PYTH PYTH / MOG Crypto vs TUT TUT / MOG Crypto

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

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Asset PYTH / MOGTUT / MOG
📈 Performance Metrics
Start Price 183,682.7089,793.23
End Price 244,621.0043,813.49
Price Change % +33.18%-51.21%
Period High 418,913.04140,310.08
Period Low 62,758.9820,949.13
Price Range % 567.5%569.8%
🏆 All-Time Records
All-Time High 418,913.04140,310.08
Days Since ATH 190 days16 days
Distance From ATH % -41.6%-68.8%
All-Time Low 62,758.9820,949.13
Distance From ATL % +289.8%+109.1%
New ATHs Hit 23 times6 times
📌 Easy-to-Understand Stats
Avg Daily Change % 4.96%8.82%
Biggest Jump (1 Day) % +123,936.39+66,309.53
Biggest Drop (1 Day) % -64,854.22-78,134.61
Days Above Avg % 42.7%41.3%
Extreme Moves days 9 (2.6%)6 (3.0%)
Stability Score % 100.0%100.0%
Trend Strength % 53.9%46.0%
Recent Momentum (10-day) % -1.43%-30.89%
📊 Statistical Measures
Average Price 192,022.7157,102.62
Median Price 178,489.0350,209.63
Price Std Deviation 80,060.0126,909.30
🚀 Returns & Growth
CAGR % +35.65%-73.01%
Annualized Return % +35.65%-73.01%
Total Return % +33.18%-51.21%
⚠️ Risk & Volatility
Daily Volatility % 8.57%12.96%
Annualized Volatility % 163.79%247.67%
Max Drawdown % -85.02%-79.37%
Sharpe Ratio 0.0460.041
Sortino Ratio 0.0560.042
Calmar Ratio 0.419-0.920
Ulcer Index 49.6351.36
📅 Daily Performance
Win Rate % 53.9%54.0%
Positive Days 185108
Negative Days 15892
Best Day % +103.46%+95.31%
Worst Day % -25.51%-68.49%
Avg Gain (Up Days) % +5.03%+8.01%
Avg Loss (Down Days) % -5.03%-8.25%
Profit Factor 1.171.14
🔥 Streaks & Patterns
Longest Win Streak days 107
Longest Loss Streak days 65
💹 Trading Metrics
Omega Ratio 1.1701.139
Expectancy % +0.39%+0.53%
Kelly Criterion % 1.56%0.80%
📅 Weekly Performance
Best Week % +90.32%+47.22%
Worst Week % -41.67%-54.88%
Weekly Win Rate % 65.4%71.0%
📆 Monthly Performance
Best Month % +146.78%+96.34%
Worst Month % -47.36%-41.07%
Monthly Win Rate % 53.8%55.6%
🔧 Technical Indicators
RSI (14-period) 61.8137.20
Price vs 50-Day MA % +24.29%-50.54%
Price vs 200-Day MA % +44.68%-23.05%
💰 Volume Analysis
Avg Volume 1,937,445,146,473318,257,595,843,489
Total Volume 666,481,130,386,65963,969,776,764,541,352

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): 0.438 (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