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100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
# -*- coding: utf-8 -*-
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import numpy as np
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from pandas import DataFrame
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from pandas_ta.utils import get_offset, verify_series
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def ha(open, high, low, close, offset=None, **kwargs):
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# indicator : Heikin Ashi
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# Validate Arguments
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open = verify_series(open)
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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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offset = get_offset(offset)
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#calculate ha_close
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ha_close = 0.25 * (open + high + low + close)
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# Initialization of the ha_open array
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ha_open = np.zeros(shape=(len(close)))
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# ha_open of the first element
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ha_open[0] = 0.5 * (open[0] + close[0])
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#calculate ha_open. Based on previous ha_open & ha_close
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for i in range (1, len(close)):
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ha_open[i] = 0.5 * (ha_open[i-1] + ha_close[i-1])
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# calculation of ha_high & ha_low
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ha_high = np.maximum.reduce([high, ha_open, ha_close])
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ha_low = np.minimum.reduce([low, ha_open, ha_close])
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# Prepare DataFrame to return
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data = {'ha_open': ha_open, 'ha_high': ha_high, 'ha_low': ha_low, 'ha_close': ha_close}
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hadf = DataFrame(data)
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hadf.name = "Heikin-Ashi"
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hadf.category = 'trend'
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# Apply offset if needed
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if offset != 0:
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hadf = hadf.shift(offset)
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# Handle fills
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if 'fillna' in kwargs:
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hadf.fillna(kwargs['fillna'], inplace=True)
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if 'fill_method' in kwargs:
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hadf.fillna(method=kwargs['fill_method'], inplace=True)
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return hadf
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ha.__doc__ = \
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"""Heikin Ashi (HA)
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The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise.
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Heikin-Ashi charts, developed by Munehisa Homma in the 1700s,
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share some characteristics with standard candlestick charts but differ based on the values used to create each candle.
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Instead of using the open, high, low, and close like standard candlestick charts,
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the Heikin-Ashi technique uses a modified formula based on two-period averages.
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This gives the chart a smoother appearance, making it easier to spots trends and reversals,
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but also obscures gaps and some price data.
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Sources:
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https://www.investopedia.com/terms/h/heikinashi.asp
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Calculation:
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The Formula for the Heikin-Ashi technique is:
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Heikin-Ashi Close=(Open0+High0+Low0+Close0)/4
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Heikin-Ashi Open=(HA Open−1+HA Close−1)/2
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Heikin-Ashi High=Max (High0,HA Open0,HA Close0)
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Heikin-Ashi Low=Min (Low0,HA Open0,HA Close0)
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where:Open0 etc.=Values from the current period
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Open−1 etc.=Values from the prior period
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HA=Heikin-Ashi
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How to Calculate Heikin-Ashi
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Use one period to create the first Heikin-Ashi (HA) candle, using the formulas.
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For example use the high, low, open, and close to create the first HA close price.
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Use the open and close to create the first HA open.
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The high of the period will be the first HA high, and the low will be the first HA low.
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With the first HA calculated, it is now possible to continue computing the HA candles per the formulas.
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Args:
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open (pd.Series): Series of 'open's
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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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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.DataFrame: ha_open, ha_high,ha_low, ha_close columns.
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"""
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