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Update docs displaying how to get last available and trade-open candles.

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This commit is contained in:
Rokas Kupstys 2021-05-08 16:56:59 +03:00
parent 8d8c782bd0
commit 17b9e898d2
1 changed files with 12 additions and 11 deletions
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docs/strategy-advanced.md
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@ -265,12 +265,6 @@ class AwesomeStrategy(IStrategy):
Imagine you want to use `custom_stoploss()` to use a trailing indicator like e.g. "ATR" Imagine you want to use `custom_stoploss()` to use a trailing indicator like e.g. "ATR"
!!! Warning
Only use `dataframe` values up until and including `current_time` value. Reading past
`current_time` you will look into the future, which will produce incorrect backtesting results
and throw an exception in dry/live runs.
see [Common mistakes when developing strategies](strategy-customization.md#common-mistakes-when-developing-strategies) for more info.
!!! Note !!! Note
`dataframe['date']` contains the candle's open date. During dry/live runs `current_time` and `dataframe['date']` contains the candle's open date. During dry/live runs `current_time` and
`trade.open_date_utc` will not match the candle date precisely and using them directly will throw `trade.open_date_utc` will not match the candle date precisely and using them directly will throw
@ -290,7 +284,6 @@ class AwesomeStrategy(IStrategy):
def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime, def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
current_rate: float, current_profit: float, **kwargs) -> float: current_rate: float, current_profit: float, **kwargs) -> float:
# Default return value # Default return value
result = 1 result = 1
if trade: if trade:
@ -298,11 +291,19 @@ class AwesomeStrategy(IStrategy):
# be rounded to previous candle to be used as dataframe index. Rounding must also be # be rounded to previous candle to be used as dataframe index. Rounding must also be
# applied to `trade.open_date(_utc)` if it is used for `dataframe` indexing. # applied to `trade.open_date(_utc)` if it is used for `dataframe` indexing.
dataframe = self.dp.get_analyzed_dataframe(pair, self.timeframe) dataframe = self.dp.get_analyzed_dataframe(pair, self.timeframe)
current_time = timeframe_to_prev_date(self.timeframe, current_time) current_candle = dataframe.loc[-1].squeeze()
current_row = dataframe.loc[dataframe['date'] == current_time].squeeze() if 'atr' in current_candle:
if 'atr' in current_row:
# new stoploss relative to current_rate # new stoploss relative to current_rate
new_stoploss = (current_rate - current_row['atr']) / current_rate new_stoploss = (current_rate - current_candle['atr']) / current_rate
# Round trade date to it's candle time.
trade_date = timeframe_to_prev_date(trade.open_date_utc)
trade_candle = dataframe.loc[dataframe['date'] == trade_date]
# Just opened trades do not have their candle complete yet therefore trade_candle may be None
if trade_candle is not None:
trade_candle = trade_candle.squeeze()
trade_stoploss = (current_rate - trade_candle['atr']) / current_rate
new_stoploss = max(new_stoploss, trade_stoploss)
# turn into relative negative offset required by `custom_stoploss` return implementation # turn into relative negative offset required by `custom_stoploss` return implementation
result = new_stoploss - 1 result = new_stoploss - 1