PYTH PYTH / MOG Crypto vs OPEN OPEN / 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 / MOGOPEN / MOG

📈 Performance Metrics

Start Price 211,623.651,552,989.87

End Price 238,677.09734,115.35

Price Change % +12.78%-52.73%

Period High 418,913.041,552,989.87

Period Low 62,758.98527,837.26

Price Range % 567.5%194.2%

🏆 All-Time Records

All-Time High 418,913.041,552,989.87

Days Since ATH 217 days62 days

Distance From ATH % -43.0%-52.7%

All-Time Low 62,758.98527,837.26

Distance From ATL % +280.3%+39.1%

New ATHs Hit 19 times0 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.86%8.17%

Biggest Jump (1 Day) % +123,936.39+198,075.78

Biggest Drop (1 Day) % -64,854.22-313,974.64

Days Above Avg % 46.2%42.9%

Extreme Moves days 8 (2.3%)1 (1.6%)

Stability Score % 100.0%100.0%

Trend Strength % 54.2%54.8%

Recent Momentum (10-day) % +4.14%+16.50%

📊 Statistical Measures

Average Price 198,155.29842,018.64

Median Price 188,009.85815,072.55

Price Std Deviation 82,036.14169,674.77

🚀 Returns & Growth

CAGR % +13.66%-98.79%

Annualized Return % +13.66%-98.79%

Total Return % +12.78%-52.73%

⚠️ Risk & Volatility

Daily Volatility % 8.46%10.58%

Annualized Volatility % 161.63%202.15%

Max Drawdown % -85.02%-66.01%

Sharpe Ratio 0.040-0.062

Sortino Ratio 0.049-0.067

Calmar Ratio 0.161-1.496

Ulcer Index 50.3847.07

📅 Daily Performance

Win Rate % 54.4%45.2%

Positive Days 18628

Negative Days 15634

Best Day % +103.46%+37.53%

Worst Day % -21.43%-20.22%

Avg Gain (Up Days) % +4.85%+8.32%

Avg Loss (Down Days) % -5.05%-8.05%

Profit Factor 1.150.85

🔥 Streaks & Patterns

Longest Win Streak days 104

Longest Loss Streak days 69

💹 Trading Metrics

Omega Ratio 1.1460.852

Expectancy % +0.34%-0.66%

Kelly Criterion % 1.37%0.00%

📅 Weekly Performance

Best Week % +90.32%+20.47%

Worst Week % -41.67%-33.17%

Weekly Win Rate % 62.3%54.5%

📆 Monthly Performance

Best Month % +146.78%+29.34%

Worst Month % -47.36%-59.44%

Monthly Win Rate % 46.2%50.0%

🔧 Technical Indicators

RSI (14-period) 47.4854.05

Price vs 50-Day MA % +0.07%-7.13%

Price vs 200-Day MA % +48.55%N/A

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 OPEN (OPEN):	-0.325 (Moderate negative)

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
OPEN: Kraken