcer Index 29.7958.36

📅 Daily Performance

Win Rate % 46.6%44.8%

Positive Days 16043

Negative Days 18353

Best Day % +90.01%+21.57%

Worst Day % -13.75%-19.95%

Avg Gain (Up Days) % +3.22%+3.96%

Avg Loss (Down Days) % -2.57%-4.77%

Profit Factor 1.100.67

🔥 Streaks & Patterns

Longest Win Streak days 64

Longest Loss Streak days 106

💹 Trading Metrics

Omega Ratio 1.0960.673

Expectancy % +0.13%-0.86%

Kelly Criterion % 1.59%0.00%

📅 Weekly Performance

Best Week % +69.93%+18.71%

Worst Week % -14.90%-24.24%

Weekly Win Rate % 50.9%37.5%

📆 Monthly Performance

Best Month % +61.10%+35.31%

Worst Month % -34.18%-40.59%

Monthly Win Rate % 53.8%20.0%

🔧 Technical Indicators

RSI (14-period) 53.3174.35

Price vs 50-Day MA % +5.17%+15.78%

Price vs 200-Day MA % -1.46%N/A

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 TREE (TREE):	0.231 (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
TREE: Kraken