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65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
# -*- coding: utf-8 -*-
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from .atr import atr
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from ..utils import get_drift, get_offset, verify_series
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def natr(high, low, close, length=None, mamode=None, drift=None, offset=None, **kwargs):
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"""Indicator: Normalized Average True Range (NATR)"""
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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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length = int(length) if length and length > 0 else 14
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mamode = mamode.lower() if mamode else 'ema'
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drift = get_drift(drift)
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offset = get_offset(offset)
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# Calculate Result
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natr = (100 / close) * atr(high=high, low=low, close=close, length=length, mamode=mamode, drift=drift, offset=offset, **kwargs)
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# Offset
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if offset != 0:
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natr = natr.shift(offset)
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# Handle fills
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if 'fillna' in kwargs:
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natr.fillna(kwargs['fillna'], inplace=True)
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if 'fill_method' in kwargs:
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natr.fillna(method=kwargs['fill_method'], inplace=True)
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# Name and Categorize it
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natr.name = f"NATR_{length}"
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natr.category = 'volatility'
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return natr
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natr.__doc__ = \
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"""Normalized Average True Range (NATR)
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Normalized Average True Range attempt to normalize the average
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true range.
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Sources:
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https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/normalized-average-true-range-natr/
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Calculation:
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Default Inputs:
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length=20
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ATR = Average True Range
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NATR = (100 / close) * ATR(high, low, close)
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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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length (int): The short period. Default: 20
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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
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""" |