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Merge pull request #4750 from rokups/rk/custom_sell

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Add IStrategy.custom_sell method which allows per-trade sell signal evaluation
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Matthias 2021-04-29 06:50:56 +02:00 committed by GitHub
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11 changed files with 249 additions and 129 deletions
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107
docs/strategy-advanced.md
View File

@ -42,32 +42,38 @@ class AwesomeStrategy(IStrategy):
***
### Storing custom information using DatetimeIndex from `dataframe`
## Custom sell signal
Imagine you need to store an indicator like `ATR` or `RSI` into `custom_info`. To use this in a meaningful way, you will not only need the raw data of the indicator, but probably also need to keep the right timestamps.
It is possible to define custom sell signals. This is very useful when we need to customize sell conditions for each individual trade, or if you need the trade profit to take the sell decision.
An example of how we can use different indicators depending on the current profit and also sell trades that were open longer than 1 day:
``` python
import talib.abstract as ta
class AwesomeStrategy(IStrategy):
# Create custom dictionary
custom_info = {}
from freqtrade.strategy import IStrategy, timeframe_to_prev_date
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# using "ATR" here as example
dataframe['atr'] = ta.ATR(dataframe)
if self.dp.runmode.value in ('backtest', 'hyperopt'):
# add indicator mapped to correct DatetimeIndex to custom_info
self.custom_info[metadata['pair']] = dataframe[['date', 'atr']].set_index('date')
return dataframe
class AwesomeStrategy(IStrategy):
def custom_sell(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
current_profit: float, dataframe: DataFrame, **kwargs):
trade_open_date = timeframe_to_prev_date(self.timeframe, trade.open_date_utc)
trade_row = dataframe.loc[dataframe['date'] == trade_open_date].squeeze()
# Sell when price falls below value in stoploss column of taken buy signal.
# above 20% profit, sell when rsi < 80
if current_profit > 0.2:
if trade_row['rsi'] < 80:
return 'rsi_below_80'
# Between 2% and 10%, sell if EMA-long above EMA-short
if 0.02 < current_profit < 0.1:
if trade_row['emalong'] > trade_row['emashort']:
return 'ema_long_below_80'
# Sell any positions at a loss if they are held for more than two days.
if current_profit < 0.0 and (current_time - trade.open_date_utc).days >= 1:
return 'unclog'
```
!!! Warning
The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
!!! Note
If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
See `custom_stoploss` examples below on how to access the saved dataframe columns
See [Custom stoploss using an indicator from dataframe example](#custom-stoploss-using-an-indicator-from-dataframe-example) for explanation on how to use `dataframe` parameter.
## Custom stoploss
@ -93,7 +99,8 @@ class AwesomeStrategy(IStrategy):
use_custom_stoploss = True
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, dataframe: DataFrame,
**kwargs) -> float:
"""
Custom stoploss logic, returning the new distance relative to current_rate (as ratio).
e.g. returning -0.05 would create a stoploss 5% below current_rate.
@ -143,7 +150,8 @@ class AwesomeStrategy(IStrategy):
use_custom_stoploss = True
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, dataframe: DataFrame,
**kwargs) -> float:
# Make sure you have the longest interval first - these conditions are evaluated from top to bottom.
if current_time - timedelta(minutes=120) > trade.open_date_utc:
@ -169,7 +177,8 @@ class AwesomeStrategy(IStrategy):
use_custom_stoploss = True
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, dataframe: DataFrame,
**kwargs) -> float:
if pair in ('ETH/BTC', 'XRP/BTC'):
return -0.10
@ -195,7 +204,8 @@ class AwesomeStrategy(IStrategy):
use_custom_stoploss = True
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, dataframe: DataFrame,
**kwargs) -> float:
if current_profit < 0.04:
return -1 # return a value bigger than the inital stoploss to keep using the inital stoploss
@ -222,7 +232,6 @@ Instead of continuously trailing behind the current price, this example sets fix
* 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
@ -235,7 +244,8 @@ class AwesomeStrategy(IStrategy):
use_custom_stoploss = True
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, dataframe: DataFrame,
**kwargs) -> float:
# evaluate highest to lowest, so that highest possible stop is used
if current_profit > 0.40:
@ -248,18 +258,25 @@ class AwesomeStrategy(IStrategy):
# return maximum stoploss value, keeping current stoploss price unchanged
return 1
```
#### Custom stoploss using an indicator from dataframe example
Imagine you want to use `custom_stoploss()` to use a trailing indicator like e.g. "ATR"
See: "Storing custom information using DatetimeIndex from `dataframe`" example above) on how to store the indicator into `custom_info`
!!! Warning
only use .iat[-1] in live mode, not in backtesting/hyperopt
otherwise you will look into the future
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
`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
an error. Use `date = timeframe_to_prev_date(self.timeframe, date)` to round a date to the candle's open date
before using it to access `dataframe`.
``` python
from freqtrade.exchange import timeframe_to_prev_date
from freqtrade.persistence import Trade
from freqtrade.state import RunMode
@ -270,28 +287,20 @@ class AwesomeStrategy(IStrategy):
use_custom_stoploss = True
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, dataframe: DataFrame,
**kwargs) -> float:
# Default return value
result = 1
if self.custom_info and pair in self.custom_info and trade:
# using current_time directly (like below) will only work in backtesting.
# so check "runmode" to make sure that it's only used in backtesting/hyperopt
if self.dp and self.dp.runmode.value in ('backtest', 'hyperopt'):
relative_sl = self.custom_info[pair].loc[current_time]['atr']
# in live / dry-run, it'll be really the current time
else:
# but we can just use the last entry from an already analyzed dataframe instead
dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=pair,
timeframe=self.timeframe)
# WARNING
# only use .iat[-1] in live mode, not in backtesting/hyperopt
# otherwise you will look into the future
# see: https://www.freqtrade.io/en/latest/strategy-customization/#common-mistakes-when-developing-strategies
relative_sl = dataframe['atr'].iat[-1]
if (relative_sl is not None):
if trade:
# Using current_time directly would only work in backtesting. Live/dry runs need time to
# 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.
current_time = timeframe_to_prev_date(self.timeframe, current_time)
current_row = dataframe.loc[dataframe['date'] == current_time].squeeze()
if 'atr' in current_row:
# new stoploss relative to current_rate
new_stoploss = (current_rate-relative_sl)/current_rate
new_stoploss = (current_rate - current_row['atr']) / current_rate
# turn into relative negative offset required by `custom_stoploss` return implementation
result = new_stoploss - 1

5
docs/strategy-customization.md
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@ -631,9 +631,10 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
use_custom_stoploss = True
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, dataframe: DataFrame,
**kwargs) -> float:
# once the profit has risin above 10%, keep the stoploss at 7% above the open price
# once the profit has risen above 10%, keep the stoploss at 7% above the open price
if current_profit > 0.10:
return stoploss_from_open(0.07, current_profit)

34
freqtrade/freqtradebot.py
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@ -11,6 +11,7 @@ from typing import Any, Dict, List, Optional
import arrow
from cachetools import TTLCache
from pandas import DataFrame
from freqtrade import __version__, constants
from freqtrade.configuration import validate_config_consistency
@ -28,7 +29,7 @@ from freqtrade.plugins.protectionmanager import ProtectionManager
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.rpc import RPCManager, RPCMessageType
from freqtrade.state import State
from freqtrade.strategy.interface import IStrategy, SellType
from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.wallets import Wallets
@ -783,10 +784,10 @@ class FreqtradeBot(LoggingMixin):
config_ask_strategy = self.config.get('ask_strategy', {})
if (config_ask_strategy.get('use_sell_signal', True) or
config_ask_strategy.get('ignore_roi_if_buy_signal', False)):
analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(trade.pair,
self.strategy.timeframe)
if (config_ask_strategy.get('use_sell_signal', True) or
config_ask_strategy.get('ignore_roi_if_buy_signal', False)):
(buy, sell) = self.strategy.get_signal(trade.pair, self.strategy.timeframe, analyzed_df)
@ -813,13 +814,13 @@ class FreqtradeBot(LoggingMixin):
# resulting in outdated RPC messages
self._sell_rate_cache[trade.pair] = sell_rate
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
if self._check_and_execute_sell(analyzed_df, trade, sell_rate, buy, sell):
return True
else:
logger.debug('checking sell')
sell_rate = self.get_sell_rate(trade.pair, True)
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
if self._check_and_execute_sell(analyzed_df, trade, sell_rate, buy, sell):
return True
logger.debug('Found no sell signal for %s.', trade)
@ -850,7 +851,8 @@ class FreqtradeBot(LoggingMixin):
trade.stoploss_order_id = None
logger.error(f'Unable to place a stoploss order on exchange. {e}')
logger.warning('Selling the trade forcefully')
self.execute_sell(trade, trade.stop_loss, sell_reason=SellType.EMERGENCY_SELL)
self.execute_sell(trade, trade.stop_loss, sell_reason=SellCheckTuple(
sell_type=SellType.EMERGENCY_SELL))
except ExchangeError:
trade.stoploss_order_id = None
@ -949,19 +951,19 @@ class FreqtradeBot(LoggingMixin):
logger.warning(f"Could not create trailing stoploss order "
f"for pair {trade.pair}.")
def _check_and_execute_sell(self, trade: Trade, sell_rate: float,
def _check_and_execute_sell(self, dataframe: DataFrame, trade: Trade, sell_rate: float,
buy: bool, sell: bool) -> bool:
"""
Check and execute sell
"""
should_sell = self.strategy.should_sell(
trade, sell_rate, datetime.now(timezone.utc), buy, sell,
dataframe, trade, sell_rate, datetime.now(timezone.utc), buy, sell,
force_stoploss=self.edge.stoploss(trade.pair) if self.edge else 0
)
if should_sell.sell_flag:
logger.info(f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}')
self.execute_sell(trade, sell_rate, should_sell.sell_type)
self.execute_sell(trade, sell_rate, should_sell)
return True
return False
@ -1150,16 +1152,16 @@ class FreqtradeBot(LoggingMixin):
raise DependencyException(
f"Not enough amount to sell. Trade-amount: {amount}, Wallet: {wallet_amount}")
def execute_sell(self, trade: Trade, limit: float, sell_reason: SellType) -> bool:
def execute_sell(self, trade: Trade, limit: float, sell_reason: SellCheckTuple) -> bool:
"""
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param limit: limit rate for the sell order
:param sellreason: Reason the sell was triggered
:param sell_reason: Reason the sell was triggered
:return: True if it succeeds (supported) False (not supported)
"""
sell_type = 'sell'
if sell_reason in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
if sell_reason.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
sell_type = 'stoploss'
# if stoploss is on exchange and we are on dry_run mode,
@ -1176,10 +1178,10 @@ class FreqtradeBot(LoggingMixin):
logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
order_type = self.strategy.order_types[sell_type]
if sell_reason == SellType.EMERGENCY_SELL:
if sell_reason.sell_type == SellType.EMERGENCY_SELL:
# Emergency sells (default to market!)
order_type = self.strategy.order_types.get("emergencysell", "market")
if sell_reason == SellType.FORCE_SELL:
if sell_reason.sell_type == SellType.FORCE_SELL:
# Force sells (default to the sell_type defined in the strategy,
# but we allow this value to be changed)
order_type = self.strategy.order_types.get("forcesell", order_type)
@ -1190,7 +1192,7 @@ class FreqtradeBot(LoggingMixin):
if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
pair=trade.pair, trade=trade, order_type=order_type, amount=amount, rate=limit,
time_in_force=time_in_force,
sell_reason=sell_reason.value):
sell_reason=sell_reason.sell_reason):
logger.info(f"User requested abortion of selling {trade.pair}")
return False
@ -1213,7 +1215,7 @@ class FreqtradeBot(LoggingMixin):
trade.open_order_id = order['id']
trade.sell_order_status = ''
trade.close_rate_requested = limit
trade.sell_reason = sell_reason.value
trade.sell_reason = sell_reason.sell_reason
# In case of market sell orders the order can be closed immediately
if order.get('status', 'unknown') == 'closed':
self.update_trade_state(trade, trade.open_order_id, order)

20
freqtrade/optimize/backtesting.py
View File

@ -247,15 +247,17 @@ class Backtesting:
else:
return sell_row[OPEN_IDX]
def _get_sell_trade_entry(self, trade: LocalTrade, sell_row: Tuple) -> Optional[LocalTrade]:
def _get_sell_trade_entry(self, dataframe: DataFrame, trade: LocalTrade,
sell_row: Tuple) -> Optional[LocalTrade]:
sell = self.strategy.should_sell(trade, sell_row[OPEN_IDX], # type: ignore
sell_row[DATE_IDX], sell_row[BUY_IDX], sell_row[SELL_IDX],
sell = self.strategy.should_sell(dataframe, trade, sell_row[OPEN_IDX], # type: ignore
sell_row[DATE_IDX].to_pydatetime(), sell_row[BUY_IDX],
sell_row[SELL_IDX],
low=sell_row[LOW_IDX], high=sell_row[HIGH_IDX])
if sell.sell_flag:
trade.close_date = sell_row[DATE_IDX]
trade.sell_reason = sell.sell_type.value
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
trade.sell_reason = sell.sell_reason
trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
@ -265,7 +267,7 @@ class Backtesting:
pair=trade.pair, trade=trade, order_type='limit', amount=trade.amount,
rate=closerate,
time_in_force=time_in_force,
sell_reason=sell.sell_type.value):
sell_reason=sell.sell_reason):
return None
trade.close(closerate, show_msg=False)
@ -293,7 +295,7 @@ class Backtesting:
trade = LocalTrade(
pair=pair,
open_rate=row[OPEN_IDX],
open_date=row[DATE_IDX],
open_date=row[DATE_IDX].to_pydatetime(),
stake_amount=stake_amount,
amount=round(stake_amount / row[OPEN_IDX], 8),
fee_open=self.fee,
@ -315,7 +317,7 @@ class Backtesting:
for trade in open_trades[pair]:
sell_row = data[pair][-1]
trade.close_date = sell_row[DATE_IDX]
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
trade.sell_reason = SellType.FORCE_SELL.value
trade.close(sell_row[OPEN_IDX], show_msg=False)
LocalTrade.close_bt_trade(trade)
@ -396,7 +398,7 @@ class Backtesting:
for trade in open_trades[pair]:
# also check the buying candle for sell conditions.
trade_entry = self._get_sell_trade_entry(trade, row)
trade_entry = self._get_sell_trade_entry(processed[pair], trade, row)
# Sell occured
if trade_entry:
# logger.debug(f"{pair} - Backtesting sell {trade}")

5
freqtrade/rpc/rpc.py
View File

@ -24,7 +24,7 @@ from freqtrade.persistence.models import PairLock
from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
from freqtrade.state import State
from freqtrade.strategy.interface import SellType
from freqtrade.strategy.interface import SellCheckTuple, SellType
logger = logging.getLogger(__name__)
@ -554,7 +554,8 @@ class RPC:
if not fully_canceled:
# Get current rate and execute sell
current_rate = self._freqtrade.get_sell_rate(trade.pair, False)
self._freqtrade.execute_sell(trade, current_rate, SellType.FORCE_SELL)
sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL)
self._freqtrade.execute_sell(trade, current_rate, sell_reason)
# ---- EOF def _exec_forcesell ----
if self._freqtrade.state != State.RUNNING:

104
freqtrade/strategy/interface.py
View File

@ -7,7 +7,7 @@ import warnings
from abc import ABC, abstractmethod
from datetime import datetime, timedelta, timezone
from enum import Enum
from typing import Dict, List, NamedTuple, Optional, Tuple
from typing import Dict, List, Optional, Tuple, Union
import arrow
from pandas import DataFrame
@ -24,6 +24,7 @@ from freqtrade.wallets import Wallets
logger = logging.getLogger(__name__)
CUSTOM_SELL_MAX_LENGTH = 64
class SignalType(Enum):
@ -45,6 +46,7 @@ class SellType(Enum):
SELL_SIGNAL = "sell_signal"
FORCE_SELL = "force_sell"
EMERGENCY_SELL = "emergency_sell"
CUSTOM_SELL = "custom_sell"
NONE = ""
def __str__(self):
@ -52,12 +54,20 @@ class SellType(Enum):
return self.value
class SellCheckTuple(NamedTuple):
class SellCheckTuple(object):
"""
NamedTuple for Sell type + reason
"""
sell_flag: bool
sell_type: SellType
sell_reason: str = ''
def __init__(self, sell_type: SellType, sell_reason: str = ''):
self.sell_type = sell_type
self.sell_reason = sell_reason or sell_type.value
@property
def sell_flag(self):
return self.sell_type != SellType.NONE
class IStrategy(ABC, HyperStrategyMixin):
@ -264,7 +274,7 @@ class IStrategy(ABC, HyperStrategyMixin):
return True
def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
current_profit: float, **kwargs) -> float:
current_profit: float, dataframe: DataFrame, **kwargs) -> float:
"""
Custom stoploss logic, returning the new distance relative to current_rate (as ratio).
e.g. returning -0.05 would create a stoploss 5% below current_rate.
@ -280,11 +290,37 @@ class IStrategy(ABC, HyperStrategyMixin):
:param current_time: datetime object, containing the current datetime
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param dataframe: Analyzed dataframe for this pair. Can contain future data in backtesting.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New stoploss value, relative to the currentrate
"""
return self.stoploss
def custom_sell(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
current_profit: float, dataframe: DataFrame,
**kwargs) -> Optional[Union[str, bool]]:
"""
Custom sell signal logic indicating that specified position should be sold. Returning a
string or True from this method is equal to setting sell signal on a candle at specified
time. This method is not called when sell signal is set.
This method should be overridden to create sell signals that depend on trade parameters. For
example you could implement a stoploss relative to candle when trade was opened, or a custom
1:2 risk-reward ROI.
Custom sell reason max length is 64. Exceeding this limit will raise OperationalException.
:param pair: Pair that's currently analyzed
:param trade: trade object.
:param current_time: datetime object, containing the current datetime
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return: To execute sell, return a string with custom sell reason or True. Otherwise return
None or False.
"""
return None
def informative_pairs(self) -> ListPairsWithTimeframes:
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
@ -500,8 +536,8 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
return False
def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool,
sell: bool, low: float = None, high: float = None,
def should_sell(self, dataframe: DataFrame, trade: Trade, rate: float, date: datetime,
buy: bool, sell: bool, low: float = None, high: float = None,
force_stoploss: float = 0) -> SellCheckTuple:
"""
This function evaluates if one of the conditions required to trigger a sell
@ -517,8 +553,9 @@ class IStrategy(ABC, HyperStrategyMixin):
trade.adjust_min_max_rates(high or current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=date, current_profit=current_profit,
stoplossflag = self.stop_loss_reached(dataframe=dataframe, current_rate=current_rate,
trade=trade, current_time=date,
current_profit=current_profit,
force_stoploss=force_stoploss, high=high)
# Set current rate to high for backtesting sell
@ -531,12 +568,29 @@ class IStrategy(ABC, HyperStrategyMixin):
and self.min_roi_reached(trade=trade, current_profit=current_profit,
current_time=date))
sell_signal = SellType.NONE
custom_reason = ''
if (ask_strategy.get('sell_profit_only', False)
and current_profit <= ask_strategy.get('sell_profit_offset', 0)):
# sell_profit_only and profit doesn't reach the offset - ignore sell signal
sell_signal = False
pass
elif ask_strategy.get('use_sell_signal', True) and not buy:
if sell:
sell_signal = SellType.SELL_SIGNAL
else:
sell_signal = sell and not buy and ask_strategy.get('use_sell_signal', True)
custom_reason = strategy_safe_wrapper(self.custom_sell, default_retval=False)(
pair=trade.pair, trade=trade, current_time=date, current_rate=current_rate,
current_profit=current_profit, dataframe=dataframe)
if custom_reason:
sell_signal = SellType.CUSTOM_SELL
if isinstance(custom_reason, str):
if len(custom_reason) > CUSTOM_SELL_MAX_LENGTH:
logger.warning(f'Custom sell reason returned from custom_sell is too '
f'long and was trimmed to {CUSTOM_SELL_MAX_LENGTH} '
f'characters.')
custom_reason = custom_reason[:CUSTOM_SELL_MAX_LENGTH]
else:
custom_reason = None
# TODO: return here if sell-signal should be favored over ROI
# Start evaluations
@ -545,26 +599,25 @@ class IStrategy(ABC, HyperStrategyMixin):
# Sell-signal
# Stoploss
if roi_reached and stoplossflag.sell_type != SellType.STOP_LOSS:
logger.debug(f"{trade.pair} - Required profit reached. sell_flag=True, "
f"sell_type=SellType.ROI")
return SellCheckTuple(sell_flag=True, sell_type=SellType.ROI)
logger.debug(f"{trade.pair} - Required profit reached. sell_type=SellType.ROI")
return SellCheckTuple(sell_type=SellType.ROI)
if sell_signal:
logger.debug(f"{trade.pair} - Sell signal received. sell_flag=True, "
f"sell_type=SellType.SELL_SIGNAL")
return SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)
if sell_signal != SellType.NONE:
logger.debug(f"{trade.pair} - Sell signal received. "
f"sell_type=SellType.{sell_signal.name}" +
(f", custom_reason={custom_reason}" if custom_reason else ""))
return SellCheckTuple(sell_type=sell_signal, sell_reason=custom_reason)
if stoplossflag.sell_flag:
logger.debug(f"{trade.pair} - Stoploss hit. sell_flag=True, "
f"sell_type={stoplossflag.sell_type}")
logger.debug(f"{trade.pair} - Stoploss hit. sell_type={stoplossflag.sell_type}")
return stoplossflag
# This one is noisy, commented out...
# logger.debug(f"{trade.pair} - No sell signal. sell_flag=False")
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
# logger.debug(f"{trade.pair} - No sell signal.")
return SellCheckTuple(sell_type=SellType.NONE)
def stop_loss_reached(self, current_rate: float, trade: Trade,
def stop_loss_reached(self, dataframe: DataFrame, current_rate: float, trade: Trade,
current_time: datetime, current_profit: float,
force_stoploss: float, high: float = None) -> SellCheckTuple:
"""
@ -582,7 +635,8 @@ class IStrategy(ABC, HyperStrategyMixin):
)(pair=trade.pair, trade=trade,
current_time=current_time,
current_rate=current_rate,
current_profit=current_profit)
current_profit=current_profit,
dataframe=dataframe)
# Sanity check - error cases will return None
if stop_loss_value:
# logger.info(f"{trade.pair} {stop_loss_value=} {current_profit=}")
@ -626,9 +680,9 @@ class IStrategy(ABC, HyperStrategyMixin):
logger.debug(f"{trade.pair} - Trailing stop saved "
f"{trade.stop_loss - trade.initial_stop_loss:.6f}")
return SellCheckTuple(sell_flag=True, sell_type=sell_type)
return SellCheckTuple(sell_type=sell_type)
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
return SellCheckTuple(sell_type=SellType.NONE)
def min_roi_reached_entry(self, trade_dur: int) -> Tuple[Optional[int], Optional[float]]:
"""

6
freqtrade/templates/subtemplates/strategy_methods_advanced.j2
View File

@ -14,8 +14,9 @@ def bot_loop_start(self, **kwargs) -> None:
use_custom_stoploss = True
def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime', current_rate: float,
current_profit: float, **kwargs) -> float:
def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime',
current_rate: float, current_profit: float, dataframe: DataFrame,
**kwargs) -> float:
"""
Custom stoploss logic, returning the new distance relative to current_rate (as ratio).
e.g. returning -0.05 would create a stoploss 5% below current_rate.
@ -31,6 +32,7 @@ def custom_stoploss(self, pair: str, trade: 'Trade', current_time: 'datetime', c
:param current_time: datetime object, containing the current datetime
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param current_profit: Current profit (as ratio), calculated based on current_rate.
:param dataframe: Analyzed dataframe for this pair. Can contain future data in backtesting.
:param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
:return float: New stoploss value, relative to the currentrate
"""

3
tests/strategy/test_default_strategy.py
View File

@ -41,4 +41,5 @@ def test_default_strategy(result, fee):
rate=20000, time_in_force='gtc', sell_reason='roi') is True
assert strategy.custom_stoploss(pair='ETH/BTC', trade=trade, current_time=datetime.now(),
current_rate=20_000, current_profit=0.05) == strategy.stoploss
current_rate=20_000, current_profit=0.05, dataframe=None
) == strategy.stoploss

48
tests/strategy/test_interface.py
View File

@ -360,7 +360,7 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
now = arrow.utcnow().datetime
sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit), trade=trade,
current_time=now, current_profit=profit,
force_stoploss=0, high=None)
force_stoploss=0, high=None, dataframe=None)
assert isinstance(sl_flag, SellCheckTuple)
assert sl_flag.sell_type == expected
if expected == SellType.NONE:
@ -371,7 +371,7 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit2), trade=trade,
current_time=now, current_profit=profit2,
force_stoploss=0, high=None)
force_stoploss=0, high=None, dataframe=None)
assert sl_flag.sell_type == expected2
if expected2 == SellType.NONE:
assert sl_flag.sell_flag is False
@ -382,6 +382,50 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
strategy.custom_stoploss = original_stopvalue
def test_custom_sell(default_conf, fee, caplog) -> None:
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
trade = Trade(
pair='ETH/BTC',
stake_amount=0.01,
amount=1,
open_date=arrow.utcnow().shift(hours=-1).datetime,
fee_open=fee.return_value,
fee_close=fee.return_value,
exchange='binance',
open_rate=1,
)
now = arrow.utcnow().datetime
res = strategy.should_sell(None, trade, 1, now, False, False, None, None, 0)
assert res.sell_flag is False
assert res.sell_type == SellType.NONE
strategy.custom_sell = MagicMock(return_value=True)
res = strategy.should_sell(None, trade, 1, now, False, False, None, None, 0)
assert res.sell_flag is True
assert res.sell_type == SellType.CUSTOM_SELL
assert res.sell_reason == 'custom_sell'
strategy.custom_sell = MagicMock(return_value='hello world')
res = strategy.should_sell(None, trade, 1, now, False, False, None, None, 0)
assert res.sell_type == SellType.CUSTOM_SELL
assert res.sell_flag is True
assert res.sell_reason == 'hello world'
caplog.clear()
strategy.custom_sell = MagicMock(return_value='h' * 100)
res = strategy.should_sell(None, trade, 1, now, False, False, None, None, 0)
assert res.sell_type == SellType.CUSTOM_SELL
assert res.sell_flag is True
assert res.sell_reason == 'h' * 64
assert log_has_re('Custom sell reason returned from custom_sell is too long.*', caplog)
def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
caplog.set_level(logging.DEBUG)
ind_mock = MagicMock(side_effect=lambda x, meta: x)

28
tests/test_freqtradebot.py
View File

@ -1959,7 +1959,7 @@ def test_handle_trade_roi(default_conf, ticker, limit_buy_order_open,
# if ROI is reached we must sell
patch_get_signal(freqtrade, value=(False, True))
assert freqtrade.handle_trade(trade)
assert log_has("ETH/BTC - Required profit reached. sell_flag=True, sell_type=SellType.ROI",
assert log_has("ETH/BTC - Required profit reached. sell_type=SellType.ROI",
caplog)
@ -1988,7 +1988,7 @@ def test_handle_trade_use_sell_signal(
patch_get_signal(freqtrade, value=(False, True))
assert freqtrade.handle_trade(trade)
assert log_has("ETH/BTC - Sell signal received. sell_flag=True, sell_type=SellType.SELL_SIGNAL",
assert log_has("ETH/BTC - Sell signal received. sell_type=SellType.SELL_SIGNAL",
caplog)
@ -2592,14 +2592,16 @@ def test_execute_sell_up(default_conf, ticker, fee, ticker_sell_up, mocker) -> N
fetch_ticker=ticker_sell_up
)
# Prevented sell ...
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
sell_reason=SellCheckTuple(sell_type=SellType.ROI))
assert rpc_mock.call_count == 0
assert freqtrade.strategy.confirm_trade_exit.call_count == 1
# Repatch with true
freqtrade.strategy.confirm_trade_exit = MagicMock(return_value=True)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
sell_reason=SellCheckTuple(sell_type=SellType.ROI))
assert freqtrade.strategy.confirm_trade_exit.call_count == 1
assert rpc_mock.call_count == 1
@ -2651,7 +2653,7 @@ def test_execute_sell_down(default_conf, ticker, fee, ticker_sell_down, mocker)
)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
sell_reason=SellType.STOP_LOSS)
sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
assert rpc_mock.call_count == 2
last_msg = rpc_mock.call_args_list[-1][0][0]
@ -2708,7 +2710,7 @@ def test_execute_sell_down_stoploss_on_exchange_dry_run(default_conf, ticker, fe
trade.stop_loss = 0.00001099 * 0.99
freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
sell_reason=SellType.STOP_LOSS)
sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
assert rpc_mock.call_count == 2
last_msg = rpc_mock.call_args_list[-1][0][0]
@ -2760,7 +2762,7 @@ def test_execute_sell_sloe_cancel_exception(mocker, default_conf, ticker, fee, c
trade.stoploss_order_id = "abcd"
freqtrade.execute_sell(trade=trade, limit=1234,
sell_reason=SellType.STOP_LOSS)
sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
assert sellmock.call_count == 1
assert log_has('Could not cancel stoploss order abcd', caplog)
@ -2810,7 +2812,7 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf, ticker, fee, ticke
)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
sell_reason=SellType.SELL_SIGNAL)
sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
trade = Trade.query.first()
assert trade
@ -2915,7 +2917,8 @@ def test_execute_sell_market_order(default_conf, ticker, fee,
)
freqtrade.config['order_types']['sell'] = 'market'
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'], sell_reason=SellType.ROI)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
sell_reason=SellCheckTuple(sell_type=SellType.ROI))
assert not trade.is_open
assert trade.close_profit == 0.0620716
@ -2969,8 +2972,9 @@ def test_execute_sell_insufficient_funds_error(default_conf, ticker, fee,
fetch_ticker=ticker_sell_up
)
sell_reason = SellCheckTuple(sell_type=SellType.ROI)
assert not freqtrade.execute_sell(trade=trade, limit=ticker_sell_up()['bid'],
sell_reason=SellType.ROI)
sell_reason=sell_reason)
assert mock_insuf.call_count == 1
@ -3063,7 +3067,7 @@ def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, limit_buy_o
freqtrade = FreqtradeBot(default_conf)
patch_get_signal(freqtrade)
freqtrade.strategy.stop_loss_reached = MagicMock(return_value=SellCheckTuple(
sell_flag=False, sell_type=SellType.NONE))
sell_type=SellType.NONE))
freqtrade.enter_positions()
trade = Trade.query.first()
@ -3212,7 +3216,7 @@ def test_locked_pairs(default_conf, ticker, fee, ticker_sell_down, mocker, caplo
)
freqtrade.execute_sell(trade=trade, limit=ticker_sell_down()['bid'],
sell_reason=SellType.STOP_LOSS)
sell_reason=SellCheckTuple(sell_type=SellType.STOP_LOSS))
trade.close(ticker_sell_down()['bid'])
assert freqtrade.strategy.is_pair_locked(trade.pair)

14
tests/test_integration.py
View File

@ -51,8 +51,8 @@ def test_may_execute_sell_stoploss_on_exchange_multi(default_conf, ticker, fee,
side_effect=[stoploss_order_closed, stoploss_order_open, stoploss_order_open])
# Sell 3rd trade (not called for the first trade)
should_sell_mock = MagicMock(side_effect=[
SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)]
SellCheckTuple(sell_type=SellType.NONE),
SellCheckTuple(sell_type=SellType.SELL_SIGNAL)]
)
cancel_order_mock = MagicMock()
mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss)
@ -156,11 +156,11 @@ def test_forcebuy_last_unlimited(default_conf, ticker, fee, limit_buy_order, moc
_notify_sell=MagicMock(),
)
should_sell_mock = MagicMock(side_effect=[
SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL),
SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
SellCheckTuple(sell_flag=None, sell_type=SellType.NONE)]
SellCheckTuple(sell_type=SellType.NONE),
SellCheckTuple(sell_type=SellType.SELL_SIGNAL),
SellCheckTuple(sell_type=SellType.NONE),
SellCheckTuple(sell_type=SellType.NONE),
SellCheckTuple(sell_type=SellType.NONE)]
)
mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)