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# Volatility Indicators
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Measures of price volatility and range that help assess market conditions, potential breakout scenarios, and risk levels. These indicators quantify the magnitude of price movements regardless of direction.
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## Capabilities
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### Average True Range
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Measures market volatility by calculating the average of true ranges over a specified period, providing insight into price movement magnitude.
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```python { .api }
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def ATR(high, low, close, timeperiod=14):
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    """
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    Average True Range
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    Parameters:
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    - high: array-like, high prices
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    - low: array-like, low prices
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    - close: array-like, close prices
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    - timeperiod: int, number of periods (default: 14)
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    Returns:
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    numpy.ndarray: ATR values (absolute price units)
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    """
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```
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### Normalized Average True Range
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ATR normalized as a percentage of the closing price, allowing comparison across different price levels and securities.
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```python { .api }
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def NATR(high, low, close, timeperiod=14):
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    """
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    Normalized Average True Range
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    Parameters:
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    - high: array-like, high prices
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    - low: array-like, low prices
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    - close: array-like, close prices
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    - timeperiod: int, number of periods (default: 14)
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    Returns:
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    numpy.ndarray: NATR values (percentage format)
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    """
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```
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### True Range
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Single-period true range calculation representing the greatest of three price differences for each period.
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```python { .api }
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def TRANGE(high, low, close):
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    """
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    True Range
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    Parameters:
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    - high: array-like, high prices
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    - low: array-like, low prices
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    - close: array-like, close prices
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    Returns:
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    numpy.ndarray: True Range values for each period
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    """
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```
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### Acceleration Bands
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Volatility-based bands that use price acceleration to create dynamic support and resistance levels, expanding during volatile periods and contracting during quieter markets.
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```python { .api }
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def ACCBANDS(high, low, close, timeperiod=20):
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    """
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    Acceleration Bands
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    Volatility-based bands using price acceleration to create dynamic
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    support and resistance levels.
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    Parameters:
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    - high: array-like, high prices
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    - low: array-like, low prices  
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    - close: array-like, close prices
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    - timeperiod: int, number of periods (default: 20)
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    Returns:
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    tuple: (upper_band, middle_band, lower_band) - Three arrays representing
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           the acceleration bands
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    """
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```
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## Usage Examples
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```python
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import talib
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import numpy as np
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# Sample OHLC data
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high = np.array([102.5, 103.2, 101.8, 104.1, 103.7])
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low = np.array([100.1, 101.5, 99.8, 101.2, 102.1])
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close = np.array([101.8, 102.9, 100.5, 103.4, 102.8])
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# Calculate volatility indicators
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atr = talib.ATR(high, low, close, timeperiod=14)
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natr = talib.NATR(high, low, close, timeperiod=14)
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trange = talib.TRANGE(high, low, close)
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print("ATR:", atr[-1])
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print("NATR:", natr[-1], "%")
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print("Current True Range:", trange[-1])
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# ATR can be used for:
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# - Position sizing (risk per trade = account_risk / ATR)
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# - Stop loss placement (stop = entry ± (ATR * multiplier))
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# - Volatility breakout systems
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# - Market regime identification (high ATR = volatile, low ATR = quiet)
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```