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abstract-streaming.mdcycle-indicators.mdindex.mdmath-operations.mdmomentum-indicators.mdoverlap-studies.mdpattern-recognition.mdprice-transform.mdstatistical-functions.mdvolatility-indicators.mdvolume-indicators.md

volume-indicators.mddocs/

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# Volume Indicators

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Indicators that analyze the relationship between price movements and trading volume to confirm trends, identify potential reversals, and validate price action. Volume analysis helps determine the strength behind price movements.

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## Capabilities

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### Chaikin A/D Line

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Accumulation/Distribution Line that combines price and volume to show how much of a security is being accumulated or distributed.

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```python { .api }

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def AD(high, low, close, volume):

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"""

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Chaikin A/D Line

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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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- volume: array-like, volume data

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Returns:

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numpy.ndarray: Accumulation/Distribution Line values

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"""

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```

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### On Balance Volume

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Cumulative volume indicator that adds volume on up days and subtracts volume on down days to measure buying and selling pressure.

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```python { .api }

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def OBV(close, volume):

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"""

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On Balance Volume

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Parameters:

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- close: array-like, close prices

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- volume: array-like, volume data

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Returns:

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numpy.ndarray: OBV values (cumulative volume)

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"""

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```

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### Chaikin A/D Oscillator

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Oscillator version of the Accumulation/Distribution Line, showing the momentum of accumulation/distribution.

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```python { .api }

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def ADOSC(high, low, close, volume, fastperiod=3, slowperiod=10):

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"""

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Chaikin A/D Oscillator

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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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- volume: array-like, volume data

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- fastperiod: int, fast EMA period (default: 3)

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- slowperiod: int, slow EMA period (default: 10)

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Returns:

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numpy.ndarray: A/D Oscillator values

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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 OHLCV data

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high = np.array([10.5, 11.0, 11.2, 10.8, 11.5])

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low = np.array([10.0, 10.3, 10.5, 10.2, 10.8])

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close = np.array([10.3, 10.8, 10.9, 10.4, 11.2])

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volume = np.array([1000, 1200, 800, 1500, 900])

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# Calculate volume indicators

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ad_line = talib.AD(high, low, close, volume)

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obv = talib.OBV(close, volume)

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ad_osc = talib.ADOSC(high, low, close, volume, fastperiod=3, slowperiod=10)

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print("A/D Line:", ad_line[-1])

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print("OBV:", obv[-1])

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print("A/D Oscillator:", ad_osc[-1])

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```