PYTH PYTH / FTT Crypto vs FIS FIS / FTT 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 / FTTFIS / FTT

📈 Performance Metrics

Start Price 0.140.14

End Price 0.110.04

Price Change % -19.73%-69.84%

Period High 0.260.29

Period Low 0.090.04

Price Range % 189.5%618.0%

🏆 All-Time Records

All-Time High 0.260.29

Days Since ATH 83 days206 days

Distance From ATH % -58.7%-85.9%

All-Time Low 0.090.04

Distance From ATL % +19.6%+1.3%

New ATHs Hit 8 times9 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.24%5.51%

Biggest Jump (1 Day) % +0.13+0.10

Biggest Drop (1 Day) % -0.05-0.04

Days Above Avg % 33.1%51.5%

Extreme Moves days 10 (2.9%)13 (3.8%)

Stability Score % 0.0%0.0%

Trend Strength % 50.1%52.5%

Recent Momentum (10-day) % -7.23%-27.75%

📊 Statistical Measures

Average Price 0.140.13

Median Price 0.130.13

Price Std Deviation 0.030.03

🚀 Returns & Growth

CAGR % -20.86%-72.08%

Annualized Return % -20.86%-72.08%

Total Return % -19.73%-69.84%

⚠️ Risk & Volatility

Daily Volatility % 7.69%8.58%

Annualized Volatility % 146.89%163.99%

Max Drawdown % -61.04%-86.07%

Sharpe Ratio 0.024-0.002

Sortino Ratio 0.031-0.002

Calmar Ratio -0.342-0.837

Ulcer Index 31.9748.67

📅 Daily Performance

Win Rate % 49.9%47.5%

Positive Days 171163

Negative Days 172180

Best Day % +95.03%+60.97%

Worst Day % -29.08%-28.35%

Avg Gain (Up Days) % +4.40%+5.55%

Avg Loss (Down Days) % -3.99%-5.06%

Profit Factor 1.090.99

🔥 Streaks & Patterns

Longest Win Streak days 77

Longest Loss Streak days 86

💹 Trading Metrics

Omega Ratio 1.0940.995

Expectancy % +0.19%-0.01%

Kelly Criterion % 1.07%0.00%

📅 Weekly Performance

Best Week % +73.25%+79.33%

Worst Week % -28.61%-37.51%

Weekly Win Rate % 48.1%38.5%

📆 Monthly Performance

Best Month % +84.19%+115.63%

Worst Month % -30.21%-46.17%

Monthly Win Rate % 46.2%46.2%

🔧 Technical Indicators

RSI (14-period) 37.5318.94

Price vs 50-Day MA % -18.07%-46.25%

Price vs 200-Day MA % -22.23%-64.41%

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 FIS (FIS):	0.254 (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
FIS: Kraken