PYTH PYTH / OPEN Crypto vs CFX CFX / USD 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 / OPENCFX / USD

📈 Performance Metrics

Start Price 0.110.13

End Price 0.320.09

Price Change % +181.52%-28.64%

Period High 0.360.26

Period Low 0.110.06

Price Range % 220.0%303.3%

🏆 All-Time Records

All-Time High 0.360.26

Days Since ATH 11 days314 days

Distance From ATH % -12.0%-65.1%

All-Time Low 0.110.06

Distance From ATL % +181.5%+40.8%

New ATHs Hit 12 times15 times

📌 Easy-to-Understand Stats

Avg Daily Change % 7.52%4.55%

Biggest Jump (1 Day) % +0.04+0.11

Biggest Drop (1 Day) % -0.10-0.05

Days Above Avg % 50.0%49.7%

Extreme Moves days 3 (8.6%)8 (2.3%)

Stability Score % 0.0%0.0%

Trend Strength % 65.7%49.9%

Recent Momentum (10-day) % -1.67%-13.18%

📊 Statistical Measures

Average Price 0.240.13

Median Price 0.240.13

Price Std Deviation 0.060.05

🚀 Returns & Growth

CAGR % +4,873,156.55%-30.17%

Annualized Return % +4,873,156.55%-30.17%

Total Return % +181.52%-28.64%

⚠️ Risk & Volatility

Daily Volatility % 10.19%8.20%

Annualized Volatility % 194.77%156.71%

Max Drawdown % -30.76%-75.20%

Sharpe Ratio 0.3460.021

Sortino Ratio 0.3630.029

Calmar Ratio 158,440.553-0.401

Ulcer Index 14.0051.26

📅 Daily Performance

Win Rate % 65.7%49.3%

Positive Days 23166

Negative Days 12171

Best Day % +29.80%+107.26%

Worst Day % -29.05%-30.32%

Avg Gain (Up Days) % +8.76%+4.79%

Avg Loss (Down Days) % -6.50%-4.30%

Profit Factor 2.581.08

🔥 Streaks & Patterns

Longest Win Streak days 97

Longest Loss Streak days 47

💹 Trading Metrics

Omega Ratio 2.5821.082

Expectancy % +3.53%+0.18%

Kelly Criterion % 6.19%0.87%

📅 Weekly Performance

Best Week % +47.17%+116.01%

Worst Week % -14.26%-25.37%

Weekly Win Rate % 57.1%44.2%

📆 Monthly Performance

Best Month % +207.62%+195.32%

Worst Month % -25.85%-31.44%

Monthly Win Rate % 66.7%23.1%

🔧 Technical Indicators

RSI (14-period) 54.6021.83

Price vs 50-Day MA % N/A-43.96%

Price vs 200-Day MA % N/A-25.88%

💰 Volume Analysis

Avg Volume 3,710,956102,388,193

Total Volume 133,594,39935,221,538,522

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 CFX (CFX):	-0.724 (Strong 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
CFX: Binance