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Improve doc wording

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Matthias 2021-04-24 13:13:41 +02:00
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docs/hyperopt.md
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@ -198,8 +198,7 @@ There you have two different types of indicators: 1. `guards` and 2. `triggers`.
However, this guide will make this distinction to make it clear that signals should not be "sticking". However, this guide will make this distinction to make it clear that signals should not be "sticking".
Sticking signals are signals that are active for multiple candles. This can lead into buying a signal late (right before the signal disappears - which means that the chance of success is a lot lower than right at the beginning). Sticking signals are signals that are active for multiple candles. This can lead into buying a signal late (right before the signal disappears - which means that the chance of success is a lot lower than right at the beginning).
Hyper-optimization will, for each epoch round, pick one trigger and possibly Hyper-optimization will, for each epoch round, pick one trigger and possibly multiple guards.
multiple guards.
#### Sell optimization #### Sell optimization
@ -266,8 +265,6 @@ The last one we call `trigger` and use it to decide which buy trigger we want to
So let's write the buy strategy using these values: So let's write the buy strategy using these values:
```python ```python
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
conditions = [] conditions = []
# GUARDS AND TRENDS # GUARDS AND TRENDS
@ -327,6 +324,9 @@ There are four parameter types each suited for different purposes.
Assuming you have a simple strategy in mind - a EMA cross strategy (2 Moving averages crossing) - and you'd like to find the ideal parameters for this strategy. Assuming you have a simple strategy in mind - a EMA cross strategy (2 Moving averages crossing) - and you'd like to find the ideal parameters for this strategy.
``` python ``` python
from pandas import DataFrame
from functools import reduce
import talib.abstract as ta import talib.abstract as ta
from freqtrade.strategy import IStrategy from freqtrade.strategy import IStrategy
@ -334,7 +334,7 @@ from freqtrade.strategy import CategoricalParameter, DecimalParameter, IntParame
import freqtrade.vendor.qtpylib.indicators as qtpylib import freqtrade.vendor.qtpylib.indicators as qtpylib
class MyAwesomeStrategy(IStrategy): class MyAwesomeStrategy(IStrategy):
stoploss = 0.5 stoploss = -0.05
timeframe = '15m' timeframe = '15m'
# Define the parameter spaces # Define the parameter spaces
buy_ema_short = IntParameter(3, 50, default=5) buy_ema_short = IntParameter(3, 50, default=5)