122 lines
4.2 KiB
YAML
122 lines
4.2 KiB
YAML
# -----------------------------------------------------------------------------
|
|
# Run 94736d89 (exp-4 tac-rd-tune2) follow-up -- single lever: WIDER UNIVERSE.
|
|
#
|
|
# Baseline (run 94736d89): 10 correlated tech/growth names -> weak cross-section
|
|
# (IC 0.038 / ICIR 0.10), topk=5 book all-correlated, 295 trades / 152d and
|
|
# $58k cost drag (5.8% of $1M) -> excess ann -18.8% vs QQQ.
|
|
#
|
|
# This run holds EVERYTHING else fixed (windows, 5-day label, LGB hyperparams,
|
|
# topk=5/n_drop=2, benchmark QQQ) and only widens the universe 10 -> 17 with the
|
|
# full lake set, adding genuinely uncorrelated assets (BIL cash, USO oil, SLV
|
|
# silver, VXX vol, KTEC/QQQE/GPIQ factor sleeves) to de-correlate the cross-section,
|
|
# stabilize the top-5 ranking and cut the churn/cost drag.
|
|
# -----------------------------------------------------------------------------
|
|
{%- 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:///mlruns.db"
|
|
default_exp_name: "tac-rd-tune3"
|
|
|
|
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,BIL,GPIQ,KTEC,QQQE,SLV,USO,VXX
|
|
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,BIL,GPIQ,KTEC,QQQE,SLV,USO,VXX
|
|
deal_price: $close
|
|
freq: day
|
|
open_cost: 0.0005
|
|
close_cost: 0.0015
|
|
min_cost: 5.0
|
|
risk_analysis_freq: 1d
|