Merge pull request #6228 from clover-es/feat/short

Stoploss from open for shorts
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Matthias 2022-01-18 16:49:58 +01:00 committed by GitHub
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2 changed files with 45 additions and 36 deletions

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@ -1,6 +1,5 @@
import pandas as pd
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes
@ -81,30 +80,26 @@ def stoploss_from_open(
The requested stop can be positive for a stop above the open price, or negative for
a stop below the open price. The return value is always >= 0.
Returns 0 if the resulting stop price would be above the current price.
Returns 0 if the resulting stop price would be above/below (longs/shorts) the current price
:param open_relative_stop: Desired stop loss percentage relative to open price
:param current_profit: The current profit percentage
:param for_short: When true, perform the calculation for short instead of long
:return: Stop loss value relative to current price
"""
# formula is undefined for current_profit -1, return maximum value
if current_profit == -1:
# formula is undefined for current_profit -1 (longs) or 1 (shorts), return maximum value
if (current_profit == -1 and not for_short) or (for_short and current_profit == 1):
return 1
if for_short is True:
# TODO-lev: How would this be calculated for short
raise OperationalException(
"Freqtrade hasn't figured out how to calculated stoploss on shorts")
# stoploss = 1-((1+open_relative_stop)/(1+current_profit))
stoploss = -1+((1-open_relative_stop)/(1-current_profit))
else:
stoploss = 1-((1+open_relative_stop)/(1+current_profit))
# negative stoploss values indicate the requested stop price is higher than the current price
if for_short:
return min(stoploss, 0.0)
else:
return max(stoploss, 0.0)
# negative stoploss values indicate the requested stop price is higher/lower
# (long/short) than the current price
return max(stoploss, 0.0)
def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:

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@ -109,33 +109,47 @@ def test_stoploss_from_open():
[1, 100, 30],
[100, 10000, 30],
]
current_profit_range = [-0.99, 2, 30]
# profit range for long is [-1, inf] while for shorts is [-inf, 1]
current_profit_range_dict = {'long': [-0.99, 2, 30], 'short': [-2.0, 0.99, 30]}
desired_stop_range = [-0.50, 0.50, 30]
for open_range in open_price_ranges:
for open_price in np.linspace(*open_range):
for desired_stop in np.linspace(*desired_stop_range):
for side, current_profit_range in current_profit_range_dict.items():
for open_range in open_price_ranges:
for open_price in np.linspace(*open_range):
for desired_stop in np.linspace(*desired_stop_range):
# -1 is not a valid current_profit, should return 1
assert stoploss_from_open(desired_stop, -1) == 1
for current_profit in np.linspace(*current_profit_range):
current_price = open_price * (1 + current_profit)
expected_stop_price = open_price * (1 + desired_stop)
stoploss = stoploss_from_open(desired_stop, current_profit)
assert stoploss >= 0
assert stoploss <= 1
stop_price = current_price * (1 - stoploss)
# there is no correct answer if the expected stop price is above
# the current price
if expected_stop_price > current_price:
assert stoploss == 0
if side == 'long':
# -1 is not a valid current_profit, should return 1
assert stoploss_from_open(desired_stop, -1) == 1
else:
assert isclose(stop_price, expected_stop_price, rel_tol=0.00001)
# 1 is not a valid current_profit for shorts, should return 1
assert stoploss_from_open(desired_stop, 1, True) == 1
for current_profit in np.linspace(*current_profit_range):
if side == 'long':
current_price = open_price * (1 + current_profit)
expected_stop_price = open_price * (1 + desired_stop)
stoploss = stoploss_from_open(desired_stop, current_profit)
stop_price = current_price * (1 - stoploss)
else:
current_price = open_price * (1 - current_profit)
expected_stop_price = open_price * (1 - desired_stop)
stoploss = stoploss_from_open(desired_stop, current_profit, True)
stop_price = current_price * (1 + stoploss)
assert stoploss >= 0
# Technically the formula can yield values greater than 1 for shorts
# eventhough it doesn't make sense because the position would be liquidated
if side == 'long':
assert stoploss <= 1
# there is no correct answer if the expected stop price is above
# the current price
if (side == 'long' and expected_stop_price > current_price) \
or (side == 'short' and expected_stop_price < current_price):
assert stoploss == 0
else:
assert isclose(stop_price, expected_stop_price, rel_tol=0.00001)
def test_stoploss_from_absolute():