1
0
mirror of https://github.com/microsoft/qlib.git synced 2026-06-06 05:51:17 +08:00
Files
qlib/examples/benchmarks/KRNN/workflow_config_krnn_Alpha360.yaml
yaxuan999 efffb2819a added KRNN and Sandwich models and their example results based on Alpha360 (#1414)
* Update README.md

updated the result of KRNN and Sandwich models based on Alpha360

* Update README.md

* Update README.md

* Add files via upload

* Update README.md

* Update README.md

* Update README.md

* Add files via upload

* Delete pytorch_krnn.py

* Delete pytorch_sandwich.py

* Add files via upload

* Update pytorch_sandwich.py

* Update pytorch_krnn.py

* Update pytorch_sandwich.py

* Update pytorch_krnn.py

* Update README.md

* Update README.md

* Update requirements.txt

* Update requirements.txt

* Update README.md

* Update README.md

* Update pytorch_sandwich.py

* Update link on index

---------

Co-authored-by: Young <afe.young@gmail.com>
2023-05-26 18:42:58 +08:00

92 lines
2.5 KiB
YAML

qlib_init:
provider_uri: "~/.qlib/qlib_data/cn_data"
region: cn
market: &market csi300
benchmark: &benchmark SH000300
data_handler_config: &data_handler_config
start_time: 2008-01-01
end_time: 2020-08-01
fit_start_time: 2008-01-01
fit_end_time: 2014-12-31
instruments: *market
infer_processors:
- class: RobustZScoreNorm
kwargs:
fields_group: feature
clip_outlier: true
- class: Fillna
kwargs:
fields_group: feature
learn_processors:
- class: DropnaLabel
- class: CSRankNorm
kwargs:
fields_group: label
label: ["Ref($close, -2) / Ref($close, -1) - 1"]
port_analysis_config: &port_analysis_config
strategy:
class: TopkDropoutStrategy
module_path: qlib.contrib.strategy
kwargs:
signal:
- <MODEL>
- <DATASET>
topk: 50
n_drop: 5
backtest:
start_time: 2017-01-01
end_time: 2020-08-01
account: 100000000
benchmark: *benchmark
exchange_kwargs:
limit_threshold: 0.095
deal_price: close
open_cost: 0.0005
close_cost: 0.0015
min_cost: 5
task:
model:
class: KRNN
module_path: qlib.contrib.model.pytorch_krnn
kwargs:
fea_dim: 6
cnn_dim: 8
cnn_kernel_size: 3
rnn_dim: 8
rnn_dups: 2
rnn_layers: 2
n_epochs: 200
lr: 0.001
early_stop: 20
batch_size: 2000
metric: loss
GPU: 0
dataset:
class: DatasetH
module_path: qlib.data.dataset
kwargs:
handler:
class: Alpha360
module_path: qlib.contrib.data.handler
kwargs: *data_handler_config
segments:
train: [2008-01-01, 2014-12-31]
valid: [2015-01-01, 2016-12-31]
test: [2017-01-01, 2020-08-01]
record:
- class: SignalRecord
module_path: qlib.workflow.record_temp
kwargs:
model: <MODEL>
dataset: <DATASET>
- class: SigAnaRecord
module_path: qlib.workflow.record_temp
kwargs:
ana_long_short: False
ann_scaler: 252
- class: PortAnaRecord
module_path: qlib.workflow.record_temp
kwargs:
config: *port_analysis_config