Merge branch 'feat/short' into lev-exchange
This commit is contained in:
Sam Germain
commit
488d729574
@ -232,7 +232,9 @@ class Backtesting:
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pair_data.loc[:, 'buy_tag'] = None # cleanup if buy_tag is exist
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df_analyzed = self.strategy.advise_sell(
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self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair}).copy()
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self.strategy.advise_buy(pair_data, {'pair': pair}),
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{'pair': pair}
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).copy()
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# Trim startup period from analyzed dataframe
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df_analyzed = trim_dataframe(df_analyzed, self.timerange,
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startup_candles=self.required_startup)
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@ -193,18 +193,22 @@ class StrategyResolver(IResolver):
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# register temp path with the bot
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abs_paths.insert(0, temp.resolve())
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strategy = StrategyResolver._load_object(paths=abs_paths,
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strategy = StrategyResolver._load_object(
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paths=abs_paths,
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object_name=strategy_name,
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add_source=True,
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kwargs={'config': config},
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)
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if strategy:
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strategy._populate_fun_len = len(getfullargspec(strategy.populate_indicators).args)
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strategy._buy_fun_len = len(getfullargspec(strategy.populate_buy_trend).args)
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strategy._sell_fun_len = len(getfullargspec(strategy.populate_sell_trend).args)
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if any(x == 2 for x in [strategy._populate_fun_len,
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if any(x == 2 for x in [
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strategy._populate_fun_len,
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strategy._buy_fun_len,
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strategy._sell_fun_len]):
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strategy._sell_fun_len
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]):
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strategy.INTERFACE_VERSION = 1
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return strategy
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@ -135,7 +135,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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@abstractmethod
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Populate indicators that will be used in the Buy and Sell strategy
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Populate indicators that will be used in the Buy, Sell, Short, Exit_short strategy
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:param dataframe: DataFrame with data from the exchange
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:param metadata: Additional information, like the currently traded pair
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:return: a Dataframe with all mandatory indicators for the strategies
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@ -164,9 +164,9 @@ class IStrategy(ABC, HyperStrategyMixin):
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def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
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"""
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Check buy timeout function callback.
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This method can be used to override the buy-timeout.
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It is called whenever a limit buy order has been created,
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Check buy enter timeout function callback.
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This method can be used to override the enter-timeout.
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It is called whenever a limit buy/short order has been created,
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and is not yet fully filled.
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Configuration options in `unfilledtimeout` will be verified before this,
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so ensure to set these timeouts high enough.
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@ -176,16 +176,16 @@ class IStrategy(ABC, HyperStrategyMixin):
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:param trade: trade object.
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:param order: Order dictionary as returned from CCXT.
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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:return bool: When True is returned, then the buy-order is cancelled.
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:return bool: When True is returned, then the buy/short-order is cancelled.
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"""
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return False
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def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
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"""
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Check sell timeout function callback.
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This method can be used to override the sell-timeout.
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It is called whenever a limit sell order has been created,
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and is not yet fully filled.
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This method can be used to override the exit-timeout.
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It is called whenever a (long) limit sell order or (short) limit buy
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has been created, and is not yet fully filled.
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Configuration options in `unfilledtimeout` will be verified before this,
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so ensure to set these timeouts high enough.
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@ -194,7 +194,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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:param trade: trade object.
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:param order: Order dictionary as returned from CCXT.
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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:return bool: When True is returned, then the sell-order is cancelled.
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:return bool: When True is returned, then the (long)sell/(short)buy-order is cancelled.
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"""
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return False
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@ -210,7 +210,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
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time_in_force: str, current_time: datetime, **kwargs) -> bool:
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"""
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Called right before placing a buy order.
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Called right before placing a buy/short order.
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Timing for this function is critical, so avoid doing heavy computations or
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network requests in this method.
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@ -218,7 +218,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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When not implemented by a strategy, returns True (always confirming).
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:param pair: Pair that's about to be bought.
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:param pair: Pair that's about to be bought/shorted.
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:param order_type: Order type (as configured in order_types). usually limit or market.
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:param amount: Amount in target (quote) currency that's going to be traded.
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:param rate: Rate that's going to be used when using limit orders
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@ -234,7 +234,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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rate: float, time_in_force: str, sell_reason: str,
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current_time: datetime, **kwargs) -> bool:
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"""
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Called right before placing a regular sell order.
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Called right before placing a regular sell/exit_short order.
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Timing for this function is critical, so avoid doing heavy computations or
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network requests in this method.
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@ -242,18 +242,18 @@ class IStrategy(ABC, HyperStrategyMixin):
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When not implemented by a strategy, returns True (always confirming).
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:param pair: Pair that's about to be sold.
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:param pair: Pair for trade that's about to be exited.
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:param trade: trade object.
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:param order_type: Order type (as configured in order_types). usually limit or market.
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:param amount: Amount in quote currency.
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:param rate: Rate that's going to be used when using limit orders
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:param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
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:param sell_reason: Sell reason.
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:param sell_reason: Exit reason.
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Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
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'sell_signal', 'force_sell', 'emergency_sell']
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:param current_time: datetime object, containing the current datetime
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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:return bool: When True is returned, then the sell-order is placed on the exchange.
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:return bool: When True, then the sell-order/exit_short-order is placed on the exchange.
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False aborts the process
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"""
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return True
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@ -283,15 +283,15 @@ class IStrategy(ABC, HyperStrategyMixin):
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def custom_sell(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
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current_profit: float, **kwargs) -> Optional[Union[str, bool]]:
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"""
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Custom sell signal logic indicating that specified position should be sold. Returning a
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string or True from this method is equal to setting sell signal on a candle at specified
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time. This method is not called when sell signal is set.
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Custom exit signal logic indicating that specified position should be sold. Returning a
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string or True from this method is equal to setting exit signal on a candle at specified
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time. This method is not called when exit signal is set.
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This method should be overridden to create sell signals that depend on trade parameters. For
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example you could implement a sell relative to the candle when the trade was opened,
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This method should be overridden to create exit signals that depend on trade parameters. For
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example you could implement an exit relative to the candle when the trade was opened,
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or a custom 1:2 risk-reward ROI.
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Custom sell reason max length is 64. Exceeding characters will be removed.
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Custom exit reason max length is 64. Exceeding characters will be removed.
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:param pair: Pair that's currently analyzed
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:param trade: trade object.
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@ -299,7 +299,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
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:param current_profit: Current profit (as ratio), calculated based on current_rate.
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:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
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:return: To execute sell, return a string with custom sell reason or True. Otherwise return
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:return: To execute exit, return a string with custom sell reason or True. Otherwise return
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None or False.
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"""
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return None
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@ -371,7 +371,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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Checks if a pair is currently locked
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The 2nd, optional parameter ensures that locks are applied until the new candle arrives,
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and not stop at 14:00:00 - while the next candle arrives at 14:00:02 leaving a gap
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of 2 seconds for a buy to happen on an old signal.
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of 2 seconds for a buy/short to happen on an old signal.
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:param pair: "Pair to check"
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:param candle_date: Date of the last candle. Optional, defaults to current date
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:returns: locking state of the pair in question.
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@ -387,7 +387,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Parses the given candle (OHLCV) data and returns a populated DataFrame
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add several TA indicators and buy signal to it
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add several TA indicators and buy/short signal to it
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:param dataframe: Dataframe containing data from exchange
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:param metadata: Metadata dictionary with additional data (e.g. 'pair')
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:return: DataFrame of candle (OHLCV) data with indicator data and signals added
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@ -502,12 +502,14 @@ class IStrategy(ABC, HyperStrategyMixin):
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dataframe: DataFrame
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) -> Tuple[bool, bool, Optional[str]]:
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"""
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Calculates current signal based based on the buy / sell columns of the dataframe.
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Used by Bot to get the signal to buy or sell
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Calculates current signal based based on the buy/short or sell/exit_short
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columns of the dataframe.
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Used by Bot to get the signal to buy, sell, short, or exit_short
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:param pair: pair in format ANT/BTC
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:param timeframe: timeframe to use
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:param dataframe: Analyzed dataframe to get signal from.
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:return: (Buy, Sell) A bool-tuple indicating buy/sell signal
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:return: (Buy, Sell)/(Short, Exit_short) A bool-tuple indicating
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(buy/sell)/(short/exit_short) signal
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"""
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if not isinstance(dataframe, DataFrame) or dataframe.empty:
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logger.warning(f'Empty candle (OHLCV) data for pair {pair}')
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@ -528,27 +530,34 @@ class IStrategy(ABC, HyperStrategyMixin):
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)
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return False, False, None
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buy = latest[SignalType.BUY.value] == 1
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enter = latest[SignalType.BUY.value] == 1
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sell = False
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exit = False
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if SignalType.SELL.value in latest:
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sell = latest[SignalType.SELL.value] == 1
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exit = latest[SignalType.SELL.value] == 1
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buy_tag = latest.get(SignalTagType.BUY_TAG.value, None)
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logger.debug('trigger: %s (pair=%s) buy=%s sell=%s',
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latest['date'], pair, str(buy), str(sell))
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latest['date'], pair, str(enter), str(exit))
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timeframe_seconds = timeframe_to_seconds(timeframe)
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if self.ignore_expired_candle(latest_date=latest_date,
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if self.ignore_expired_candle(
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latest_date=latest_date,
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current_time=datetime.now(timezone.utc),
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timeframe_seconds=timeframe_seconds,
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buy=buy):
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return False, sell, buy_tag
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return buy, sell, buy_tag
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enter=enter
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):
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return False, exit, buy_tag
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return enter, exit, buy_tag
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def ignore_expired_candle(self, latest_date: datetime, current_time: datetime,
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timeframe_seconds: int, buy: bool):
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if self.ignore_buying_expired_candle_after and buy:
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def ignore_expired_candle(
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self,
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latest_date: datetime,
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current_time: datetime,
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timeframe_seconds: int,
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enter: bool
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):
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if self.ignore_buying_expired_candle_after and enter:
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time_delta = current_time - (latest_date + timedelta(seconds=timeframe_seconds))
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return time_delta.total_seconds() > self.ignore_buying_expired_candle_after
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else:
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@ -558,12 +567,12 @@ class IStrategy(ABC, HyperStrategyMixin):
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sell: bool, low: float = None, high: float = None,
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force_stoploss: float = 0) -> SellCheckTuple:
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"""
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This function evaluates if one of the conditions required to trigger a sell
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has been reached, which can either be a stop-loss, ROI or sell-signal.
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:param low: Only used during backtesting to simulate stoploss
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:param high: Only used during backtesting, to simulate ROI
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This function evaluates if one of the conditions required to trigger a sell/exit_short
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has been reached, which can either be a stop-loss, ROI or exit-signal.
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:param low: Only used during backtesting to simulate (long)stoploss/(short)ROI
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:param high: Only used during backtesting, to simulate (short)stoploss/(long)ROI
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:param force_stoploss: Externally provided stoploss
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:return: True if trade should be sold, False otherwise
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:return: True if trade should be exited, False otherwise
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"""
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current_rate = rate
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current_profit = trade.calc_profit_ratio(current_rate)
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@ -578,7 +587,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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current_rate = high or rate
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current_profit = trade.calc_profit_ratio(current_rate)
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# if buy signal and ignore_roi is set, we don't need to evaluate min_roi.
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# if enter signal and ignore_roi is set, we don't need to evaluate min_roi.
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roi_reached = (not (buy and self.ignore_roi_if_buy_signal)
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and self.min_roi_reached(trade=trade, current_profit=current_profit,
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current_time=date))
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@ -609,12 +618,12 @@ class IStrategy(ABC, HyperStrategyMixin):
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custom_reason = custom_reason[:CUSTOM_SELL_MAX_LENGTH]
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else:
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custom_reason = None
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# TODO: return here if sell-signal should be favored over ROI
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# TODO: return here if exit-signal should be favored over ROI
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# Start evaluations
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# Sequence:
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# ROI (if not stoploss)
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# Sell-signal
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# Exit-signal
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# Stoploss
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if roi_reached and stoplossflag.sell_type != SellType.STOP_LOSS:
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logger.debug(f"{trade.pair} - Required profit reached. sell_type=SellType.ROI")
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@ -632,7 +641,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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return stoplossflag
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# This one is noisy, commented out...
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# logger.debug(f"{trade.pair} - No sell signal.")
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# logger.debug(f"{trade.pair} - No exit signal.")
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return SellCheckTuple(sell_type=SellType.NONE)
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def stop_loss_reached(self, current_rate: float, trade: Trade,
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@ -641,7 +650,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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high: float = None) -> SellCheckTuple:
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"""
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Based on current profit of the trade and configured (trailing) stoploss,
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decides to sell or not
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decides to exit or not
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:param current_profit: current profit as ratio
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:param low: Low value of this candle, only set in backtesting
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:param high: High value of this candle, only set in backtesting
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@ -746,7 +755,7 @@ class IStrategy(ABC, HyperStrategyMixin):
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def advise_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Populate indicators that will be used in the Buy and Sell strategy
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Populate indicators that will be used in the Buy, Sell, short, exit_short strategy
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This method should not be overridden.
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:param dataframe: Dataframe with data from the exchange
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:param metadata: Additional information, like the currently traded pair
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@ -762,14 +771,15 @@ class IStrategy(ABC, HyperStrategyMixin):
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def advise_buy(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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"""
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Based on TA indicators, populates the buy signal for the given dataframe
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Based on TA indicators, populates the buy/short signal for the given dataframe
|
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This method should not be overridden.
|
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:param dataframe: DataFrame
|
||||
:param metadata: Additional information dictionary, with details like the
|
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currently traded pair
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:return: DataFrame with buy column
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"""
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logger.debug(f"Populating buy signals for pair {metadata.get('pair')}.")
|
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logger.debug(f"Populating enter signals for pair {metadata.get('pair')}.")
|
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|
||||
if self._buy_fun_len == 2:
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warnings.warn("deprecated - check out the Sample strategy to see "
|
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@ -780,14 +790,15 @@ class IStrategy(ABC, HyperStrategyMixin):
|
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|
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def advise_sell(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
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"""
|
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Based on TA indicators, populates the sell signal for the given dataframe
|
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Based on TA indicators, populates the sell/exit_short signal for the given dataframe
|
||||
This method should not be overridden.
|
||||
:param dataframe: DataFrame
|
||||
:param metadata: Additional information dictionary, with details like the
|
||||
currently traded pair
|
||||
:return: DataFrame with sell column
|
||||
"""
|
||||
logger.debug(f"Populating sell signals for pair {metadata.get('pair')}.")
|
||||
|
||||
logger.debug(f"Populating exit signals for pair {metadata.get('pair')}.")
|
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if self._sell_fun_len == 2:
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||||
warnings.warn("deprecated - check out the Sample strategy to see "
|
||||
"the current function headers!", DeprecationWarning)
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||||
|
||||
@ -72,7 +72,7 @@ def stoploss_from_open(open_relative_stop: float, current_profit: float) -> floa
|
||||
|
||||
:param open_relative_stop: Desired stop loss percentage relative to open price
|
||||
:param current_profit: The current profit percentage
|
||||
:return: Positive stop loss value relative to current price
|
||||
:return: Stop loss value relative to current price
|
||||
"""
|
||||
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# formula is undefined for current_profit -1, return maximum value
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||||
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@ -59,7 +59,7 @@ class SampleHyperOpt(IHyperOpt):
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Categorical([True, False], name='fastd-enabled'),
|
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Categorical([True, False], name='adx-enabled'),
|
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Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
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Categorical(['boll', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
]
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||||
|
||||
@staticmethod
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@ -71,37 +71,39 @@ class SampleHyperOpt(IHyperOpt):
|
||||
"""
|
||||
Buy strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
long_conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
if 'mfi-enabled' in params and params['mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
long_conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
if 'fastd-enabled' in params and params['fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
long_conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
if 'adx-enabled' in params and params['adx-enabled']:
|
||||
conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
long_conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
if 'rsi-enabled' in params and params['rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
long_conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'trigger' in params:
|
||||
if params['trigger'] == 'bb_lower':
|
||||
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'boll':
|
||||
long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'], dataframe['macdsignal']
|
||||
long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'],
|
||||
dataframe['macdsignal']
|
||||
))
|
||||
if params['trigger'] == 'sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'], dataframe['sar']
|
||||
long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'],
|
||||
dataframe['sar']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
long_conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
if long_conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
reduce(lambda x, y: x & y, long_conditions),
|
||||
'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
@ -122,9 +124,11 @@ class SampleHyperOpt(IHyperOpt):
|
||||
Categorical([True, False], name='sell-fastd-enabled'),
|
||||
Categorical([True, False], name='sell-adx-enabled'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
Categorical(['sell-boll',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
'sell-sar_reversal'],
|
||||
name='sell-trigger'
|
||||
)
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
@ -136,37 +140,39 @@ class SampleHyperOpt(IHyperOpt):
|
||||
"""
|
||||
Sell strategy Hyperopt will build and use.
|
||||
"""
|
||||
conditions = []
|
||||
exit_long_conditions = []
|
||||
|
||||
# GUARDS AND TRENDS
|
||||
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
|
||||
conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sell-bb_upper':
|
||||
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-boll':
|
||||
exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
exit_long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'],
|
||||
dataframe['macd']
|
||||
))
|
||||
if params['sell-trigger'] == 'sell-sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'], dataframe['close']
|
||||
exit_long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'],
|
||||
dataframe['close']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
exit_long_conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
if exit_long_conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
reduce(lambda x, y: x & y, exit_long_conditions),
|
||||
'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
@ -74,7 +74,7 @@ class AdvancedSampleHyperOpt(IHyperOpt):
|
||||
Categorical([True, False], name='fastd-enabled'),
|
||||
Categorical([True, False], name='adx-enabled'),
|
||||
Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
Categorical(['boll', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
@ -86,36 +86,36 @@ class AdvancedSampleHyperOpt(IHyperOpt):
|
||||
"""
|
||||
Buy strategy Hyperopt will build and use
|
||||
"""
|
||||
conditions = []
|
||||
long_conditions = []
|
||||
# GUARDS AND TRENDS
|
||||
if 'mfi-enabled' in params and params['mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
long_conditions.append(dataframe['mfi'] < params['mfi-value'])
|
||||
if 'fastd-enabled' in params and params['fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
long_conditions.append(dataframe['fastd'] < params['fastd-value'])
|
||||
if 'adx-enabled' in params and params['adx-enabled']:
|
||||
conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
long_conditions.append(dataframe['adx'] > params['adx-value'])
|
||||
if 'rsi-enabled' in params and params['rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
long_conditions.append(dataframe['rsi'] < params['rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'trigger' in params:
|
||||
if params['trigger'] == 'bb_lower':
|
||||
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'boll':
|
||||
long_conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'], dataframe['macdsignal']
|
||||
))
|
||||
if params['trigger'] == 'sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'], dataframe['sar']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
long_conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
if long_conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
reduce(lambda x, y: x & y, long_conditions),
|
||||
'buy'] = 1
|
||||
|
||||
return dataframe
|
||||
@ -136,9 +136,10 @@ class AdvancedSampleHyperOpt(IHyperOpt):
|
||||
Categorical([True, False], name='sell-fastd-enabled'),
|
||||
Categorical([True, False], name='sell-adx-enabled'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
Categorical(['sell-boll',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
'sell-sar_reversal'],
|
||||
name='sell-trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
@ -151,36 +152,38 @@ class AdvancedSampleHyperOpt(IHyperOpt):
|
||||
Sell strategy Hyperopt will build and use
|
||||
"""
|
||||
# print(params)
|
||||
conditions = []
|
||||
exit_long_conditions = []
|
||||
# GUARDS AND TRENDS
|
||||
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
|
||||
conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
exit_long_conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
|
||||
if 'sell-fastd-enabled' in params and params['sell-fastd-enabled']:
|
||||
conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
exit_long_conditions.append(dataframe['fastd'] > params['sell-fastd-value'])
|
||||
if 'sell-adx-enabled' in params and params['sell-adx-enabled']:
|
||||
conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
exit_long_conditions.append(dataframe['adx'] < params['sell-adx-value'])
|
||||
if 'sell-rsi-enabled' in params and params['sell-rsi-enabled']:
|
||||
conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
exit_long_conditions.append(dataframe['rsi'] > params['sell-rsi-value'])
|
||||
|
||||
# TRIGGERS
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sell-bb_upper':
|
||||
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-boll':
|
||||
exit_long_conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
exit_long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'],
|
||||
dataframe['macd']
|
||||
))
|
||||
if params['sell-trigger'] == 'sell-sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'], dataframe['close']
|
||||
exit_long_conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'],
|
||||
dataframe['close']
|
||||
))
|
||||
|
||||
# Check that volume is not 0
|
||||
conditions.append(dataframe['volume'] > 0)
|
||||
exit_long_conditions.append(dataframe['volume'] > 0)
|
||||
|
||||
if conditions:
|
||||
if exit_long_conditions:
|
||||
dataframe.loc[
|
||||
reduce(lambda x, y: x & y, conditions),
|
||||
reduce(lambda x, y: x & y, exit_long_conditions),
|
||||
'sell'] = 1
|
||||
|
||||
return dataframe
|
||||
|
||||
@ -68,15 +68,17 @@ class DefaultHyperOpt(IHyperOpt):
|
||||
|
||||
# TRIGGERS
|
||||
if 'trigger' in params:
|
||||
if params['trigger'] == 'bb_lower':
|
||||
if params['trigger'] == 'boll':
|
||||
conditions.append(dataframe['close'] < dataframe['bb_lowerband'])
|
||||
if params['trigger'] == 'macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macd'], dataframe['macdsignal']
|
||||
dataframe['macd'],
|
||||
dataframe['macdsignal']
|
||||
))
|
||||
if params['trigger'] == 'sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['close'], dataframe['sar']
|
||||
dataframe['close'],
|
||||
dataframe['sar']
|
||||
))
|
||||
|
||||
if conditions:
|
||||
@ -102,7 +104,7 @@ class DefaultHyperOpt(IHyperOpt):
|
||||
Categorical([True, False], name='fastd-enabled'),
|
||||
Categorical([True, False], name='adx-enabled'),
|
||||
Categorical([True, False], name='rsi-enabled'),
|
||||
Categorical(['bb_lower', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
Categorical(['boll', 'macd_cross_signal', 'sar_reversal'], name='trigger')
|
||||
]
|
||||
|
||||
@staticmethod
|
||||
@ -128,15 +130,17 @@ class DefaultHyperOpt(IHyperOpt):
|
||||
|
||||
# TRIGGERS
|
||||
if 'sell-trigger' in params:
|
||||
if params['sell-trigger'] == 'sell-bb_upper':
|
||||
if params['sell-trigger'] == 'sell-boll':
|
||||
conditions.append(dataframe['close'] > dataframe['bb_upperband'])
|
||||
if params['sell-trigger'] == 'sell-macd_cross_signal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['macdsignal'], dataframe['macd']
|
||||
dataframe['macdsignal'],
|
||||
dataframe['macd']
|
||||
))
|
||||
if params['sell-trigger'] == 'sell-sar_reversal':
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe['sar'], dataframe['close']
|
||||
dataframe['sar'],
|
||||
dataframe['close']
|
||||
))
|
||||
|
||||
if conditions:
|
||||
@ -162,9 +166,10 @@ class DefaultHyperOpt(IHyperOpt):
|
||||
Categorical([True, False], name='sell-fastd-enabled'),
|
||||
Categorical([True, False], name='sell-adx-enabled'),
|
||||
Categorical([True, False], name='sell-rsi-enabled'),
|
||||
Categorical(['sell-bb_upper',
|
||||
Categorical(['sell-boll',
|
||||
'sell-macd_cross_signal',
|
||||
'sell-sar_reversal'], name='sell-trigger')
|
||||
'sell-sar_reversal'],
|
||||
name='sell-trigger')
|
||||
]
|
||||
|
||||
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
@ -167,7 +167,7 @@ class HyperoptableStrategy(IStrategy):
|
||||
Based on TA indicators, populates the sell signal for the given dataframe
|
||||
:param dataframe: DataFrame
|
||||
:param metadata: Additional information, like the currently traded pair
|
||||
:return: DataFrame with buy column
|
||||
:return: DataFrame with sell column
|
||||
"""
|
||||
dataframe.loc[
|
||||
(
|
||||
|
||||
@ -156,17 +156,21 @@ def test_ignore_expired_candle(default_conf):
|
||||
# Add 1 candle length as the "latest date" defines candle open.
|
||||
current_time = latest_date + timedelta(seconds=80 + 300)
|
||||
|
||||
assert strategy.ignore_expired_candle(latest_date=latest_date,
|
||||
assert strategy.ignore_expired_candle(
|
||||
latest_date=latest_date,
|
||||
current_time=current_time,
|
||||
timeframe_seconds=300,
|
||||
buy=True) is True
|
||||
enter=True
|
||||
) is True
|
||||
|
||||
current_time = latest_date + timedelta(seconds=30 + 300)
|
||||
|
||||
assert not strategy.ignore_expired_candle(latest_date=latest_date,
|
||||
assert not strategy.ignore_expired_candle(
|
||||
latest_date=latest_date,
|
||||
current_time=current_time,
|
||||
timeframe_seconds=300,
|
||||
buy=True) is True
|
||||
enter=True
|
||||
) is True
|
||||
|
||||
|
||||
def test_assert_df_raise(mocker, caplog, ohlcv_history):
|
||||
|
||||
@ -382,13 +382,13 @@ def test_call_deprecated_function(result, monkeypatch, default_conf, caplog):
|
||||
assert isinstance(indicator_df, DataFrame)
|
||||
assert 'adx' in indicator_df.columns
|
||||
|
||||
buydf = strategy.advise_buy(result, metadata=metadata)
|
||||
assert isinstance(buydf, DataFrame)
|
||||
assert 'buy' in buydf.columns
|
||||
enterdf = strategy.advise_buy(result, metadata=metadata)
|
||||
assert isinstance(enterdf, DataFrame)
|
||||
assert 'buy' in enterdf.columns
|
||||
|
||||
selldf = strategy.advise_sell(result, metadata=metadata)
|
||||
assert isinstance(selldf, DataFrame)
|
||||
assert 'sell' in selldf
|
||||
exitdf = strategy.advise_sell(result, metadata=metadata)
|
||||
assert isinstance(exitdf, DataFrame)
|
||||
assert 'sell' in exitdf
|
||||
|
||||
assert log_has("DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'.",
|
||||
caplog)
|
||||
@ -409,10 +409,10 @@ def test_strategy_interface_versioning(result, monkeypatch, default_conf):
|
||||
assert isinstance(indicator_df, DataFrame)
|
||||
assert 'adx' in indicator_df.columns
|
||||
|
||||
buydf = strategy.advise_buy(result, metadata=metadata)
|
||||
assert isinstance(buydf, DataFrame)
|
||||
assert 'buy' in buydf.columns
|
||||
enterdf = strategy.advise_buy(result, metadata=metadata)
|
||||
assert isinstance(enterdf, DataFrame)
|
||||
assert 'buy' in enterdf.columns
|
||||
|
||||
selldf = strategy.advise_sell(result, metadata=metadata)
|
||||
assert isinstance(selldf, DataFrame)
|
||||
assert 'sell' in selldf
|
||||
exitdf = strategy.advise_sell(result, metadata=metadata)
|
||||
assert isinstance(exitdf, DataFrame)
|
||||
assert 'sell' in exitdf
|
||||
|
||||
Loading…
Reference in New Issue
Block a user