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Align example of ROI in the docs

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hroff-1902 2019-09-28 11:56:19 +03:00 committed by GitHub
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docs/hyperopt.md
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@ -375,23 +375,12 @@ Buy hyperspace params:
'rsi-enabled': True, 'rsi-enabled': True,
'trigger': 'bb_lower'} 'trigger': 'bb_lower'}
ROI table: ROI table:
{ 0: 0.10674752302642071, { 0: 0.10674,
21: 0.09158372701087236, 21: 0.09158,
78: 0.03634636907306948, 78: 0.03634,
118: 0} 118: 0}
``` ```
This would translate to the following ROI table:
``` python
minimal_roi = {
"118": 0,
"78": 0.0363,
"21": 0.0915,
"0": 0.106
}
```
If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the ticker_interval used. By default the values can vary in the following ranges (for some of the most used ticker intervals, values are rounded to 5 digits after the decimal point): If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the ticker_interval used. By default the values can vary in the following ranges (for some of the most used ticker intervals, values are rounded to 5 digits after the decimal point):
| # step | 1m | | 5m | | 1h | | 1d | | | # step | 1m | | 5m | | 1h | | 1d | |