IntermediateOptions, Derivatives & FinancePython
Run this module
Volatility Calculator¶
Calculate various volatility metrics for financial instruments.
Features¶
- Historical Volatility (close-to-close)
- Parkinson Volatility (high-low estimator)
- Garman-Klass Volatility (OHLC estimator)
- EWMA Volatility (RiskMetrics)
- Realized Volatility (high-frequency)
- Volatility Cone Analysis
Usage¶
from volatility_calculator import historical_volatility, volatility_cone
prices = [100, 102, 101, 103, 105, 104, 106]
vol = historical_volatility(prices, window=5)
print(f"Volatility: {vol:.2%}")
cone = volatility_cone(prices)
Methods¶
Historical Volatility¶
Standard deviation of log returns, annualized to 252 trading days.
Parkinson Volatility¶
Uses high-low range, more efficient than close-to-close.
Garman-Klass Volatility¶
Most efficient OHLC estimator, accounts for opening jumps.
EWMA Volatility¶
Exponentially weighted moving average, gives more weight to recent data.
Volatility Cone¶
Shows volatility distribution across different time horizons.
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