PYTH PYTH / D Crypto vs ACM ACM / D 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 / DACM / D
📈 Performance Metrics
Start Price 1.808.01
End Price 4.4134.46
Price Change % +144.34%+330.51%
Period High 6.9134.60
Period Low 1.808.01
Price Range % 282.8%332.2%
🏆 All-Time Records
All-Time High 6.9134.60
Days Since ATH 74 days1 days
Distance From ATH % -36.2%-0.4%
All-Time Low 1.808.01
Distance From ATL % +144.3%+330.5%
New ATHs Hit 18 times36 times
📌 Easy-to-Understand Stats
Avg Daily Change % 3.39%3.47%
Biggest Jump (1 Day) % +3.36+5.67
Biggest Drop (1 Day) % -0.98-3.74
Days Above Avg % 33.3%54.9%
Extreme Moves days 8 (2.6%)16 (5.2%)
Stability Score % 0.0%74.4%
Trend Strength % 52.5%51.8%
Recent Momentum (10-day) % -6.91%+7.75%
📊 Statistical Measures
Average Price 3.5422.18
Median Price 3.3323.01
Price Std Deviation 0.936.61
🚀 Returns & Growth
CAGR % +191.29%+473.73%
Annualized Return % +191.29%+473.73%
Total Return % +144.34%+330.51%
⚠️ Risk & Volatility
Daily Volatility % 7.33%5.68%
Annualized Volatility % 140.02%108.43%
Max Drawdown % -38.83%-31.16%
Sharpe Ratio 0.0700.112
Sortino Ratio 0.1000.132
Calmar Ratio 4.92715.203
Ulcer Index 19.1011.69
📅 Daily Performance
Win Rate % 52.5%51.8%
Positive Days 160158
Negative Days 145147
Best Day % +94.97%+31.81%
Worst Day % -31.31%-28.05%
Avg Gain (Up Days) % +3.85%+4.27%
Avg Loss (Down Days) % -3.17%-3.26%
Profit Factor 1.341.41
🔥 Streaks & Patterns
Longest Win Streak days 1013
Longest Loss Streak days 87
💹 Trading Metrics
Omega Ratio 1.3391.406
Expectancy % +0.51%+0.64%
Kelly Criterion % 4.19%4.58%
📅 Weekly Performance
Best Week % +65.49%+23.88%
Worst Week % -14.00%-9.48%
Weekly Win Rate % 60.9%65.2%
📆 Monthly Performance
Best Month % +72.99%+45.96%
Worst Month % -13.59%-9.35%
Monthly Win Rate % 66.7%75.0%
🔧 Technical Indicators
RSI (14-period) 26.4177.85
Price vs 50-Day MA % -10.03%+14.25%
Price vs 200-Day MA % +11.13%+31.93%
💰 Volume Analysis
Avg Volume 57,511,23845,194,448
Total Volume 17,598,438,85713,829,500,962

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): 0.783 (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
ByBit Futures Trading Trade hundreds of crypto perpetual futures