# region declaration
schema_version: "1.0"
metadata:
  name: book_compiled_selection
  mode: development
sfd:
  manifest:
    type: ml
# region recorded_source
    data_source:
      method: limen.data.HistoricalData.get_any_file
      params:
        file_path_or_url: inputs/spot_15m_20250101_20250531.parquet
# endregion recorded_source
    split_dates:
      train_start: "2025-01-01"
      train_end: "2025-01-15"
      val_start: "2025-01-15"
      val_end: "2025-01-18"
      test_start: "2025-01-18"
      test_end: "2025-01-22"
# region momentum_indicator
    indicators:
      - func: limen.indicators.roc
        params:
          period: 1
          group: momentum
# endregion momentum_indicator
# region fitted_target
    target:
      name: quantile_flag
      class: limen.targets.QuantileBinaryTarget
      fit_params:
        source_column: roc_1
        quantile: 0.5
      transform_params:
        shift: -1
# endregion fitted_target
# region validation_objective
    objective:
      metric: backtest_total_return
      direction: maximize
# endregion validation_objective
    backtest:
      source_interval_seconds: 900
      fee_bps: 1.0
      slip_bps: 0.0
      product:
        kind: cash_spot
        instrument: BTCUSDT
        base_currency: BTC
        quote_currency: USDT
        quantity_step: 1.0e-9
        min_notional: 0.0
# region fitted_scaler
    scaler:
      from_params: scaler_type
# endregion fitted_scaler
    reference_architecture: limen.sfd.reference_architecture.logreg_binary
  params:
    scaler_type: [logreg]
    C: [1.0, 0.5]
    random_state: [42]
uel:
  output_path: compiled-cli
  n_permutations: 2
  search_strategy:
    type: grid
  output_format: csv

# region assessment
assessment:
  metric: val_backtest_total_return
  direction: maximize
  top_k: 1
  predict: true
# endregion assessment
# endregion declaration