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fix(Labelling): didn't forward shift forward returns previously, introduced major lookahead bias (#249)

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* fix(Labelling): didn't forward shift forward returns previously, introduced major lookahead bias

* fix(Baseline): use the same config
This commit is contained in:
Mark Aron Szulyovszky
2022-03-15 19:12:40 +01:00
committed by GitHub
parent 7deeb2de01
commit 2606639cc2
3 changed files with 7 additions and 12 deletions
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config/presets.py
+5 -5
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@@ -23,16 +23,16 @@ def get_default_config() -> RawConfig:
assets=["fivemin_crypto"], assets=["fivemin_crypto"],
target_asset="BTCUSDT", target_asset="BTCUSDT",
other_assets=[], other_assets=[],
exogenous_data=[], exogenous_data=["daily_glassnode"],
load_non_target_asset=True, load_non_target_asset=True,
own_features=["level_1"], own_features=["level_2"],
other_features=["z_score"], other_features=["z_score"],
exogenous_features=[], exogenous_features=["z_score"],
directional_models=classification_models, directional_models=classification_models,
meta_models=meta_models, meta_models=meta_models,
event_filter="cusum_vol", event_filter="cusum_vol",
event_filter_multiplier=3.5, event_filter_multiplier=3.5,
remove_overlapping_events=True, remove_overlapping_events=False,
labeling="two_class", labeling="two_class",
forecasting_horizon=10, forecasting_horizon=10,
transaction_costs=0.002, transaction_costs=0.002,
@@ -74,7 +74,7 @@ def get_minimal_config() -> RawConfig:
event_filter_multiplier=3.5, event_filter_multiplier=3.5,
remove_overlapping_events=False, remove_overlapping_events=False,
labeling="two_class", labeling="two_class",
forecasting_horizon=10, forecasting_horizon=1,
transaction_costs=0.002, transaction_costs=0.002,
save_models=True, save_models=True,
ensembling_method="voting_soft", ensembling_method="voting_soft",
labeling/labellers/utils.py
+1 -3
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@@ -8,9 +8,7 @@ import numpy as np
def create_forward_returns(series: pd.Series, period: int) -> ForwardReturnSeries: def create_forward_returns(series: pd.Series, period: int) -> ForwardReturnSeries:
assert period > 0 assert period > 0
indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=period) indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=period)
return series.rolling(window=indexer).sum().shift(-1)
forward_returns = series.rolling(window=indexer).sum()
return forward_returns
def purge_overlapping_events(events: EventsDataFrame) -> EventsDataFrame: def purge_overlapping_events(events: EventsDataFrame) -> EventsDataFrame:
run_baseline.py
+1 -4
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@@ -1,6 +1,3 @@
from re import S
from typing import Optional
from sklearn.model_selection import train_test_split from sklearn.model_selection import train_test_split
from config.types import Config, RawConfig from config.types import Config, RawConfig
@@ -65,5 +62,5 @@ def run_sklearn_training(config: Config):
if __name__ == "__main__": if __name__ == "__main__":
run_sklearn_pipeline( run_sklearn_pipeline(
raw_config=get_minimal_config(), raw_config=get_default_config(),
) )