# start & end time for training/validation/test datasets start_time: !!str &start 2020-01-01 end_time: !!str &end 2020-07-31 train_end_time: !!str &tend 2020-03-31 valid_start_time: !!str &vstart 2020-04-01 valid_end_time: !!str &vend 2020-05-31 test_start_time: !!str &tstart 2020-06-01 # the instrument set instruments: &ins all # qlib related configuration qlib_conf: provider_uri: ./data/bin # path to generated qlib bin redis_port: 233 feature_conf: path: ./data/pickle/feature.pkl # output path of feature class: DatasetH module_path: qlib.data.dataset kwargs: handler: class: HighFreqGeneralHandler module_path: qlib.contrib.data.highfreq_handler kwargs: start_time: *start end_time: *end fit_start_time: *start fit_end_time: *tend instruments: *ins day_length: 240 # how many minutes in one trading day infer_processors: - class: HighFreqNorm module_path: qlib.contrib.data.highfreq_processor kwargs: feature_save_dir: ./stat/ # output path of statistics of features (for feature normalization) norm_groups: price: 10 volume: 2 segments: train: !!python/tuple [*start, *tend] valid: !!python/tuple [*vstart, *vend] test: !!python/tuple [*tstart, *end] backtest_conf: path: ./data/pickle/backtest.pkl # output path of backtest class: DatasetH module_path: qlib.data.dataset kwargs: handler: class: HighFreqGeneralBacktestHandler module_path: qlib.contrib.data.highfreq_handler kwargs: start_time: *start end_time: *end instruments: *ins day_length: 240 segments: train: !!python/tuple [*start, *tend] valid: !!python/tuple [*vstart, *vend] test: !!python/tuple [*tstart, *end]