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feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns (#95)

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* feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns

* fix(Sweep): config

* fix(Sweep): name

* fix(Sweep): grid

* feat(Config): separated sliding_window_size_level1 & sliding_window_size_level2

* feat(Dependencies): added ray, now using it to parallel process feature extraction

* fix(Dependencies): added pip explicitly

* fix(Dependencies): removed ray from root

* fix(Models): average model was probably not taking the right timestamp to average

* feat(Config): separated expanding_window_level1 & expanding_window_level2

* fix(Config): set n_features_to_select to the optimal 30
This commit is contained in:
Mark Aron Szulyovszky
2021-12-28 22:50:09 +01:00
committed by GitHub
parent cc70d3f907
commit f762ceed2a
13 changed files with 626 additions and 417 deletions
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feature_extractors/feature_extractor_presets.py
+2
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@@ -1,6 +1,7 @@
from feature_extractors.feature_extractors import feature_lag, feature_mom, feature_ROC, feature_RSI, feature_STOD, feature_STOK, feature_vol, feature_day_of_month, feature_day_of_week, feature_month, feature_debug_future_lookahead
from utils.typing import FeatureExtractorConfig
from utils.helpers import flatten
from feature_extractors.fractional_differentiation import feature_fractional_differentiation
__presets = dict(
debug_future_lookahead = [('debug_future', feature_debug_future_lookahead, [1])],
@@ -22,6 +23,7 @@ __presets = dict(
rsi = [('rsi', feature_ROC, [10, 30, 100])],
stod = [('stod', feature_STOD, [10, 30, 200])],
stok = [('stok', feature_STOK, [10, 30, 200])],
fracdiff = [('fracdiff', feature_fractional_differentiation, [10, 30])],
)
presets = __presets | dict(