PYTH PYTH / ALGO Crypto vs BCUT BCUT / ALGO Crypto

Stats Comprehensive Analytics for the Selected Time Period

Detailed statistical analysis including performance metrics, risk indicators, technical analysis, and advanced ratios.

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🤖 AI Analysis

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Asset PYTH / ALGOBCUT / ALGO

📈 Performance Metrics

Start Price 1.040.23

End Price 0.520.04

Price Change % -50.26%-82.59%

Period High 1.190.29

Period Low 0.410.04

Price Range % 194.6%628.1%

🏆 All-Time Records

All-Time High 1.190.29

Days Since ATH 333 days312 days

Distance From ATH % -56.8%-86.3%

All-Time Low 0.410.04

Distance From ATL % +27.3%+0.0%

New ATHs Hit 4 times1 times

📌 Easy-to-Understand Stats

Avg Daily Change % 2.80%4.91%

Biggest Jump (1 Day) % +0.44+0.08

Biggest Drop (1 Day) % -0.12-0.03

Days Above Avg % 52.9%49.2%

Extreme Moves days 6 (1.7%)10 (3.2%)

Stability Score % 0.0%0.0%

Trend Strength % 54.8%53.5%

Recent Momentum (10-day) % -3.24%-21.60%

📊 Statistical Measures

Average Price 0.690.11

Median Price 0.700.11

Price Std Deviation 0.160.05

🚀 Returns & Growth

CAGR % -52.44%-86.89%

Annualized Return % -52.44%-86.89%

Total Return % -50.26%-82.59%

⚠️ Risk & Volatility

Daily Volatility % 6.37%6.76%

Annualized Volatility % 121.71%129.17%

Max Drawdown % -66.06%-86.27%

Sharpe Ratio -0.008-0.050

Sortino Ratio -0.014-0.058

Calmar Ratio -0.794-1.007

Ulcer Index 44.0264.15

📅 Daily Performance

Win Rate % 45.2%46.5%

Positive Days 155146

Negative Days 188168

Best Day % +94.89%+38.87%

Worst Day % -15.91%-20.99%

Avg Gain (Up Days) % +3.03%+4.70%

Avg Loss (Down Days) % -2.59%-4.72%

Profit Factor 0.960.87

🔥 Streaks & Patterns

Longest Win Streak days 66

Longest Loss Streak days 107

💹 Trading Metrics

Omega Ratio 0.9650.866

Expectancy % -0.05%-0.34%

Kelly Criterion % 0.00%0.00%

📅 Weekly Performance

Best Week % +76.23%+47.98%

Worst Week % -17.04%-28.62%

Weekly Win Rate % 48.1%35.4%

📆 Monthly Performance

Best Month % +68.82%+17.65%

Worst Month % -21.88%-41.99%

Monthly Win Rate % 30.8%16.7%

🔧 Technical Indicators

RSI (14-period) 43.9922.40

Price vs 50-Day MA % -14.01%-37.69%

Price vs 200-Day MA % -13.26%-53.94%

💰 Volume Analysis

Avg Volume 8,350,62922,432,386

Total Volume 2,872,616,4097,066,201,508

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 BCUT (BCUT):	0.796 (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
BCUT: Bybit