143 lines
4.7 KiB
YAML
143 lines
4.7 KiB
YAML
# QUEUE-rt
|
||
# Long-short (Q09): long top-10 / short bottom-10 equal-weight, market-neutral construction.
|
||
# Acceptance: net_IR > 0.21 AND net_ann > +2.13% AND total_cost within ~2× reference; SPY beta ~ 0 sanity.
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
{%- 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 FEATURES = "$open,$high,$low,$close,$vwap,$volume,sp_ret,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-q09-longshort"
|
||
|
||
task:
|
||
model:
|
||
class: RankICEnsembleLGBModel
|
||
module_path: tac_qlib.contrib.model.rank_ensemble
|
||
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
|
||
seeds: "42,7,2026,99,123"
|
||
parallel: 5
|
||
|
||
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: 2016-01-04
|
||
fit_end_time: 2025-09-01
|
||
freq: day
|
||
lake_root: "{{ LAKE }}"
|
||
market: US
|
||
label: "Ref($close,-6)/Ref($close,-1)-1"
|
||
feature_fields: "{{ FEATURES }}"
|
||
infer_processors:
|
||
- class: DropAllNaN
|
||
kwargs: {}
|
||
- class: ProcessInf
|
||
kwargs: {}
|
||
- class: CSRankNorm
|
||
kwargs: {}
|
||
- class: ZScoreNorm
|
||
kwargs: {}
|
||
- class: Fillna
|
||
kwargs: {}
|
||
segments:
|
||
train: [2016-01-04, 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: TopBottomDropoutStrategy
|
||
module_path: tac_qlib.contrib.strategy.top_bottom
|
||
kwargs:
|
||
signal: "<PRED>"
|
||
topk: 10
|
||
short_leg: true
|
||
rebalance_daily: 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 |