liuyu/qlib

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Huoran Li 653c082e7a Order execution open source (#1447 )

* Waiting for bin data

* Complete readme

* CI

* Add inst filter by time

* Update qlib/data/dataset/processor.py

* typo

* Fix time filter bug

* Add Filter and set Universe

* Complete data pipeline

* Fix Provider Logger Info Args

* Add DQN; a minor bugfix in ppo reward.

* update readme. modify assertion logic in strategy check.

* Fix Doc issues and fix black

* Fix pylint Error

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Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>

2023-03-13 12:06:28 +08:00

..

features_resample_N.py

Merge nested main (#597 )

2021-10-01 02:15:30 +08:00

features_sample.py

Add docs for the reampling example. (#1285 )

2022-09-14 18:02:19 +08:00

multi_freq_handler.py

Order execution open source (#1447 )

2023-03-13 12:06:28 +08:00

README.md

Update README.md

2022-07-08 17:56:59 +08:00

requirements.txt

Csi500 example (#1126 )

2022-06-15 10:18:13 +08:00

workflow_config_lightgbm_Alpha158_csi500.yaml

Update LightGBM alpha158 csi500 result (#1199 )

2022-08-05 16:45:54 +08:00

workflow_config_lightgbm_Alpha158_multi_freq.yaml

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2023-03-13 12:06:28 +08:00

workflow_config_lightgbm_Alpha158.yaml

Being compatible with previous Qlib version

2021-10-16 16:43:38 +00:00

workflow_config_lightgbm_Alpha360_csi500.yaml

Csi500 example (#1126 )

2022-06-15 10:18:13 +08:00

workflow_config_lightgbm_Alpha360.yaml

simplify signal parameter

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workflow_config_lightgbm_configurable_dataset.yaml

simplify signal parameter

2021-10-15 14:48:31 +00:00

workflow_config_lightgbm_multi_freq.yaml

Order execution open source (#1447 )

2023-03-13 12:06:28 +08:00

README.md

LightGBM

Code: https://github.com/microsoft/LightGBM
Paper: LightGBM: A Highly Efficient Gradient Boosting Decision Tree. https://proceedings.neurips.cc/paper/2017/file/6449f44a102fde848669bdd9eb6b76fa-Paper.pdf.

Introductions about the settings/configs.

workflow_config_lightgbm_multi_freq.yaml

It uses data sources of different frequencies (i.e. multiple frequencies) for daily prediction.