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correct math used in examples and clarify some terminology regarding custom stoploss functions

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Brook Miles 2021-03-14 22:02:53 +09:00
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@ -71,12 +71,13 @@ See `custom_stoploss` examples below on how to access the saved dataframe column
## Custom stoploss
A stoploss can only ever move upwards - so if you set it to an absolute profit of 2%, you can never move it below this price.
Also, the traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss.
The stoploss price can only ever move upwards - if the stoploss value returned from `custom_stoploss` would result in a lower stoploss price than was previously set, it will be ignored. The traditional `stoploss` value serves as an absolute lower level and will be instated as the initial stoploss.
The usage of the custom stoploss method must be enabled by setting `use_custom_stoploss=True` on the strategy object.
The method must return a stoploss value (float / number) with a relative ratio below the current price.
E.g. `current_profit = 0.05` (5% profit) - stoploss returns `0.02` - then you "locked in" a profit of 3% (`0.05 - 0.02 = 0.03`).
The method must return a stoploss value (float / number) as a percentage of the current price.
E.g. If the `current_rate` is 200 USD, then returning `0.02` will set the stoploss price 2% lower, at 196 USD.
The absolute value of the return value is used (the sign is ignored), so returning `0.05` or `-0.05` have the same result, a stoploss 5% below the current price.
To simulate a regular trailing stoploss of 4% (trailing 4% behind the maximum reached price) you would use the following very simple method:
@ -177,16 +178,33 @@ class AwesomeStrategy(IStrategy):
return -0.15
```
#### Calculating stoploss relative to open price
Stoploss values returned from `custom_stoploss` always specify a percentage relative to `current_rate`. In order to set a stoploss relative to the *open* price, we need to use `current_profit` to calculate what percentage relative to the `current_rate` will give you the same result as if the percentage was specified from the open price.
This can be calculated as:
``` python
def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float:
return 1-((1+open_relative_stop)/(1+current_profit))
```
For example, say our open price was $100, and `current_price` is $121 (`current_profit` will be `0.21`). If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, 0.21)` which will return `0.1157024793`. 11.57% below $121 is $107, which is the same as 7% above $100.
#### Trailing stoploss with positive offset
Use the initial stoploss until the profit is above 4%, then use a trailing stoploss of 50% of the current profit with a minimum of 2.5% and a maximum of 5%.
Please note that the stoploss can only increase, values lower than the current stoploss are ignored.
``` python
from datetime import datetime, timedelta
from freqtrade.persistence import Trade
def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float:
return 1-((1+open_relative_stop)/(1+current_profit))
class AwesomeStrategy(IStrategy):
# ... populate_* methods
@ -197,28 +215,32 @@ class AwesomeStrategy(IStrategy):
current_rate: float, current_profit: float, **kwargs) -> float:
if current_profit < 0.04:
return -1 # return a value bigger than the inital stoploss to keep using the inital stoploss
return 1 # return a value bigger than the inital stoploss to keep using the inital stoploss
# After reaching the desired offset, allow the stoploss to trail by half the profit
desired_stoploss = current_profit / 2
# Use a minimum of 2.5% and a maximum of 5%
return max(min(desired_stoploss, 0.05), 0.025)
desired_stop_from_open = max(min(current_profit / 2, 0.05), 0.025)
return stoploss_from_open(desired_stop_from_open, current_profit)
```
#### Absolute stoploss
#### Stepped stoploss
The below example sets absolute profit levels based on the current profit.
Instead of continuously trailing behind the current price, this example sets fixed stoploss price levels based on the current profit.
* Use the regular stoploss until 20% profit is reached
* Once profit is > 40%, stoploss will be at 25%, locking in at least 25% of the profit.
* Once profit is > 25% - stoploss will be 15%.
* Once profit is > 20% - stoploss will be set to 7%.
* Once profit is > 20% - set stoploss to 7% above open price.
* Once profit is > 25% - set stoploss to 15% above open price.
* Once profit is > 40% - set stoploss to 25% above open price.
``` python
from datetime import datetime
from freqtrade.persistence import Trade
def stoploss_from_open(open_relative_stop: float, current_profit: float) -> float:
return 1-((1+open_relative_stop)/(1+current_profit))
class AwesomeStrategy(IStrategy):
# ... populate_* methods
@ -228,13 +250,15 @@ class AwesomeStrategy(IStrategy):
def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
current_rate: float, current_profit: float, **kwargs) -> float:
# Calculate as `-desired_stop_from_open + current_profit` to get the distance between current_profit and initial price
# evaluate highest to lowest, so that highest possible stop is used
if current_profit > 0.40:
return (-0.25 + current_profit)
if current_profit > 0.25:
return (-0.15 + current_profit)
if current_profit > 0.20:
return (-0.07 + current_profit)
return stoploss_from_open(0.25, current_profit)
elif current_profit > 0.25:
return stoploss_from_open(0.15, current_profit)
elif current_profit > 0.20:
return stoploss_from_open(0.07, current_profit)
# return maximum stoploss value, keeping current stoploss price unchanged
return 1
```
#### Custom stoploss using an indicator from dataframe example