Test and document leverage strategy callback

This commit is contained in:
Matthias 2021-09-22 20:14:52 +02:00
parent c791b95405
commit 5928ba9c88
5 changed files with 83 additions and 20 deletions

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@ -642,6 +642,34 @@ Freqtrade will fall back to the `proposed_stake` value should your code raise an
!!! Tip !!! Tip
Returning `0` or `None` will prevent trades from being placed. Returning `0` or `None` will prevent trades from being placed.
## Leverage Callback
When trading in markets that allow leverage, this method must return the desired Leverage (Defaults to 1 -> No leverage).
Assuming a capital of 500USDT, a trade with leverage=3 would result in a position with 500 x 3 = 1500 USDT.
Values that are above `max_leverage` will be adjusted to `max_leverage`.
For markets / exchanges that don't support leverage, this method is ignored.
``` python
class AwesomeStrategy(IStrategy):
def leverage(self, pair: str, current_time: 'datetime', current_rate: float,
proposed_leverage: float, max_leverage: float, side: str,
**kwargs) -> float:
"""
Customize leverage for each new trade.
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param proposed_leverage: A leverage proposed by the bot.
:param max_leverage: Max leverage allowed on this pair
:param side: 'long' or 'short' - indicating the direction of the proposed trade
:return: A leverage amount, which is between 1.0 and max_leverage.
"""
return 1.0
```
--- ---
## Derived strategies ## Derived strategies

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@ -370,8 +370,7 @@ class IStrategy(ABC, HyperStrategyMixin):
proposed_stake: float, min_stake: float, max_stake: float, proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float: **kwargs) -> float:
""" """
Customize stake size for each new trade. This method is not called when edge module is Customize stake size for each new trade.
enabled.
:param pair: Pair that's currently analyzed :param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime :param current_time: datetime object, containing the current datetime
@ -383,6 +382,23 @@ class IStrategy(ABC, HyperStrategyMixin):
""" """
return proposed_stake return proposed_stake
def leverage(self, pair: str, current_time: datetime, current_rate: float,
proposed_leverage: float, max_leverage: float, side: str,
**kwargs) -> float:
"""
Customize leverage for each new trade. This method is not called when edge module is
enabled.
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param proposed_leverage: A leverage proposed by the bot.
:param max_leverage: Max leverage allowed on this pair
:param side: 'long' or 'short' - indicating the direction of the proposed trade
:return: A leverage amount, which is between 1.0 and max_leverage.
"""
return 1.0
def informative_pairs(self) -> ListPairsWithTimeframes: def informative_pairs(self) -> ListPairsWithTimeframes:
""" """
Define additional, informative pair/interval combinations to be cached from the exchange. Define additional, informative pair/interval combinations to be cached from the exchange.
@ -971,20 +987,3 @@ class IStrategy(ABC, HyperStrategyMixin):
if 'exit_long' not in df.columns: if 'exit_long' not in df.columns:
df = df.rename({'sell': 'exit_long'}, axis='columns') df = df.rename({'sell': 'exit_long'}, axis='columns')
return df return df
def leverage(self, pair: str, current_time: datetime, current_rate: float,
proposed_leverage: float, max_leverage: float, side: str,
**kwargs) -> float:
"""
Customize leverage for each new trade. This method is not called when edge module is
enabled.
:param pair: Pair that's currently analyzed
:param current_time: datetime object, containing the current datetime
:param current_rate: Rate, calculated based on pricing settings in ask_strategy.
:param proposed_leverage: A leverage proposed by the bot.
:param max_leverage: Max leverage allowed on this pair
:param side: 'long' or 'short' - indicating the direction of the proposed trade
:return: A leverage amount, which is between 1.0 and max_leverage.
"""
return 1.0

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@ -36,6 +36,7 @@ logging.getLogger('').setLevel(logging.INFO)
np.seterr(all='raise') np.seterr(all='raise')
CURRENT_TEST_STRATEGY = 'StrategyTestV3' CURRENT_TEST_STRATEGY = 'StrategyTestV3'
TRADE_SIDES = ('long', 'short')
def pytest_addoption(parser): def pytest_addoption(parser):

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@ -1,5 +1,6 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
from datetime import datetime
import talib.abstract as ta import talib.abstract as ta
from pandas import DataFrame from pandas import DataFrame
@ -159,3 +160,11 @@ class StrategyTestV3(IStrategy):
# TODO-lev: Add short logic # TODO-lev: Add short logic
return dataframe return dataframe
def leverage(self, pair: str, current_time: datetime, current_rate: float,
proposed_leverage: float, max_leverage: float, side: str,
**kwargs) -> float:
# Return 3.0 in all cases.
# Bot-logic must make sure it's an allowed leverage and eventually adjust accordingly.
return 3.0

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@ -21,7 +21,7 @@ from freqtrade.strategy.hyper import (BaseParameter, BooleanParameter, Categoric
DecimalParameter, IntParameter, RealParameter) DecimalParameter, IntParameter, RealParameter)
from freqtrade.strategy.interface import SellCheckTuple from freqtrade.strategy.interface import SellCheckTuple
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from tests.conftest import log_has, log_has_re from tests.conftest import CURRENT_TEST_STRATEGY, TRADE_SIDES, log_has, log_has_re
from .strats.strategy_test_v3 import StrategyTestV3 from .strats.strategy_test_v3 import StrategyTestV3
@ -506,6 +506,32 @@ def test_custom_sell(default_conf, fee, caplog) -> None:
assert log_has_re('Custom sell reason returned from custom_sell is too long.*', caplog) assert log_has_re('Custom sell reason returned from custom_sell is too long.*', caplog)
@pytest.mark.parametrize('side', TRADE_SIDES)
def test_leverage_callback(default_conf, side) -> None:
default_conf['strategy'] = 'StrategyTestV2'
strategy = StrategyResolver.load_strategy(default_conf)
assert strategy.leverage(
pair='XRP/USDT',
current_time=datetime.now(timezone.utc),
current_rate=2.2,
proposed_leverage=1.0,
max_leverage=5.0,
side=side,
) == 1
default_conf['strategy'] = CURRENT_TEST_STRATEGY
strategy = StrategyResolver.load_strategy(default_conf)
assert strategy.leverage(
pair='XRP/USDT',
current_time=datetime.now(timezone.utc),
current_rate=2.2,
proposed_leverage=1.0,
max_leverage=5.0,
side=side,
) == 3
def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None: def test_analyze_ticker_default(ohlcv_history, mocker, caplog) -> None:
caplog.set_level(logging.DEBUG) caplog.set_level(logging.DEBUG)
ind_mock = MagicMock(side_effect=lambda x, meta: x) ind_mock = MagicMock(side_effect=lambda x, meta: x)