mirror of
https://github.com/NicolasBohn/NexQuant.git
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TPTBusiness
574a9cb75e
Root Cause: Qlib configs used cn_data (Chinese stocks) instead of eurusd - provider_uri: cn_data → eurusd_1min_data - market: csi300 → eurusd - topk: 50 → 1 (single-asset EURUSD, was opening 0 positions) - n_drop: 5 → 0, limit_threshold: 0.095 → 0.0 Add failed run tracking and validation: - factor_runner.py: Validate results before DB save, track failed runs - model_runner.py: Same validation and tracking - results_db.py: generate_results_summary() → RESULTS_SUMMARY.md - extract_results.py: Failed run tracking, progress indicators Fix project root paths in all modules: - ResultsDatabase: correct path from rdagent/results/ → results/ - factor_runner: db, factors, failed_runs paths - model_runner: failed_runs path All 246 tests passing.
102 lines
3.3 KiB
YAML
102 lines
3.3 KiB
YAML
qlib_init:
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provider_uri: "~/.qlib/qlib_data/eurusd_1min_data"
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region: cn
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market: &market eurusd
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benchmark: &benchmark EURUSD
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data_handler_config: &data_handler_config
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start_time: {{ train_start | default("2008-01-01", true) }}
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end_time: {{ test_end | default("null", true) }}
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instruments: *market
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data_loader:
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class: NestedDataLoader
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kwargs:
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dataloader_l:
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- class: qlib.contrib.data.loader.Alpha158DL
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kwargs:
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config:
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label:
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- ["Ref($close, -2)/Ref($close, -1) - 1"]
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- ["LABEL0"]
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feature:
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- {{ feature_expressions }}
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- {{ feature_names }}
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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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fit_start_time: {{ train_start | default("2008-01-01", true) }}
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fit_end_time: {{ train_end | default("2014-12-31", 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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kwargs:
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fields_group: label
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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: <PRED>
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topk: 1
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n_drop: 0
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backtest:
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start_time: {{ test_start | default("2017-01-01", true) }}
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end_time: {{ test_end | default("null", true) }}
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account: 100000000
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benchmark: *benchmark
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exchange_kwargs:
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limit_threshold: 0.0
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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: 0
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task:
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model:
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class: LGBModel
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module_path: qlib.contrib.model.gbdt
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kwargs:
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loss: mse
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colsample_bytree: 0.8879
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learning_rate: 0.2
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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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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: DataHandlerLP
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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: [{{ train_start | default("2008-01-01", true) }}, {{ train_end | default("2014-12-31", true) }}]
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valid: [{{ valid_start | default("2015-01-01", true) }}, {{ valid_end | default("2016-12-31", true) }}]
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test: [{{ test_start | default("2017-01-01", true) }}, {{ test_end | default("null", true) }}]
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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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