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Add the HIST and IGMTF model on Alpha360 (#1040)
* Commit the code of HIST and IGMTF on Alpha360 * add stock index * Update README.md * delete useless code * fix the bug of code format with black * fix pylint bugs * fix the bugs of pylint * fix pylint bugs * fix flake8
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examples/benchmarks/HIST/README.md
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examples/benchmarks/HIST/README.md
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# HIST
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* Code: [https://github.com/Wentao-Xu/HIST](https://github.com/Wentao-Xu/HIST)
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* Paper: [HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared InformationAdaRNN: Adaptive Learning and Forecasting for Time Series](https://arxiv.org/abs/2110.13716).
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examples/benchmarks/HIST/qlib_csi300_stock_index.npy
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examples/benchmarks/HIST/qlib_csi300_stock_index.npy
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examples/benchmarks/HIST/requirements.txt
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examples/benchmarks/HIST/requirements.txt
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pandas==1.1.2
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numpy==1.21.0
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scikit_learn==0.23.2
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torch==1.7.0
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examples/benchmarks/HIST/workflow_config_hist_Alpha360.yaml
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examples/benchmarks/HIST/workflow_config_hist_Alpha360.yaml
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qlib_init:
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provider_uri: "~/.qlib/qlib_data/cn_data"
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region: cn
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market: &market csi300
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benchmark: &benchmark SH000300
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data_handler_config: &data_handler_config
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start_time: 2008-01-01
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end_time: 2020-08-01
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fit_start_time: 2008-01-01
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fit_end_time: 2014-12-31
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instruments: *market
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infer_processors:
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- class: RobustZScoreNorm
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kwargs:
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fields_group: feature
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clip_outlier: true
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- class: Fillna
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kwargs:
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fields_group: feature
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learn_processors:
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- class: DropnaLabel
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- class: CSRankNorm
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kwargs:
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fields_group: label
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label: ["Ref($close, -2) / Ref($close, -1) - 1"]
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port_analysis_config: &port_analysis_config
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strategy:
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class: TopkDropoutStrategy
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module_path: qlib.contrib.strategy
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kwargs:
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signal:
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- <MODEL>
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- <DATASET>
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topk: 50
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n_drop: 5
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backtest:
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start_time: 2017-01-01
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end_time: 2020-08-01
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account: 100000000
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benchmark: *benchmark
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exchange_kwargs:
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limit_threshold: 0.095
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deal_price: close
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open_cost: 0.0005
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close_cost: 0.0015
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min_cost: 5
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task:
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model:
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class: HIST
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module_path: qlib.contrib.model.pytorch_hist
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kwargs:
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d_feat: 6
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hidden_size: 64
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num_layers: 2
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dropout: 0
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n_epochs: 200
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lr: 1e-4
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early_stop: 20
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metric: ic
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loss: mse
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base_model: LSTM
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model_path: "benchmarks/LSTM/model_lstm_csi300.pkl"
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stock2concept: "benchmarks/HIST/qlib_csi300_stock2concept.npy"
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stock_index: "benchmarks/HIST/qlib_csi300_stock_index.npy"
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GPU: 0
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dataset:
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class: DatasetH
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module_path: qlib.data.dataset
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kwargs:
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handler:
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class: Alpha360
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module_path: qlib.contrib.data.handler
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kwargs: *data_handler_config
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segments:
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train: [2008-01-01, 2014-12-31]
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valid: [2015-01-01, 2016-12-31]
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test: [2017-01-01, 2020-08-01]
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record:
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- class: SignalRecord
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module_path: qlib.workflow.record_temp
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kwargs:
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model: <MODEL>
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dataset: <DATASET>
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- class: SigAnaRecord
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module_path: qlib.workflow.record_temp
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kwargs:
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ana_long_short: False
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ann_scaler: 252
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- class: PortAnaRecord
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module_path: qlib.workflow.record_temp
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kwargs:
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config: *port_analysis_config
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