mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
James Sawyer
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
# -*- coding: utf-8 -*-
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from .hlc3 import hlc3
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from ..utils import get_offset, is_datetime_ordered, verify_series
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def vwap(high, low, close, volume, offset=None, **kwargs):
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"""Indicator: Volume Weighted Average Price (VWAP)"""
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# Validate Arguments
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high = verify_series(high)
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low = verify_series(low)
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close = verify_series(close)
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volume = verify_series(volume)
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offset = get_offset(offset)
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if not is_datetime_ordered(volume):
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print(
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f"[!] VWAP volume series is not datetime ordered. Results may not be as expected."
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)
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# Calculate Result
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tp = hlc3(high=high, low=low, close=close)
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vwap = (tp * volume).cumsum() / volume.cumsum()
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# Offset
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if offset != 0:
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vwap = vwap.shift(offset)
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# Name & Category
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vwap.name = "VWAP"
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vwap.category = "overlap"
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return vwap
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vwap.__doc__ = """Volume Weighted Average Price (VWAP)
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The Volume Weighted Average Price that measures the average typical price
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by volume. It is typically used with intraday charts to identify general
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direction.
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Sources:
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https://www.tradingview.com/wiki/Volume_Weighted_Average_Price_(VWAP)
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https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/volume-weighted-average-price-vwap/
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https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:vwap_intraday
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Calculation:
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tp = typical_price = hlc3(high, low, close)
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tpv = tp * volume
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VWAP = tpv.cumsum() / volume.cumsum()
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Args:
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high (pd.Series): Series of 'high's
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low (pd.Series): Series of 'low's
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close (pd.Series): Series of 'close's
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volume (pd.Series): Series of 'volume's
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offset (int): How many periods to offset the result. Default: 0
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Kwargs:
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fillna (value, optional): pd.DataFrame.fillna(value)
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fill_method (value, optional): Type of fill method
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Returns:
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pd.Series: New feature generated.
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"""
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