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make drawdown function less restrictive

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This commit is contained in:
Matthias 2020-03-03 07:23:38 +01:00
parent 88e7cab5b9
commit 33a63562cb
1 changed files with 10 additions and 5 deletions
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15
freqtrade/data/btanalysis.py
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@ -190,21 +190,26 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
return df return df
def calculate_max_drawdown(trades: pd.DataFrame) -> Tuple[float, pd.Timestamp, pd.Timestamp]: def calculate_max_drawdown(trades: pd.DataFrame, date_col: str = 'close_time',
value_col: str = 'profitperc'
) -> Tuple[float, pd.Timestamp, pd.Timestamp]:
""" """
Calculate max drawdown and the corresponding close dates Calculate max drawdown and the corresponding close dates
:param trades: DataFrame containing trades (requires columns close_time and profitperc) :param trades: DataFrame containing trades (requires columns close_time and profitperc)
:param date_col: Column in DataFrame to use for dates (defaults to 'close_time')
:param value_col: Column in DataFrame to use for values (defaults to 'profitperc')
:return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time :return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time
:raise: ValueError if trade-dataframe was found empty. :raise: ValueError if trade-dataframe was found empty.
""" """
if len(trades) == 0: if len(trades) == 0:
raise ValueError("Trade dataframe empty.") raise ValueError("Trade dataframe empty.")
profit_results = trades.sort_values('close_time') profit_results = trades.sort_values(date_col)
max_drawdown_df = pd.DataFrame() max_drawdown_df = pd.DataFrame()
max_drawdown_df['cumulative'] = profit_results['profitperc'].cumsum() max_drawdown_df['cumulative'] = profit_results[value_col].cumsum()
max_drawdown_df['high_value'] = max_drawdown_df['cumulative'].cummax() max_drawdown_df['high_value'] = max_drawdown_df['cumulative'].cummax()
max_drawdown_df['drawdown'] = max_drawdown_df['cumulative'] - max_drawdown_df['high_value'] max_drawdown_df['drawdown'] = max_drawdown_df['cumulative'] - max_drawdown_df['high_value']
high_date = profit_results.loc[max_drawdown_df['high_value'].idxmax(), 'close_time']
low_date = profit_results.loc[max_drawdown_df['drawdown'].idxmin(), 'close_time'] high_date = profit_results.loc[max_drawdown_df['high_value'].idxmax(), date_col]
low_date = profit_results.loc[max_drawdown_df['drawdown'].idxmin(), date_col]
return abs(min(max_drawdown_df['drawdown'])), high_date, low_date return abs(min(max_drawdown_df['drawdown'])), high_date, low_date