PYTH PYTH / USD Crypto vs TUT TUT / USD 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 / USDTUT / USD

📈 Performance Metrics

Start Price 0.450.05

End Price 0.060.01

Price Change % -86.72%-73.29%

Period High 0.450.12

Period Low 0.060.01

Price Range % 664.9%846.0%

🏆 All-Time Records

All-Time High 0.450.12

Days Since ATH 343 days67 days

Distance From ATH % -86.7%-89.3%

All-Time Low 0.060.01

Distance From ATL % +1.6%+0.9%

New ATHs Hit 0 times13 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.58%5.70%

Biggest Jump (1 Day) % +0.11+0.05

Biggest Drop (1 Day) % -0.06-0.07

Days Above Avg % 31.4%45.1%

Extreme Moves days 6 (1.7%)9 (3.7%)

Stability Score % 0.0%0.0%

Trend Strength % 53.1%49.0%

Recent Momentum (10-day) % -10.34%-10.73%

📊 Statistical Measures

Average Price 0.170.04

Median Price 0.140.03

Price Std Deviation 0.080.02

🚀 Returns & Growth

CAGR % -88.33%-86.23%

Annualized Return % -88.33%-86.23%

Total Return % -86.72%-73.29%

⚠️ Risk & Volatility

Daily Volatility % 7.93%9.99%

Annualized Volatility % 151.43%190.80%

Max Drawdown % -86.93%-89.43%

Sharpe Ratio -0.0410.010

Sortino Ratio -0.0530.010

Calmar Ratio -1.016-0.964

Ulcer Index 66.0546.63

📅 Daily Performance

Win Rate % 46.8%51.0%

Positive Days 160124

Negative Days 182119

Best Day % +99.34%+76.53%

Worst Day % -32.57%-77.79%

Avg Gain (Up Days) % +4.60%+5.25%

Avg Loss (Down Days) % -4.65%-5.26%

Profit Factor 0.871.04

🔥 Streaks & Patterns

Longest Win Streak days 77

Longest Loss Streak days 66

💹 Trading Metrics

Omega Ratio 0.8691.039

Expectancy % -0.33%+0.10%

Kelly Criterion % 0.00%0.36%

📅 Weekly Performance

Best Week % +65.86%+25.56%

Worst Week % -23.21%-38.52%

Weekly Win Rate % 48.1%54.1%

📆 Monthly Performance

Best Month % +65.32%+109.71%

Worst Month % -32.91%-21.14%

Monthly Win Rate % 30.8%30.0%

🔧 Technical Indicators

RSI (14-period) 25.1828.11

Price vs 50-Day MA % -30.03%-37.35%

Price vs 200-Day MA % -50.66%-72.87%

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):	0.489 (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