134 lines
5.1 KiB
YAML
134 lines
5.1 KiB
YAML
# -----------------------------------------------------------------------------
|
|
# ABLATION A (baseline): LightGBM with RankIC early-stopping on the 50-ETF SP-5d
|
|
# panel, using ALL 24 sp_* feature columns (ou,hmm,jump,har,trend,hurst,
|
|
# signature). Copy of the canonical workflow_lgb_sp5d_rankic.yaml with a
|
|
# distinct experiment name so the ablation runs are isolated.
|
|
#
|
|
# Run:
|
|
# rd_run_workflow config_path=tac-qlib/workflows/ablate_baseline_all_sp_fields.yaml \
|
|
# experiment_name=tac-rd-rank-ablate
|
|
# -----------------------------------------------------------------------------
|
|
{%- set LAKE = TAC_LAKE_DIR %}
|
|
{%- set UNIVERSE = "SPY,QQQ,DIA,IWM,MDY,VTI,VOO,VEA,VWO,VT,EFA,EEM,TLT,IEF,SHY,AGG,BND,LQD,HYG,JNK,EMB,GLD,SLV,USO,UNG,DBA,DBC,XLK,XLF,XLE,XLV,XLI,XLY,XLP,XLU,XLB,XLRE,ARKK,SMH,SOXX,IBB,XBI,ITA,XAR,ICLN,TAN,FDN,IGV,ESPO,REM" %}
|
|
{%- set SP_FIELDS = "sp_ret,sp_ou_zscore,sp_ou_half_life,sp_ou_revert,sp_hmm_p_regime1,sp_hmm_state,sp_jump_ratio,sp_jump_flag,sp_jump_tail,sp_max_move,sp_rv1,sp_rv5,sp_rv22,sp_vol_ratio_5_22,sp_vol_ratio_1_22,sp_trend_slope_5,sp_trend_slope_20,sp_trend_slope_60,sp_logp,sp_hurst_exponent,sp_sig_level1_lead,sp_sig_level1_lag,sp_sig_level2_lead_lag,sp_sig_level2_lag_lead" %}
|
|
|
|
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-rank-ablate"
|
|
|
|
task:
|
|
model:
|
|
class: RankICLGBModel
|
|
module_path: tac_qlib.contrib.model.rank_gbdt
|
|
kwargs:
|
|
loss: mse
|
|
learning_rate: 0.02
|
|
num_leaves: 31
|
|
n_estimators: 3000
|
|
num_boost_round: 3000
|
|
early_stopping_rounds: 200
|
|
min_data_in_leaf: 20
|
|
lambda_l2: 0.5
|
|
colsample_bytree: 0.8
|
|
subsample: 0.8
|
|
subsample_freq: 1
|
|
reg_alpha: 0.1
|
|
reg_lambda: 1.0
|
|
seed: 42
|
|
|
|
dataset:
|
|
class: DatasetH
|
|
module_path: qlib.data.dataset
|
|
kwargs:
|
|
handler:
|
|
class: TACHandler
|
|
module_path: tac_qlib.contrib.data.handler
|
|
kwargs:
|
|
instruments: "{{ UNIVERSE }}"
|
|
start_time: 2015-01-03
|
|
end_time: 2026-08-10
|
|
fit_start_time: 2015-01-03
|
|
fit_end_time: 2025-09-01
|
|
freq: day
|
|
lake_root: "{{ LAKE }}"
|
|
market: US
|
|
label: "Ref($close,-6)/Ref($close,-1)-1"
|
|
feature_fields: "$open,$high,$low,$close,$vwap,$volume,{{ SP_FIELDS }}"
|
|
infer_processors:
|
|
- class: DropAllNaN
|
|
kwargs: {}
|
|
- class: ProcessInf
|
|
kwargs: {}
|
|
- class: CSRankNorm
|
|
kwargs: {}
|
|
- class: ZScoreNorm
|
|
kwargs: {}
|
|
- class: Fillna
|
|
kwargs: {}
|
|
segments:
|
|
train: [2015-01-03, 2025-09-01]
|
|
valid: [2025-09-03, 2026-01-03]
|
|
test: [2026-01-04, 2026-08-10]
|
|
|
|
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: 10
|
|
n_drop: 2
|
|
only_tradable: true
|
|
risk_degree: 0.95
|
|
backtest:
|
|
start_time: 2026-01-04
|
|
end_time: 2026-08-10
|
|
account: 1000000
|
|
benchmark: SPY
|
|
exchange_kwargs:
|
|
codes: "{{ UNIVERSE }}"
|
|
deal_price: $close
|
|
freq: day
|
|
open_cost: 0.0005
|
|
close_cost: 0.0015
|
|
min_cost: 5.0
|
|
risk_analysis_freq: 1d
|