mirror of
https://github.com/wassname/pandas-ta.git
synced 2026-06-27 16:10:07 +08:00
James Sawyer
71 lines
2.1 KiB
Python
71 lines
2.1 KiB
Python
# -*- coding: utf-8 -*-
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from ..utils import get_offset, verify_series
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def ao(high, low, fast=None, slow=None, offset=None, **kwargs):
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"""Indicator: Awesome Oscillator (AO)"""
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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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fast = int(fast) if fast and fast > 0 else 5
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slow = int(slow) if slow and slow > 0 else 34
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if slow < fast:
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fast, slow = slow, fast
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min_periods = (int(kwargs["min_periods"]) if "min_periods" in kwargs and
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kwargs["min_periods"] is not None else fast)
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offset = get_offset(offset)
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# Calculate Result
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median_price = 0.5 * (high + low)
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fast_sma = median_price.rolling(fast, min_periods=min_periods).mean()
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slow_sma = median_price.rolling(slow, min_periods=min_periods).mean()
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ao = fast_sma - slow_sma
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# Offset
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if offset != 0:
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ao = ao.shift(offset)
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# Handle fills
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if "fillna" in kwargs:
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ao.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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ao.fillna(method=kwargs["fill_method"], inplace=True)
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# Name and Categorize it
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ao.name = f"AO_{fast}_{slow}"
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ao.category = "momentum"
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return ao
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ao.__doc__ = """Awesome Oscillator (AO)
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The Awesome Oscillator is an indicator used to measure a security's momentum.
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AO is generally used to affirm trends or to anticipate possible reversals.
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Sources:
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https://www.tradingview.com/wiki/Awesome_Oscillator_(AO)
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https://www.ifcm.co.uk/ntx-indicators/awesome-oscillator
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Calculation:
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Default Inputs:
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fast=5, slow=34
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SMA = Simple Moving Average
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median = (high + low) / 2
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AO = SMA(median, fast) - SMA(median, slow)
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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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fast (int): The short period. Default: 5
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slow (int): The long period. Default: 34
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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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