# -----------------------------------------------------------------------------
# Tune run 5: longer backtest window (2026-01-01 -> 2026-08-01).
#
# Purpose: test the fixed universe provider (_resolve_symbols now honors the
# comma-separated 10-name instruments) and the fixed artifact pinning
# (mlruns/<exp_id>/<run_id>/) over a 7-month out-of-sample window instead of
# the single month (Jul) of run 47e9e369 / tune_run4.
#
# Changes vs tune_run4_fix_universe_longtrain.yaml:
#   - test/backtest window 2026-07-01..08-06  ->  2026-01-01..2026-08-01
#   - train/valid moved back so they stay strictly before test (no leakage):
#       train: 2024-06-03 .. 2025-11-28   (~18 months, ~4500 rows x 10 names)
#       valid: 2025-12-01 .. 2025-12-31   (1 month, right before test)
#       test : 2026-01-01 .. 2026-08-01   (7 months)
#   - everything else held fixed: 5-day label, LGB baseline hyperparams,
#     topk 5 / n_drop 2, benchmark QQQ, universe 10 names.
#
# NOTE: requires the providers.py fix so the universe is actually 10 names
# (not silently expanded to all 17 lake symbols).
#
# Trigger (existing experiment, exp id 4 -> artifacts under
#   $TAC_LAKE_DIR/mlruns/4/<run_id>/ ):
#   rd_run_workflow config_path=tac-qlib/workflows/tune_run5_longtest.yaml \
#       experiment_name=tac-rd-tune2
# -----------------------------------------------------------------------------
{%- set LAKE = TAC_LAKE_DIR %}

qlib_init:
    provider_uri: "{{ LAKE }}"
    region: us
    expression_cache: null
    dataset_cache: null

    calendar_provider:
        class: tac_qlib.data.providers.LakeCalendarProvider
        kwargs:
            lake_root: "{{ LAKE }}"
            market: US
    instrument_provider:
        class: tac_qlib.data.providers.LakeInstrumentProvider
        kwargs:
            lake_root: "{{ LAKE }}"
            market: US
            markets: {}
    feature_provider:
        class: tac_qlib.data.providers.LakeFeatureProvider
        kwargs:
            lake_root: "{{ LAKE }}"
            market: US

    exp_manager:
        class: MLflowExpManager
        module_path: qlib.workflow.expm
        kwargs:
            uri: "sqlite:///{{ LAKE }}/mlruns.db"
            default_exp_name: "tac-rd-tune2"

task:
    model:
        class: LGBModel
        module_path: qlib.contrib.model.gbdt
        kwargs:
            loss: mse
            learning_rate: 0.05
            num_leaves: 15
            num_boost_round: 1000
            early_stopping_rounds: 50
            colsample_bytree: 0.8
            subsample: 0.8
            subsample_freq: 1
            reg_alpha: 0.01
            reg_lambda: 0.01
            seed: 2026

    dataset:
        class: DatasetH
        module_path: qlib.data.dataset
        kwargs:
            handler:
                class: TACHandler
                module_path: tac_qlib.contrib.data.handler
                kwargs:
                    instruments: AAPL,MSFT,TSLA,QQQ,IVV,SMH,TLT,IBIT,MCHI,AIQ
                    start_time: 2000-01-03
                    end_time: 2026-08-01
                    fit_start_time: 2024-06-03
                    fit_end_time: 2025-11-28
                    freq: day
                    lake_root: "{{ LAKE }}"
                    market: US
                    label: "Ref($close,-6)/Ref($close,-1)-1"
            segments:
                train: [2024-06-03, 2025-11-28]
                valid: [2025-12-01, 2025-12-31]
                test:  [2026-01-01, 2026-08-01]

    record:
        - class: SignalRecord
          module_path: qlib.workflow.record_temp
          kwargs: {}

        - class: SigAnaRecord
          module_path: qlib.workflow.record_temp
          kwargs:
              ana_long_short: true
              ann_scaler: 252

        - class: PortAnaRecord
          module_path: qlib.workflow.record_temp
          kwargs:
              config:
                  strategy:
                      class: TopkDropoutStrategy
                      module_path: qlib.contrib.strategy
                      kwargs:
                          signal: "<PRED>"
                          topk: 5
                          n_drop: 2
                          only_tradable: true
                          risk_degree: 0.95
                  backtest:
                      start_time: 2026-01-01
                      end_time: 2026-08-01
                      account: 1000000
                      benchmark: QQQ
                      exchange_kwargs:
                          codes: AAPL,MSFT,TSLA,QQQ,IVV,SMH,TLT,IBIT,MCHI,AIQ
                          deal_price: $close
                          freq: day
                          open_cost: 0.0005
                          close_cost: 0.0015
                          min_cost: 5.0
              risk_analysis_freq: 1d