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https://github.com/wassname/pandas-ta.git
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James Sawyer
69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
# -*- coding: utf-8 -*-
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from pandas_ta.overlap import ema, sma
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from pandas_ta.volatility import atr
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from pandas_ta.utils import get_offset, verify_series
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def pgo(high, low, close, length=None, offset=None, **kwargs):
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"""Indicator: Pretty Good Oscillator (PGO)"""
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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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offset = get_offset(offset)
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# Calculate Result
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pgo = close - sma(close, length)
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pgo /= ema(atr(high, low, close, length), length)
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# Offset
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if offset != 0:
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pgo = pgo.shift(offset)
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# Handle fills
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if "fillna" in kwargs:
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pgo.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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pgo.fillna(method=kwargs["fill_method"], inplace=True)
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# Name and Categorize it
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pgo.name = f"PGO_{length}"
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pgo.category = "momentum"
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return pgo
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pgo.__doc__ = """Pretty Good Oscillator (PGO)
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The Pretty Good Oscillator indicator was created by Mark Johnson to measure the distance of the current close from its N-day Simple Moving Average, expressed in terms of an average true range over a similar period. Johnson's approach was to
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use it as a breakout system for longer term trades. Long if greater than 3.0 and
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short if less than -3.0.
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Sources:
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https://library.tradingtechnologies.com/trade/chrt-ti-pretty-good-oscillator.html
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Calculation:
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Default Inputs:
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length=14
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ATR = Average True Range
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SMA = Simple Moving Average
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EMA = Exponential Moving Average
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PGO = (close - SMA(close, length)) / EMA(ATR(high, low, close, length), length)
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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): It's period. Default: 14
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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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