PYTH PYTH / LUNC Crypto vs SQT SQT / 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 / LUNCSQT / USD
📈 Performance Metrics
Start Price 3,765.160.01
End Price 2,715.390.00
Price Change % -27.88%-90.81%
Period High 3,961.560.01
Period Low 1,628.480.00
Price Range % 143.3%1,666.3%
🏆 All-Time Records
All-Time High 3,961.560.01
Days Since ATH 342 days328 days
Distance From ATH % -31.5%-92.0%
All-Time Low 1,628.480.00
Distance From ATL % +66.7%+41.2%
New ATHs Hit 1 times1 times
📌 Easy-to-Understand Stats
Avg Daily Change % 3.03%5.24%
Biggest Jump (1 Day) % +1,827.83+0.00
Biggest Drop (1 Day) % -468.110.00
Days Above Avg % 48.8%29.1%
Extreme Moves days 6 (1.7%)10 (3.0%)
Stability Score % 99.8%0.0%
Trend Strength % 52.2%62.0%
Recent Momentum (10-day) % +6.23%-28.26%
📊 Statistical Measures
Average Price 2,628.670.00
Median Price 2,586.810.00
Price Std Deviation 596.400.00
🚀 Returns & Growth
CAGR % -29.38%-92.75%
Annualized Return % -29.38%-92.75%
Total Return % -27.88%-90.81%
⚠️ Risk & Volatility
Daily Volatility % 6.37%8.88%
Annualized Volatility % 121.66%169.71%
Max Drawdown % -58.89%-94.34%
Sharpe Ratio 0.009-0.043
Sortino Ratio 0.016-0.067
Calmar Ratio -0.499-0.983
Ulcer Index 36.8676.88
📅 Daily Performance
Win Rate % 47.8%37.4%
Positive Days 164123
Negative Days 179206
Best Day % +93.85%+73.41%
Worst Day % -15.88%-17.36%
Avg Gain (Up Days) % +3.23%+5.95%
Avg Loss (Down Days) % -2.85%-4.17%
Profit Factor 1.040.85
🔥 Streaks & Patterns
Longest Win Streak days 105
Longest Loss Streak days 87
💹 Trading Metrics
Omega Ratio 1.0400.852
Expectancy % +0.06%-0.39%
Kelly Criterion % 0.64%0.00%
📅 Weekly Performance
Best Week % +62.46%+28.30%
Worst Week % -15.52%-36.57%
Weekly Win Rate % 55.8%28.0%
📆 Monthly Performance
Best Month % +63.24%+33.51%
Worst Month % -22.89%-44.45%
Monthly Win Rate % 46.2%15.4%
🔧 Technical Indicators
RSI (14-period) 60.7138.24
Price vs 50-Day MA % -1.79%-11.74%
Price vs 200-Day MA % +17.79%-38.53%

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 SQT (SQT): 0.727 (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
SQT: Bybit