PYTH PYTH / TREE Crypto vs TUT TUT / 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

Ask me anything about the statistics below. I can help explain metrics, identify patterns, or answer specific questions.
Asset PYTH / TREETUT / TREE
📈 Performance Metrics
Start Price 0.190.09
End Price 0.640.12
Price Change % +247.11%+34.01%
Period High 0.690.39
Period Low 0.190.09
Price Range % 274.8%344.6%
🏆 All-Time Records
All-Time High 0.690.39
Days Since ATH 8 days19 days
Distance From ATH % -7.4%-69.9%
All-Time Low 0.190.09
Distance From ATL % +247.1%+34.0%
New ATHs Hit 25 times16 times
📌 Easy-to-Understand Stats
Avg Daily Change % 3.84%8.85%
Biggest Jump (1 Day) % +0.21+0.18
Biggest Drop (1 Day) % -0.07-0.23
Days Above Avg % 61.4%43.2%
Extreme Moves days 2 (2.3%)4 (4.6%)
Stability Score % 0.0%0.0%
Trend Strength % 59.8%58.6%
Recent Momentum (10-day) % +4.42%-47.78%
📊 Statistical Measures
Average Price 0.480.20
Median Price 0.520.19
Price Std Deviation 0.140.08
🚀 Returns & Growth
CAGR % +18,413.06%+241.50%
Annualized Return % +18,413.06%+241.50%
Total Return % +247.11%+34.01%
⚠️ Risk & Volatility
Daily Volatility % 7.73%14.72%
Annualized Volatility % 147.69%281.22%
Max Drawdown % -26.43%-70.44%
Sharpe Ratio 0.2190.105
Sortino Ratio 0.3780.105
Calmar Ratio 696.7503.428
Ulcer Index 9.1530.85
📅 Daily Performance
Win Rate % 59.8%58.6%
Positive Days 5251
Negative Days 3536
Best Day % +56.29%+84.41%
Worst Day % -14.23%-66.30%
Avg Gain (Up Days) % +4.94%+7.88%
Avg Loss (Down Days) % -3.14%-7.41%
Profit Factor 2.341.51
🔥 Streaks & Patterns
Longest Win Streak days 65
Longest Loss Streak days 54
💹 Trading Metrics
Omega Ratio 2.3391.506
Expectancy % +1.69%+1.55%
Kelly Criterion % 10.90%2.66%
📅 Weekly Performance
Best Week % +43.16%+47.72%
Worst Week % -7.91%-12.65%
Weekly Win Rate % 78.6%71.4%
📆 Monthly Performance
Best Month % +144.64%+67.89%
Worst Month % -0.17%1.17%
Monthly Win Rate % 80.0%100.0%
🔧 Technical Indicators
RSI (14-period) 51.2252.99
Price vs 50-Day MA % +11.27%-48.73%
💰 Volume Analysis
Avg Volume 11,972,074516,648,987
Total Volume 1,053,542,49045,465,110,829

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 TUT (TUT): 0.319 (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
TUT: Binance