PYTH PYTH / BNC Crypto vs LAYER LAYER / BNC 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 / BNCLAYER / BNC

📈 Performance Metrics

Start Price 1.735.90

End Price 0.842.51

Price Change % -51.50%-57.46%

Period High 2.2023.49

Period Low 0.732.13

Price Range % 202.0%1,001.7%

🏆 All-Time Records

All-Time High 2.2023.49

Days Since ATH 70 days186 days

Distance From ATH % -61.8%-89.3%

All-Time Low 0.732.13

Distance From ATL % +15.3%+17.7%

New ATHs Hit 2 times20 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.02%5.50%

Biggest Jump (1 Day) % +1.11+2.93

Biggest Drop (1 Day) % -0.52-8.65

Days Above Avg % 39.0%24.6%

Extreme Moves days 7 (2.0%)10 (4.0%)

Stability Score % 0.0%0.0%

Trend Strength % 51.9%51.0%

Recent Momentum (10-day) % -17.87%+2.95%

📊 Statistical Measures

Average Price 1.206.89

Median Price 1.105.58

Price Std Deviation 0.294.22

🚀 Returns & Growth

CAGR % -53.70%-71.73%

Annualized Return % -53.70%-71.73%

Total Return % -51.50%-57.46%

⚠️ Risk & Volatility

Daily Volatility % 7.72%7.32%

Annualized Volatility % 147.53%139.82%

Max Drawdown % -65.51%-90.92%

Sharpe Ratio 0.004-0.008

Sortino Ratio 0.006-0.008

Calmar Ratio -0.820-0.789

Ulcer Index 38.2967.75

📅 Daily Performance

Win Rate % 48.0%48.8%

Positive Days 164120

Negative Days 178126

Best Day % +102.96%+29.05%

Worst Day % -32.37%-40.43%

Avg Gain (Up Days) % +4.25%+4.92%

Avg Loss (Down Days) % -3.86%-4.80%

Profit Factor 1.020.98

🔥 Streaks & Patterns

Longest Win Streak days 85

Longest Loss Streak days 88

💹 Trading Metrics

Omega Ratio 1.0150.975

Expectancy % +0.03%-0.06%

Kelly Criterion % 0.19%0.00%

📅 Weekly Performance

Best Week % +76.91%+54.03%

Worst Week % -21.37%-65.41%

Weekly Win Rate % 38.5%45.9%

📆 Monthly Performance

Best Month % +81.59%+121.35%

Worst Month % -22.30%-74.65%

Monthly Win Rate % 38.5%33.3%

🔧 Technical Indicators

RSI (14-period) 42.6657.27

Price vs 50-Day MA % -32.49%-24.71%

Price vs 200-Day MA % -25.99%-59.71%

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 LAYER (LAYER):	-0.124 (Weak)

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
LAYER: Kraken