PYTH PYTH / MOG Crypto vs SPK SPK / 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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🤖 AI Analysis

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Asset PYTH / MOGSPK / MOG

📈 Performance Metrics

Start Price 192,781.5450,430.44

End Price 257,882.19103,643.17

Price Change % +33.77%+105.52%

Period High 418,913.04118,808.35

Period Low 62,758.9816,894.83

Price Range % 567.5%603.2%

🏆 All-Time Records

All-Time High 418,913.04118,808.35

Days Since ATH 215 days21 days

Distance From ATH % -38.4%-12.8%

All-Time Low 62,758.9816,894.83

Distance From ATL % +310.9%+513.5%

New ATHs Hit 20 times3 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.86%7.38%

Biggest Jump (1 Day) % +123,936.39+61,337.77

Biggest Drop (1 Day) % -64,854.22-41,568.34

Days Above Avg % 45.6%53.2%

Extreme Moves days 8 (2.3%)5 (3.6%)

Stability Score % 100.0%100.0%

Trend Strength % 54.5%45.7%

Recent Momentum (10-day) % +3.88%+11.50%

📊 Statistical Measures

Average Price 197,878.4868,075.03

Median Price 188,009.8569,542.46

Price Std Deviation 81,973.0423,668.18

🚀 Returns & Growth

CAGR % +36.29%+554.09%

Annualized Return % +36.29%+554.09%

Total Return % +33.77%+105.52%

⚠️ Risk & Volatility

Daily Volatility % 8.46%14.46%

Annualized Volatility % 161.71%276.33%

Max Drawdown % -85.02%-70.97%

Sharpe Ratio 0.0450.092

Sortino Ratio 0.0570.158

Calmar Ratio 0.4277.808

Ulcer Index 50.2838.07

📅 Daily Performance

Win Rate % 54.5%45.7%

Positive Days 18764

Negative Days 15676

Best Day % +103.46%+111.29%

Worst Day % -21.43%-35.70%

Avg Gain (Up Days) % +4.87%+10.11%

Avg Loss (Down Days) % -5.00%-6.06%

Profit Factor 1.171.41

🔥 Streaks & Patterns

Longest Win Streak days 105

Longest Loss Streak days 66

💹 Trading Metrics

Omega Ratio 1.1691.406

Expectancy % +0.38%+1.34%

Kelly Criterion % 1.58%2.18%

📅 Weekly Performance

Best Week % +90.32%+44.33%

Worst Week % -41.67%-48.79%

Weekly Win Rate % 65.4%50.0%

📆 Monthly Performance

Best Month % +146.78%+85.79%

Worst Month % -47.36%-16.67%

Monthly Win Rate % 46.2%33.3%

🔧 Technical Indicators

RSI (14-period) 56.5461.52

Price vs 50-Day MA % +9.03%+21.58%

Price vs 200-Day MA % +60.15%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 SPK (SPK):	0.671 (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
SPK: Kraken