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79 lines
2.2 KiB
Python
79 lines
2.2 KiB
Python
# -*- coding: utf-8 -*-
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from numpy import sqrt
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from pandas import Series
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from pandas_ta._typing import DictLike, Int
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from pandas_ta.overlap import sma
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from pandas_ta.utils import v_offset, v_pos_default, v_series
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def ui(
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close: Series, length: Int = None, scalar: Int = None,
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offset: Int = None, **kwargs: DictLike
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) -> Series:
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"""Ulcer Index (UI)
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The Ulcer Index by Peter Martin measures the downside volatility with
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the use of the Quadratic Mean, which has the effect of emphasising
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large drawdowns.
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Sources:
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https://library.tradingtechnologies.com/trade/chrt-ti-ulcer-index.html
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https://en.wikipedia.org/wiki/Ulcer_index
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http://www.tangotools.com/ui/ui.htm
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Args:
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high (pd.Series): Series of 'high's
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close (pd.Series): Series of 'close's
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length (int): The short period. Default: 14
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scalar (float): A positive float to scale the bands. Default: 100
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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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everget (value, optional): TradingView's Evergets SMA instead of SUM
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calculation. Default: False
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Returns:
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pd.Series: New feature
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"""
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# Validate
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length = v_pos_default(length, 14)
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scalar = v_pos_default(scalar, 100)
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close = v_series(close, 2 * length - 1)
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if close is None:
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return
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offset = v_offset(offset)
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# Calculate
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highest_close = close.rolling(length).max()
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downside = scalar * (close - highest_close)
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downside /= highest_close
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d2 = downside * downside
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everget = kwargs.pop("everget", False)
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if everget:
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# Everget uses SMA instead of SUM for calculation
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_ui = sma(d2, length)
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else:
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_ui = d2.rolling(length).sum()
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ui = sqrt(_ui / length)
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# Offset
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if offset != 0:
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ui = ui.shift(offset)
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# Fill
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if "fillna" in kwargs:
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ui.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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ui.fillna(method=kwargs["fill_method"], inplace=True)
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# Name and Category
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ui.name = f"UI{'' if not everget else 'e'}_{length}"
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ui.category = "volatility"
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return ui
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