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@ -303,8 +303,9 @@ Given the following result from hyperopt:
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```
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Best result:
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135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins.
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44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
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with values:
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Buy hyperspace params:
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{ 'adx-value': 44,
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'rsi-value': 29,
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'adx-enabled': False,
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@ -347,21 +348,14 @@ If you are optimizing ROI, you're result will look as follows and include a ROI
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```
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Best result:
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135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins.
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44/100: 135 trades. Avg profit 0.57%. Total profit 0.03871918 BTC (0.7722Σ%). Avg duration 180.4 mins. Objective: 1.94367
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with values:
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Buy hyperspace params:
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{ 'adx-value': 44,
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'rsi-value': 29,
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'adx-enabled': false,
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'adx-enabled': False,
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'rsi-enabled': True,
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'trigger': 'bb_lower',
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'roi_t1': 40,
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'roi_t2': 57,
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'roi_t3': 21,
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'roi_p1': 0.03634636907306948,
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'roi_p2': 0.055237357937802885,
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'roi_p3': 0.015163796015548354,
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'stoploss': -0.37996664668703606
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}
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'trigger': 'bb_lower'}
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ROI table:
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{ 0: 0.10674752302642071,
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21: 0.09158372701087236,
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@ -372,9 +366,9 @@ ROI table:
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This would translate to the following ROI table:
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``` python
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minimal_roi = {
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minimal_roi = {
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"118": 0,
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"78": 0.0363463,
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"78": 0.0363,
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"21": 0.0915,
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"0": 0.106
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}
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