зеркало из https://github.com/microsoft/qlib.git
c9ed050ef0
* Init model for both dataset * Remove some deprecated code * Add model template; * We must align with previous results * We choose another mode as the initial version * Almost success to run GRU * Successfully run training * Passed general_nn test * gru test * Alignment test passed * comment * fix readme & minor errors * general nn updates & benchmarks * Update examples/benchmarks/GeneralPtNN/workflow_config_gru2mlp.yaml --------- Co-authored-by: Young <afe.young@gmail.com> Co-authored-by: you-n-g <you-n-g@users.noreply.github.com> |
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| .. | ||
| benchmarks | ||
| benchmarks_dynamic | ||
| data_demo | ||
| highfreq | ||
| hyperparameter/LightGBM | ||
| model_interpreter | ||
| model_rolling | ||
| nested_decision_execution | ||
| online_srv | ||
| orderbook_data | ||
| portfolio | ||
| rl | ||
| rl_order_execution | ||
| rolling_process_data | ||
| tutorial | ||
| README.md | ||
| run_all_model.py | ||
| workflow_by_code.ipynb | ||
| workflow_by_code.py | ||
README.md
Requirements
Here is the minimal hardware requirements to run the workflow_by_code example.
- Memory: 16G
- Free Disk: 5G
NOTE
The results will slightly vary on different OSs(the variance of annualized return will be less than 2%).
The evaluation results in the README.md page are from Linux OS.