PYTH PYTH / MOG Crypto vs FLOW FLOW / 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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Asset PYTH / MOGFLOW / MOG

📈 Performance Metrics

Start Price 229,730.77336,813.19

End Price 284,313.17777,275.30

Price Change % +23.76%+130.77%

Period High 418,913.041,210,144.93

Period Low 62,758.98204,353.53

Price Range % 567.5%492.2%

🏆 All-Time Records

All-Time High 418,913.041,210,144.93

Days Since ATH 198 days198 days

Distance From ATH % -32.1%-35.8%

All-Time Low 62,758.98204,353.53

Distance From ATL % +353.0%+280.4%

New ATHs Hit 19 times24 times

📌 Easy-to-Understand Stats

Avg Daily Change % 5.01%5.04%

Biggest Jump (1 Day) % +123,936.39+146,926.54

Biggest Drop (1 Day) % -64,854.22-245,439.05

Days Above Avg % 42.7%36.0%

Extreme Moves days 10 (2.9%)22 (6.4%)

Stability Score % 100.0%100.0%

Trend Strength % 53.6%52.5%

Recent Momentum (10-day) % +35.84%+52.17%

📊 Statistical Measures

Average Price 193,945.74491,787.12

Median Price 178,647.50419,621.72

Price Std Deviation 81,094.68205,987.41

🚀 Returns & Growth

CAGR % +25.46%+143.49%

Annualized Return % +25.46%+143.49%

Total Return % +23.76%+130.77%

⚠️ Risk & Volatility

Daily Volatility % 8.65%6.78%

Annualized Volatility % 165.23%129.53%

Max Drawdown % -85.02%-83.11%

Sharpe Ratio 0.0440.071

Sortino Ratio 0.0540.069

Calmar Ratio 0.2991.726

Ulcer Index 49.8450.85

📅 Daily Performance

Win Rate % 53.8%52.6%

Positive Days 184180

Negative Days 158162

Best Day % +103.46%+25.87%

Worst Day % -25.51%-26.58%

Avg Gain (Up Days) % +5.08%+5.21%

Avg Loss (Down Days) % -5.09%-4.78%

Profit Factor 1.161.21

🔥 Streaks & Patterns

Longest Win Streak days 1010

Longest Loss Streak days 66

💹 Trading Metrics

Omega Ratio 1.1621.212

Expectancy % +0.38%+0.48%

Kelly Criterion % 1.47%1.93%

📅 Weekly Performance

Best Week % +90.32%+30.28%

Worst Week % -41.67%-39.48%

Weekly Win Rate % 63.5%65.4%

📆 Monthly Performance

Best Month % +146.78%+75.99%

Worst Month % -47.36%-39.27%

Monthly Win Rate % 46.2%53.8%

🔧 Technical Indicators

RSI (14-period) 72.6179.05

Price vs 50-Day MA % +34.21%+48.72%

Price vs 200-Day MA % +70.96%+70.26%

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 FLOW (FLOW):	0.942 (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

PYTH: Kraken
FLOW: Kraken