From 3eda434fcf7d108a520f494b4ef62b68afceb657 Mon Sep 17 00:00:00 2001 From: Yazeed Al Oyoun Date: Fri, 31 Jan 2020 22:16:44 +0100 Subject: [PATCH] added daily sharpe ratio test and modified hyperopt_loss_sharpe_daily --- .../optimize/hyperopt_loss_sharpe_daily.py | 4 +-- tests/optimize/test_hyperopt.py | 26 ++++++++++++++++++- 2 files changed, 27 insertions(+), 3 deletions(-) diff --git a/freqtrade/optimize/hyperopt_loss_sharpe_daily.py b/freqtrade/optimize/hyperopt_loss_sharpe_daily.py index 7c2587e1b..7f751b419 100644 --- a/freqtrade/optimize/hyperopt_loss_sharpe_daily.py +++ b/freqtrade/optimize/hyperopt_loss_sharpe_daily.py @@ -1,5 +1,5 @@ """ -SharpeHyperOptLoss +SharpeHyperOptLossDaily This module defines the alternative HyperOptLoss class which can be used for Hyperoptimization. @@ -43,7 +43,7 @@ class SharpeHyperOptLossDaily(IHyperOptLoss): * 100.0 ) - if np.std(results.profit_percent) != 0.0: + if (np.std(sum_daily.profit_percent) != 0.): sharp_ratio = ( sum_daily["profit_percent"].mean() / sum_daily["profit_percent"].std() diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index 69d110649..b3356bd6d 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -42,7 +42,13 @@ def hyperopt_results(): 'profit_percent': [-0.1, 0.2, 0.3], 'profit_abs': [-0.2, 0.4, 0.6], 'trade_duration': [10, 30, 10], - 'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI] + 'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI], + 'close_time': + [ + datetime(2019, 1, 1, 9, 26, 3, 478039), + datetime(2019, 2, 1, 9, 26, 3, 478039), + datetime(2019, 3, 1, 9, 26, 3, 478039) + ] } ) @@ -336,6 +342,24 @@ def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> N assert under > correct +def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None: + results_over = hyperopt_results.copy() + results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2 + results_under = hyperopt_results.copy() + results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 + + default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'}) + hl = HyperOptLossResolver.load_hyperoptloss(default_conf) + correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results), + datetime(2019, 1, 1), datetime(2019, 5, 1)) + over = hl.hyperopt_loss_function(results_over, len(hyperopt_results), + datetime(2019, 1, 1), datetime(2019, 5, 1)) + under = hl.hyperopt_loss_function(results_under, len(hyperopt_results), + datetime(2019, 1, 1), datetime(2019, 5, 1)) + assert over < correct + assert under > correct + + def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None: results_over = hyperopt_results.copy() results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2