PYTH PYTH / USD Crypto vs IOTA IOTA / 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

Model:

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

Asset PYTH / USDIOTA / USD

📈 Performance Metrics

Start Price 0.420.19

End Price 0.080.12

Price Change % -79.85%-33.76%

Period High 0.530.49

Period Low 0.080.12

Price Range % 525.3%297.3%

🏆 All-Time Records

All-Time High 0.530.49

Days Since ATH 328 days327 days

Distance From ATH % -84.0%-74.8%

All-Time Low 0.080.12

Distance From ATL % +0.0%+0.0%

New ATHs Hit 9 times8 times

📌 Easy-to-Understand Stats

Avg Daily Change % 4.45%4.40%

Biggest Jump (1 Day) % +0.11+0.10

Biggest Drop (1 Day) % -0.09-0.08

Days Above Avg % 29.7%33.1%

Extreme Moves days 7 (2.0%)18 (5.2%)

Stability Score % 0.0%0.0%

Trend Strength % 50.7%48.7%

Recent Momentum (10-day) % -15.72%-7.04%

📊 Statistical Measures

Average Price 0.200.22

Median Price 0.150.20

Price Std Deviation 0.110.07

🚀 Returns & Growth

CAGR % -81.82%-35.49%

Annualized Return % -81.82%-35.49%

Total Return % -79.85%-33.76%

⚠️ Risk & Volatility

Daily Volatility % 8.00%5.79%

Annualized Volatility % 152.77%110.70%

Max Drawdown % -84.01%-74.83%

Sharpe Ratio -0.0250.008

Sortino Ratio -0.0310.008

Calmar Ratio -0.974-0.474

Ulcer Index 65.9056.16

📅 Daily Performance

Win Rate % 49.1%50.6%

Positive Days 168171

Negative Days 174167

Best Day % +99.34%+27.72%

Worst Day % -32.57%-24.16%

Avg Gain (Up Days) % +4.53%+4.18%

Avg Loss (Down Days) % -4.77%-4.18%

Profit Factor 0.921.02

🔥 Streaks & Patterns

Longest Win Streak days 78

Longest Loss Streak days 66

💹 Trading Metrics

Omega Ratio 0.9181.023

Expectancy % -0.20%+0.05%

Kelly Criterion % 0.00%0.27%

📅 Weekly Performance

Best Week % +65.86%+37.96%

Worst Week % -27.08%-23.58%

Weekly Win Rate % 51.9%48.1%

📆 Monthly Performance

Best Month % +65.32%+46.17%

Worst Month % -31.62%-27.14%

Monthly Win Rate % 38.5%38.5%

🔧 Technical Indicators

RSI (14-period) 46.0949.40

Price vs 50-Day MA % -38.75%-25.04%

Price vs 200-Day MA % -36.26%-33.41%

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 IOTA (IOTA):	0.842 (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
IOTA: Binance