Minor documentation updates
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@ -43,8 +43,8 @@ By default, loop runs every few seconds (`internals.process_throttle_secs`) and
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* Verifies buy signal trying to enter new positions.
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* Determine buy-price based on `bid_strategy` configuration setting, or by using the `custom_entry_price()` callback.
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* Determine stake size by calling the `custom_stake_amount()` callback.
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* Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
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* In Margin and Futures mode, `leverage()` strategy callback is called to determine the desired leverage.
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* Before a buy order is placed, `confirm_trade_entry()` strategy callback is called.
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This loop will be repeated again and again until the bot is stopped.
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@ -60,6 +60,7 @@ This loop will be repeated again and again until the bot is stopped.
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* Confirm trade buy / sell (calls `confirm_trade_entry()` and `confirm_trade_exit()` if implemented in the strategy).
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* Call `custom_entry_price()` (if implemented in the strategy) to determine entry price (Prices are moved to be within the opening candle).
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* Determine stake size by calling the `custom_stake_amount()` callback.
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* In Margin and Futures mode, `leverage()` strategy callback is called to determine the desired leverage.
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* Check position adjustments for open trades if enabled and call `adjust_trade_position()` to determine if an additional order is requested.
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* Call `custom_stoploss()` and `custom_sell()` to find custom exit points.
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* For sells based on sell-signal and custom-sell: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle).
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@ -52,7 +52,7 @@ Please switch to the new [Parametrized Strategies](hyperopt.md) to benefit from
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As strategies now have to support multiple different signal types, some things had to change.
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Columns:
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Dataframe columns:
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* `buy` -> `enter_long`
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* `sell` -> `exit_long`
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@ -395,6 +395,8 @@ for more information.
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``` python
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def informative(timeframe: str, asset: str = '',
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fmt: Optional[Union[str, Callable[[KwArg(str)], str]]] = None,
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*,
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candle_type: Optional[CandleType] = None,
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ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
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"""
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A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
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@ -423,6 +425,7 @@ for more information.
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* {column} - name of dataframe column.
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* {timeframe} - timeframe of informative dataframe.
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:param ffill: ffill dataframe after merging informative pair.
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:param candle_type: '', mark, index, premiumIndex, or funding_rate
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"""
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```
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@ -510,7 +513,6 @@ for more information.
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will overwrite previously defined method and not produce any errors due to limitations of Python programming language. In such cases you will find that indicators
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created in earlier-defined methods are not available in the dataframe. Carefully review method names and make sure they are unique!
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## Additional data (DataProvider)
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The strategy provides access to the `DataProvider`. This allows you to get additional data to use in your strategy.
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