Merge pull request #3137 from freqtrade/fix_maxdrawdown

[minor] Fix maxdrawdown
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hroff-1902 2020-04-14 16:03:25 +03:00 committed by GitHub
commit f2b1802666
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3 changed files with 33 additions and 6 deletions

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@ -220,13 +220,15 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_time'
""" """
if len(trades) == 0: if len(trades) == 0:
raise ValueError("Trade dataframe empty.") raise ValueError("Trade dataframe empty.")
profit_results = trades.sort_values(date_col) profit_results = trades.sort_values(date_col).reset_index(drop=True)
max_drawdown_df = pd.DataFrame() max_drawdown_df = pd.DataFrame()
max_drawdown_df['cumulative'] = profit_results[value_col].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(), date_col] idxmin = max_drawdown_df['drawdown'].idxmin()
low_date = profit_results.loc[max_drawdown_df['drawdown'].idxmin(), date_col] if idxmin == 0:
raise ValueError("No losing trade, therefore no drawdown.")
high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col]
low_date = profit_results.loc[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

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@ -191,3 +191,28 @@ def test_calculate_max_drawdown(testdatadir):
assert low == Timestamp('2018-01-30 04:45:00', tz='UTC') assert low == Timestamp('2018-01-30 04:45:00', tz='UTC')
with pytest.raises(ValueError, match='Trade dataframe empty.'): with pytest.raises(ValueError, match='Trade dataframe empty.'):
drawdown, h, low = calculate_max_drawdown(DataFrame()) drawdown, h, low = calculate_max_drawdown(DataFrame())
def test_calculate_max_drawdown2():
values = [0.011580, 0.010048, 0.011340, 0.012161, 0.010416, 0.010009, 0.020024,
-0.024662, -0.022350, 0.020496, -0.029859, -0.030511, 0.010041, 0.010872,
-0.025782, 0.010400, 0.012374, 0.012467, 0.114741, 0.010303, 0.010088,
-0.033961, 0.010680, 0.010886, -0.029274, 0.011178, 0.010693, 0.010711]
dates = [Arrow(2020, 1, 1).shift(days=i) for i in range(len(values))]
df = DataFrame(zip(values, dates), columns=['profit', 'open_time'])
# sort by profit and reset index
df = df.sort_values('profit').reset_index(drop=True)
df1 = df.copy()
drawdown, h, low = calculate_max_drawdown(df, date_col='open_time', value_col='profit')
# Ensure df has not been altered.
assert df.equals(df1)
assert isinstance(drawdown, float)
# High must be before low
assert h < low
assert drawdown == 0.091755
df = DataFrame(zip(values[:5], dates[:5]), columns=['profit', 'open_time'])
with pytest.raises(ValueError, match='No losing trade, therefore no drawdown.'):
calculate_max_drawdown(df, date_col='open_time', value_col='profit')

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@ -266,7 +266,7 @@ def test_generate_profit_graph(testdatadir):
filename = testdatadir / "backtest-result_test.json" filename = testdatadir / "backtest-result_test.json"
trades = load_backtest_data(filename) trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112") timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["TRX/BTC", "ADA/BTC"] pairs = ["TRX/BTC", "XLM/BTC"]
trades = trades[trades['close_time'] < pd.Timestamp('2018-01-12', tz='UTC')] trades = trades[trades['close_time'] < pd.Timestamp('2018-01-12', tz='UTC')]
data = history.load_data(datadir=testdatadir, data = history.load_data(datadir=testdatadir,
@ -292,7 +292,7 @@ def test_generate_profit_graph(testdatadir):
profit = find_trace_in_fig_data(figure.data, "Profit") profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scatter) assert isinstance(profit, go.Scatter)
profit = find_trace_in_fig_data(figure.data, "Max drawdown 0.00%") profit = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
assert isinstance(profit, go.Scatter) assert isinstance(profit, go.Scatter)
for pair in pairs: for pair in pairs: