TREE TREE / MOG Crypto vs PYTH PYTH / MOG Crypto

Stats Comprehensive Analytics for the Selected Time Period

Detailed statistical analysis including performance metrics, risk indicators, technical analysis, and advanced ratios.

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🤖 AI Analysis

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Asset TREE / MOGPYTH / MOG

📈 Performance Metrics

Start Price 478,102.19222,643.53

End Price 420,262.06239,629.27

Price Change % -12.10%+7.63%

Period High 555,222.76418,913.04

Period Low 275,440.5462,758.98

Price Range % 101.6%567.5%

🏆 All-Time Records

All-Time High 555,222.76418,913.04

Days Since ATH 9 days220 days

Distance From ATH % -24.3%-42.8%

All-Time Low 275,440.5462,758.98

Distance From ATL % +52.6%+281.8%

New ATHs Hit 3 times19 times

📌 Easy-to-Understand Stats

Avg Daily Change % 5.21%4.82%

Biggest Jump (1 Day) % +96,544.04+123,936.39

Biggest Drop (1 Day) % -104,875.05-64,854.22

Days Above Avg % 54.2%46.2%

Extreme Moves days 8 (7.5%)8 (2.3%)

Stability Score % 100.0%100.0%

Trend Strength % 54.7%54.2%

Recent Momentum (10-day) % +1.72%-2.28%

📊 Statistical Measures

Average Price 376,099.94198,349.84

Median Price 380,116.24188,009.85

Price Std Deviation 60,272.5782,109.05

🚀 Returns & Growth

CAGR % -35.85%+8.14%

Annualized Return % -35.85%+8.14%

Total Return % -12.10%+7.63%

⚠️ Risk & Volatility

Daily Volatility % 7.51%8.44%

Annualized Volatility % 143.52%161.18%

Max Drawdown % -42.39%-85.02%

Sharpe Ratio 0.0200.038

Sortino Ratio 0.0240.047

Calmar Ratio -0.8460.096

Ulcer Index 25.2550.28

📅 Daily Performance

Win Rate % 45.3%54.2%

Positive Days 48186

Negative Days 58157

Best Day % +30.18%+103.46%

Worst Day % -21.94%-21.43%

Avg Gain (Up Days) % +5.88%+4.80%

Avg Loss (Down Days) % -4.59%-4.99%

Profit Factor 1.061.14

🔥 Streaks & Patterns

Longest Win Streak days 410

Longest Loss Streak days 76

💹 Trading Metrics

Omega Ratio 1.0601.139

Expectancy % +0.15%+0.32%

Kelly Criterion % 0.56%1.33%

📅 Weekly Performance

Best Week % +32.94%+90.32%

Worst Week % -26.96%-39.02%

Weekly Win Rate % 58.8%63.5%

📆 Monthly Performance

Best Month % +40.63%+146.78%

Worst Month % -19.60%-47.36%

Monthly Win Rate % 33.3%46.2%

🔧 Technical Indicators

RSI (14-period) 51.1747.61

Price vs 50-Day MA % +3.06%-0.46%

Price vs 200-Day MA % N/A+49.35%

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).

TREE (TREE) vs PYTH (PYTH):	0.712 (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

TREE: Kraken
PYTH: Kraken