start experiment 58 (exp/58-signal-quality-gate-5-year-walk-forward)

This commit is contained in:
zhaoli
2026-08-20 23:24:38 +00:00
parent fd5382caa4
commit e952feed0a
43 changed files with 2887 additions and 0 deletions
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#!/usr/bin/env python3
"""Precompute the signal-quality gate series and save to pickle.
Usage:
python precompute_signal_quality_gate.py <pred_path> <output_path> [topk] [lookback] [threshold]
Example:
python precompute_signal_quality_gate.py \
/home/data/lake/mlruns/49/34165f27e4a34378ad54843a079a78c0/artifacts/pred.pkl \
/app/experiments/book/data/signal_quality_gate/sq_gate_5d_0.50.pkl \
10 5 0.5
"""
import sys
import pickle
from pathlib import Path
# Add tac-qlib to path
sys.path.insert(0, "/app/tac-qlib")
from tac_qlib.contrib.strategy.signal_quality_gate import compute_signal_quality_gate
if __name__ == "__main__":
if len(sys.argv) < 3:
print(__doc__)
sys.exit(1)
pred_path = sys.argv[1]
output_path = sys.argv[2]
topk = int(sys.argv[3]) if len(sys.argv) > 3 else 10
lookback = int(sys.argv[4]) if len(sys.argv) > 4 else 5
threshold = float(sys.argv[5]) if len(sys.argv) > 5 else 0.5
lake_root = "/home/data/lake"
print(f"Computing signal-quality gate: topk={topk}, lookback={lookback}, threshold={threshold}")
gate = compute_signal_quality_gate(
pred_path,
lake_root=lake_root,
topk=topk,
lookback=lookback,
threshold=threshold,
)
print(f"Gate: {gate.sum()}/{len(gate)} days open ({gate.mean():.1%})")
with open(output_path, "wb") as f:
pickle.dump(gate, f)
print(f"Saved to {output_path}")
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# -----------------------------------------------------------------------------
# Signal-quality gate: TopkDropout gated by rolling hit-rate of topk picks.
#
# 1. Compute the gate: python precompute_signal_quality_gate.py <pred.pkl> <gate.pkl>
# 2. Run this workflow: rd_run_workflow config_path=<this yaml> experiment_name=<exp>
#
# The strategy loads the precomputed gate from signal_quality_gate_path.
# When hit rate >= threshold, trade; otherwise, go to cash.
# -----------------------------------------------------------------------------
{%- 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" %}
{%- set GATE_PATH = "/app/experiments/book/data/signal_quality_gate/sq_gate_5d_0.50.pkl" %}
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-sq-gate"
task:
model:
class: LGBModel
module_path: qlib.contrib.model.gbdt
kwargs:
loss: mse
learning_rate: 0.05
num_leaves: 15
n_estimators: 200
colsample_bytree: 0.8
subsample: 0.8
subsample_freq: 1
reg_alpha: 0.01
reg_lambda: 0.01
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: SignalQualityGateStrategy
module_path: tac_qlib.contrib.strategy.signal_quality_gate
kwargs:
signal: "<PRED>"
signal_quality_gate_path: "{{ GATE_PATH }}"
topk: 10
n_drop: 1
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
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# Signal-quality gate backtest for 2021
{%- 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" %}
{%- set GATE_PATH = "/app/experiments/book/data/signal_quality_gate/sq_gate_2021.pkl" %}
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-sq-gate-2021"
task:
model:
class: LGBModel
module_path: qlib.contrib.model.gbdt
kwargs:
loss: mse
learning_rate: 0.05
num_leaves: 15
n_estimators: 200
colsample_bytree: 0.8
subsample: 0.8
subsample_freq: 1
reg_alpha: 0.01
reg_lambda: 0.01
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: 2021-12-31
fit_start_time: 2015-01-03
fit_end_time: 2021-01-03
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, 2020-09-01]
valid: [2020-09-03, 2021-01-03]
test: [2021-01-04, 2021-12-31]
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: SignalQualityGateStrategy
module_path: tac_qlib.contrib.strategy.signal_quality_gate
kwargs:
signal: "<PRED>"
signal_quality_gate_path: "{{ GATE_PATH }}"
topk: 10
n_drop: 1
only_tradable: true
risk_degree: 0.95
backtest:
start_time: 2021-01-04
end_time: 2021-12-31
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
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# Signal-quality gate backtest for 2023
{%- 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" %}
{%- set GATE_PATH = "/app/experiments/book/data/signal_quality_gate/sq_gate_2023.pkl" %}
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-sq-gate-2023"
task:
model:
class: LGBModel
module_path: qlib.contrib.model.gbdt
kwargs:
loss: mse
learning_rate: 0.05
num_leaves: 15
n_estimators: 200
colsample_bytree: 0.8
subsample: 0.8
subsample_freq: 1
reg_alpha: 0.01
reg_lambda: 0.01
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: 2023-12-29
fit_start_time: 2015-01-03
fit_end_time: 2023-01-03
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, 2022-09-01]
valid: [2022-09-03, 2023-01-03]
test: [2023-01-03, 2023-12-29]
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: SignalQualityGateStrategy
module_path: tac_qlib.contrib.strategy.signal_quality_gate
kwargs:
signal: "<PRED>"
signal_quality_gate_path: "{{ GATE_PATH }}"
topk: 10
n_drop: 1
only_tradable: true
risk_degree: 0.95
backtest:
start_time: 2023-01-03
end_time: 2023-12-29
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
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# Signal-quality gate backtest for 2024
{%- 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" %}
{%- set GATE_PATH = "/app/experiments/book/data/signal_quality_gate/sq_gate_2024.pkl" %}
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-sq-gate-2024"
task:
model:
class: LGBModel
module_path: qlib.contrib.model.gbdt
kwargs:
loss: mse
learning_rate: 0.05
num_leaves: 15
n_estimators: 200
colsample_bytree: 0.8
subsample: 0.8
subsample_freq: 1
reg_alpha: 0.01
reg_lambda: 0.01
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: 2024-12-31
fit_start_time: 2015-01-03
fit_end_time: 2024-01-03
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, 2023-09-01]
valid: [2023-09-03, 2024-01-03]
test: [2024-01-02, 2024-12-31]
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: SignalQualityGateStrategy
module_path: tac_qlib.contrib.strategy.signal_quality_gate
kwargs:
signal: "<PRED>"
signal_quality_gate_path: "{{ GATE_PATH }}"
topk: 10
n_drop: 1
only_tradable: true
risk_degree: 0.95
backtest:
start_time: 2024-01-02
end_time: 2024-12-31
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
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# Signal-quality gate backtest for 2025
{%- 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" %}
{%- set GATE_PATH = "/app/experiments/book/data/signal_quality_gate/sq_gate_2025.pkl" %}
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-sq-gate-2025"
task:
model:
class: LGBModel
module_path: qlib.contrib.model.gbdt
kwargs:
loss: mse
learning_rate: 0.05
num_leaves: 15
n_estimators: 200
colsample_bytree: 0.8
subsample: 0.8
subsample_freq: 1
reg_alpha: 0.01
reg_lambda: 0.01
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: 2025-12-31
fit_start_time: 2015-01-03
fit_end_time: 2026-01-03
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: [2025-01-02, 2025-12-31]
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: SignalQualityGateStrategy
module_path: tac_qlib.contrib.strategy.signal_quality_gate
kwargs:
signal: "<PRED>"
signal_quality_gate_path: "{{ GATE_PATH }}"
topk: 10
n_drop: 1
only_tradable: true
risk_degree: 0.95
backtest:
start_time: 2025-01-02
end_time: 2025-12-31
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
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# Signal-quality gate backtest for 2026
{%- 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" %}
{%- set GATE_PATH = "/app/experiments/book/data/signal_quality_gate/sq_gate_2026.pkl" %}
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-sq-gate-2026"
task:
model:
class: LGBModel
module_path: qlib.contrib.model.gbdt
kwargs:
loss: mse
learning_rate: 0.05
num_leaves: 15
n_estimators: 200
colsample_bytree: 0.8
subsample: 0.8
subsample_freq: 1
reg_alpha: 0.01
reg_lambda: 0.01
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: 2026-01-03
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: SignalQualityGateStrategy
module_path: tac_qlib.contrib.strategy.signal_quality_gate
kwargs:
signal: "<PRED>"
signal_quality_gate_path: "{{ GATE_PATH }}"
topk: 10
n_drop: 1
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