update with new comments and new data for tc5
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Matthias
parent
b8f78cb187
commit
30a6e684a6
@ -21,7 +21,8 @@ class BTContainer(NamedTuple):
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roi: float
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trades: int
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profit_perc: float
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sl: float
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sl: bool
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remains: bool
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columns = ['date', 'open', 'high', 'low', 'close', 'volume', 'buy', 'sell']
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@ -39,9 +40,9 @@ data_profit = DataFrame([
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], columns=columns)
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tc_profit1 = BTContainer(data=data_profit, stop_loss=-0.01, roi=1, trades=1,
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profit_perc=0.10557, sl=False) # should be stoploss - drops 8%
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profit_perc=0.10557, sl=False, remains=False) # should be stoploss - drops 8%
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tc_profit2 = BTContainer(data=data_profit, stop_loss=-0.10, roi=1,
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trades=1, profit_perc=0.10557, sl=True)
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trades=1, profit_perc=0.10557, sl=True, remains=False)
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tc_loss0 = BTContainer(data=DataFrame([
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@ -56,31 +57,37 @@ tc_loss0 = BTContainer(data=DataFrame([
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[getdate('2018-07-08 22:00:00').datetime, 0.001000,
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0.001011, 0.00098618, 0.00091618, 12345, 0, 0]
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], columns=columns),
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stop_loss=-0.05, roi=1, trades=1, profit_perc=-0.08839, sl=True)
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stop_loss=-0.05, roi=1, trades=1, profit_perc=-0.08839, sl=True, remains=False)
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# Test 1 Minus 8% Close
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# Candle Data for test 1 – close at -8% (9200)
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# Test with Stop-loss at 1%
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# TC1: Stop-Loss Triggered 1% loss
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tc1 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9925, 9950, 12345, 0, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9200, 9200, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9960, 9955, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9955, 9975, 9955, 9990, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9990, 9990, 9200, 9200, 12345, 0, 0]
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[getdate('2018-06-10 12:00:00').datetime, 9990, 9990, 9990, 9900, 12345, 0, 0]
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], columns=columns),
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stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.07999, sl=True)
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# stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sl=True, remains=False) # should be
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stop_loss=-0.01, roi=1, trades=1, profit_perc=0.071, sl=False, remains=True) #
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# Test 2 Minus 4% Low, minus 1% close
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# Candle Data for test 2
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# Test with Stop-Loss at 3%
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# TC2: Stop-Loss Triggered 3% Loss
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tc2 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9925, 9950, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9600, 9925, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns), stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.00999, sl=False) #
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], columns=columns),
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# stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.03, sl=True, remains=False) #should be
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stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.00999, sl=False, remains=True) #
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# Test 3 Candle drops 4%, Recovers 1%.
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@ -88,19 +95,23 @@ tc2 = BTContainer(data=DataFrame([
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# Candle drops 20%
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# Candle Data for test 3
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# Test with Stop-Loss at 2%
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# TC3: Trade-A: Stop-Loss Triggered 2% Loss
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# Trade-B: Stop-Loss Triggered 2% Loss
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tc3 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10025, 9600, 9950, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 1, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 8000, 8000, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9950, 9900, 12345, 0, 0]
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], columns=columns), stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.19999, sl=True) #
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], columns=columns),
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# stop_loss=-0.02, roi=1, trades=2, profit_perc=-0.4, sl=True, remains=False) #should be
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stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.19999, sl=True, remains=False) #
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# Test 4 Minus 3% / recovery +15%
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# Candle Data for test 4 – Candle drops 3% Closed 15% up
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# Test with Stop-loss at 2% ROI 6%
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# TC4: Stop-Loss Triggered 2% Loss
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tc4 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 11500, 9700, 11500, 12345, 0, 0],
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@ -108,49 +119,55 @@ tc4 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns),
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stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.141, sl=True)
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# stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.02, sl=False, remains=False) #should be
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stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.141, sl=True, remains=False)
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# Test 5 / Drops 0.5% Closes +20%
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# Candle Data for test 5
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# Set stop-loss at 1% ROI 3%
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# TC5: ROI triggers 3% Gain
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tc5 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 12000, 9950, 12000, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9960, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10050, 9950, 9975, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 12000, 9950, 12000, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns),
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stop_loss=-0.01, roi=0.03, trades=1, profit_perc=-0.177, sl=True)
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# stop_loss=-0.01, roi=0.03, trades=1, profit_perc=0.03, sl=False, remains=False) #should be
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stop_loss=-0.01, roi=0.03, trades=1, profit_perc=0.197, sl=False, remains=False)
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# Test 6 / Drops 3% / Recovers 6% Positive / Closes 1% positve
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# Candle Data for test 6
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# Set stop-loss at 2% ROI at 5%
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# TC6: Stop-Loss triggers 2% Loss
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tc6 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10600, 9700, 10100, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns), stop_loss=-0.02, roi=0.05,
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trades=1, profit_perc=-0.025, sl=False)
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], columns=columns),
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# stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.02, sl=False, remains=False) #should be
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stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.025, sl=False, remains=True) #
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# Test 7 - 6% Positive / 1% Negative / Close 1% Positve
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# Candle Data for test 7
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# Set stop-loss at 2% ROI at 3%
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# TC7: ROI Triggers 3% Gain
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tc7 = BTContainer(data=DataFrame([
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[getdate('2018-06-10 08:00:00').datetime, 10000, 10050, 9950, 9975, 12345, 1, 0],
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[getdate('2018-06-10 09:00:00').datetime, 9975, 10600, 9900, 10100, 12345, 0, 0],
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[getdate('2018-06-10 10:00:00').datetime, 9950, 10000, 9900, 9925, 12345, 0, 0],
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[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
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[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
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], columns=columns), stop_loss=-0.02, roi=0.03,
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trades=1, profit_perc=-0.025, sl=False)
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], columns=columns),
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# stop_loss=-0.02, roi=0.03, trades=1, profit_perc=-0.03, sl=False, remains=False) #should be
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stop_loss=-0.02, roi=0.03, trades=1, profit_perc=-0.025, sl=False, remains=True) #
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TESTS = [
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# tc_profit1,
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# tc_profit2,
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tc_loss0,
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# tc_loss0,
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tc1,
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tc2,
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tc3,
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@ -195,5 +212,12 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
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if data.sl:
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assert log_has("Stop loss hit.", caplog.record_tuples)
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else:
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assert not log_has("Stop loss hit.", caplog.record_tuples)
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log_test = (f'Force_selling still open trade UNITTEST/BTC with '
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f'{results.iloc[-1].profit_percent} perc - {results.iloc[-1].profit_abs}')
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if data.remains:
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assert log_has(log_test,
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caplog.record_tuples)
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else:
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assert not log_has(log_test,
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caplog.record_tuples)
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