PYTH PYTH / SIS Crypto vs AGI AGI / SIS 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

Model:

Ask me anything about the statistics below. I can help explain metrics, identify patterns, or answer specific questions.

Asset PYTH / SISAGI / SIS

📈 Performance Metrics

Start Price 2.631.26

End Price 1.200.30

Price Change % -54.25%-76.50%

Period High 3.521.51

Period Low 1.130.29

Price Range % 211.0%429.2%

🏆 All-Time Records

All-Time High 3.521.51

Days Since ATH 303 days295 days

Distance From ATH % -65.9%-80.4%

All-Time Low 1.130.29

Distance From ATL % +6.1%+3.5%

New ATHs Hit 8 times5 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.46%4.15%

Biggest Jump (1 Day) % +1.54+0.27

Biggest Drop (1 Day) % -0.53-0.23

Days Above Avg % 45.9%51.6%

Extreme Moves days 8 (2.3%)17 (4.9%)

Stability Score % 0.0%0.0%

Trend Strength % 52.8%53.5%

Recent Momentum (10-day) % -15.80%-13.99%

📊 Statistical Measures

Average Price 2.330.92

Median Price 2.250.93

Price Std Deviation 0.570.29

🚀 Returns & Growth

CAGR % -56.49%-78.49%

Annualized Return % -56.49%-78.49%

Total Return % -54.25%-76.50%

⚠️ Risk & Volatility

Daily Volatility % 7.46%5.78%

Annualized Volatility % 142.46%110.43%

Max Drawdown % -67.84%-81.10%

Sharpe Ratio 0.001-0.044

Sortino Ratio 0.002-0.046

Calmar Ratio -0.833-0.968

Ulcer Index 37.0943.49

📅 Daily Performance

Win Rate % 47.2%46.5%

Positive Days 162160

Negative Days 181184

Best Day % +88.45%+27.55%

Worst Day % -17.66%-18.42%

Avg Gain (Up Days) % +4.85%+4.20%

Avg Loss (Down Days) % -4.33%-4.13%

Profit Factor 1.000.88

🔥 Streaks & Patterns

Longest Win Streak days 96

Longest Loss Streak days 78

💹 Trading Metrics

Omega Ratio 1.0040.885

Expectancy % +0.01%-0.25%

Kelly Criterion % 0.04%0.00%

📅 Weekly Performance

Best Week % +47.45%+29.32%

Worst Week % -21.19%-21.95%

Weekly Win Rate % 44.2%36.5%

📆 Monthly Performance

Best Month % +52.70%+28.56%

Worst Month % -38.78%-32.24%

Monthly Win Rate % 38.5%23.1%

🔧 Technical Indicators

RSI (14-period) 32.2835.71

Price vs 50-Day MA % -26.56%-30.43%

Price vs 200-Day MA % -39.21%-60.24%

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 AGI (AGI):	0.821 (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
AGI: Bybit