101 lines
2.9 KiB
YAML
101 lines
2.9 KiB
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 all
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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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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.strategy
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kwargs:
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topk: 50
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n_drop: 5
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backtest:
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verbose: False
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limit_threshold: 0.095
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account: 100000000
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benchmark: *benchmark
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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: DEnsembleModel
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module_path: qlib.contrib.model.double_ensemble
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kwargs:
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base_model: "gbm"
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loss: mse
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num_models: 6
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enable_sr: True
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enable_fs: True
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alpha1: 1
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alpha2: 1
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bins_sr: 10
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bins_fs: 5
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decay: 0.5
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sample_ratios:
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- 0.8
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- 0.7
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- 0.6
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- 0.5
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- 0.4
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sub_weights:
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- 1
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- 0.2
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- 0.2
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- 0.2
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- 0.2
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- 0.2
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epochs: 136
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colsample_bytree: 0.8879
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learning_rate: 0.0421
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subsample: 0.8789
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lambda_l1: 205.6999
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lambda_l2: 580.9768
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max_depth: 8
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num_leaves: 210
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num_threads: 20
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verbosity: -1
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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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- class: SignalMseRecord
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module_path: qlib.contrib.workflow.record_temp
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kwargs: {}
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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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