diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py index 1ff737b90..4505ea52a 100644 --- a/freqtrade/data/btanalysis.py +++ b/freqtrade/data/btanalysis.py @@ -220,6 +220,8 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_time' max_drawdown_df['drawdown'] = max_drawdown_df['cumulative'] - max_drawdown_df['high_value'] idxmin = max_drawdown_df['drawdown'].idxmin() + 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 diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py index 9f23ecf8f..4eec20976 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -206,3 +206,7 @@ def test_calculate_max_drawdown2(): # 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') diff --git a/tests/test_plotting.py b/tests/test_plotting.py index a5c965429..0258b94d1 100644 --- a/tests/test_plotting.py +++ b/tests/test_plotting.py @@ -266,7 +266,7 @@ def test_generate_profit_graph(testdatadir): filename = testdatadir / "backtest-result_test.json" trades = load_backtest_data(filename) 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')] 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") 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) for pair in pairs: