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https://github.com/wassname/pandas-ta.git
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73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
# -*- coding: utf-8 -*-
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from numpy import log, seterr
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from pandas import DataFrame, Series
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from pandas_ta._typing import DictLike, Int
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from pandas_ta.utils import v_offset, v_series
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def drawdown(
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close: Series, offset: Int = None, **kwargs: DictLike
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) -> DataFrame:
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"""Drawdown (DD)
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Drawdown is a peak-to-trough decline during a specific period for an
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investment, trading account, or fund. It is usually quoted as the
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percentage between the peak and the subsequent trough.
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Sources:
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https://www.investopedia.com/terms/d/drawdown.asp
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Args:
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close (pd.Series): Series of 'close's.
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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.DataFrame: drawdown, drawdown percent, drawdown log columns
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"""
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# Validate
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close = v_series(close)
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offset = v_offset(offset)
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# Calculate
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max_close = close.cummax()
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dd = max_close - close
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dd_pct = 1 - (close / max_close)
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_np_err = seterr()
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seterr(divide="ignore", invalid="ignore")
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dd_log = log(max_close) - log(close)
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seterr(divide=_np_err["divide"], invalid=_np_err["invalid"])
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# Offset
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if offset != 0:
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dd = dd.shift(offset)
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dd_pct = dd_pct.shift(offset)
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dd_log = dd_log.shift(offset)
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# Fill
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if "fillna" in kwargs:
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dd.fillna(kwargs["fillna"], inplace=True)
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dd_pct.fillna(kwargs["fillna"], inplace=True)
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dd_log.fillna(kwargs["fillna"], inplace=True)
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if "fill_method" in kwargs:
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dd.fillna(method=kwargs["fill_method"], inplace=True)
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dd_pct.fillna(method=kwargs["fill_method"], inplace=True)
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dd_log.fillna(method=kwargs["fill_method"], inplace=True)
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# Name and Category
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dd.name = "DD"
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dd_pct.name = f"{dd.name}_PCT"
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dd_log.name = f"{dd.name}_LOG"
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dd.category = dd_pct.category = dd_log.category = "performance"
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data = {dd.name: dd, dd_pct.name: dd_pct, dd_log.name: dd_log}
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df = DataFrame(data)
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df.name = dd.name
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df.category = dd.category
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return df
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