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Improve outstanding balance

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This commit is contained in:
Matthias 2021-10-02 15:23:09 +02:00
parent 1604436e54
commit e2356c856d
2 changed files with 27 additions and 13 deletions
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6
freqtrade/data/btanalysis.py
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@ -446,13 +446,13 @@ def calculate_outstanding_balance(results: pd.DataFrame, timeframe: str,
from freqtrade.exchange import timeframe_to_minutes
timeframe_min = timeframe_to_minutes(timeframe)
df3 = expand_trades_over_period(results, timeframe, timeframe_min)
trades_over_period = expand_trades_over_period(results, timeframe, timeframe_min)
values = {}
# Iterate over every pair
for pair in hloc:
ohlc = hloc[pair].set_index('date')
df_pair = df3.loc[df3['pair'] == pair]
df_pair = trades_over_period.loc[trades_over_period['pair'] == pair]
# filter on pair and convert dateindex to utc
# * Temporary workaround
df_pair.index = pd.to_datetime(df_pair.index, utc=True)
@ -466,6 +466,6 @@ def calculate_outstanding_balance(results: pd.DataFrame, timeframe: str,
values[pair] = df4
balance = pd.concat([df[['value']] for k, df in values.items()])
# TODO: Does this resample make sense ... ?
# Combine multi-pair balances
balance = balance.resample(f"{timeframe_min}min").agg({"value": sum})
return balance

34
tests/optimize/test_hyperoptloss.py
View File

@ -6,6 +6,7 @@ import pytest
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt_loss_short_trade_dur import ShortTradeDurHyperOptLoss
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
from tests.strategy.test_strategy_helpers import generate_test_data
def test_hyperoptlossresolver_noname(default_conf):
@ -78,14 +79,16 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
assert under > correct
@pytest.mark.parametrize('lossfunction', [
"OnlyProfitHyperOptLoss",
"SortinoHyperOptLoss",
"SortinoHyperOptLossDaily",
"SharpeHyperOptLoss",
"SharpeHyperOptLossDaily",
@pytest.mark.parametrize('lossfunction, needsdata', [
("OnlyProfitHyperOptLoss", False),
("SortinoHyperOptLoss", False),
("SortinoHyperOptLossDaily", False),
("SharpeHyperOptLoss", False),
("SharpeHyperOptLossDaily", False),
("SortinoLossBalance", True),
])
def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunction) -> None:
def test_loss_functions_better_profits(default_conf, hyperopt_results,
lossfunction, needsdata) -> None:
results_over = hyperopt_results.copy()
results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
@ -93,13 +96,24 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
if needsdata:
data = {'ETH/USDT': generate_test_data('5m', 1200, start='2019-01-01')}
else:
data = {}
default_conf.update({'hyperopt_loss': lossfunction})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
datetime(2019, 1, 1), datetime(2019, 5, 1),
config=default_conf, processed=data,
)
over = hl.hyperopt_loss_function(results_over, len(results_over),
datetime(2019, 1, 1), datetime(2019, 5, 1))
datetime(2019, 1, 1), datetime(2019, 5, 1),
config=default_conf, processed=data,
)
under = hl.hyperopt_loss_function(results_under, len(results_under),
datetime(2019, 1, 1), datetime(2019, 5, 1))
datetime(2019, 1, 1), datetime(2019, 5, 1),
config=default_conf, processed=data,
)
assert over < correct
assert under > correct