PYTH PYTH / BBSOL Crypto vs ACM ACM / 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

Ask me anything about the statistics below. I can help explain metrics, identify patterns, or answer specific questions.
Asset PYTH / BBSOLACM / USD
📈 Performance Metrics
Start Price 0.001.59
End Price 0.000.62
Price Change % -71.34%-61.18%
Period High 0.002.07
Period Low 0.000.56
Price Range % 333.7%268.9%
🏆 All-Time Records
All-Time High 0.002.07
Days Since ATH 320 days314 days
Distance From ATH % -73.3%-70.2%
All-Time Low 0.000.56
Distance From ATL % +15.8%+10.0%
New ATHs Hit 2 times12 times
📌 Easy-to-Understand Stats
Avg Daily Change % 3.12%2.89%
Biggest Jump (1 Day) % +0.00+0.26
Biggest Drop (1 Day) % 0.00-0.27
Days Above Avg % 39.8%31.7%
Extreme Moves days 7 (2.0%)14 (4.1%)
Stability Score % 0.0%0.0%
Trend Strength % 56.6%51.6%
Recent Momentum (10-day) % -12.09%-28.39%
📊 Statistical Measures
Average Price 0.001.07
Median Price 0.000.93
Price Std Deviation 0.000.34
🚀 Returns & Growth
CAGR % -73.55%-63.47%
Annualized Return % -73.55%-63.47%
Total Return % -71.34%-61.18%
⚠️ Risk & Volatility
Daily Volatility % 6.34%4.48%
Annualized Volatility % 121.06%85.50%
Max Drawdown % -76.94%-72.89%
Sharpe Ratio -0.032-0.039
Sortino Ratio -0.050-0.040
Calmar Ratio -0.956-0.871
Ulcer Index 56.8050.64
📅 Daily Performance
Win Rate % 43.4%47.2%
Positive Days 149158
Negative Days 194177
Best Day % +88.65%+27.66%
Worst Day % -17.49%-29.15%
Avg Gain (Up Days) % +3.36%+2.89%
Avg Loss (Down Days) % -2.95%-2.92%
Profit Factor 0.880.88
🔥 Streaks & Patterns
Longest Win Streak days 64
Longest Loss Streak days 96
💹 Trading Metrics
Omega Ratio 0.8770.884
Expectancy % -0.20%-0.18%
Kelly Criterion % 0.00%0.00%
📅 Weekly Performance
Best Week % +54.45%+27.70%
Worst Week % -26.28%-18.97%
Weekly Win Rate % 32.7%50.0%
📆 Monthly Performance
Best Month % +33.49%+26.44%
Worst Month % -34.74%-18.00%
Monthly Win Rate % 23.1%38.5%
🔧 Technical Indicators
RSI (14-period) 49.1823.10
Price vs 50-Day MA % -8.73%-26.57%
Price vs 200-Day MA % -18.43%-28.68%
💰 Volume Analysis
Avg Volume 9,4931,445,053
Total Volume 3,265,710497,098,110

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 ACM (ACM): 0.898 (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
ACM: Binance