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release-0.5.0 (#1)
* init commit * change the version number * rich the docs&fix cache docs * update index readme * Modify cache class name * Modify sharpe to information_ratio * Modify Group- to Group * add the description of graphical results & fix the backtest docs * fix docs in details * update docs * Update introduction.rst * Update README.md * Update introduction.rst * Update introduction.rst * Update introduction.rst * Update installation.rst * Update installation.rst * Update initialization.rst * Update getdata.rst * Update integration.rst * Update initialization.rst * Update getdata.rst * Update estimator.rst Modify some typos. * Update README.md Modify the typos. * Update initialization.rst * Update data.rst * Update report.rst * Update estimator.rst * Update cumulative_return.py * Update model.rst * Update rank_label.py * Update cumulative_return.py * Update strategy.rst * Update getdata.rst * Update backtest.rst * Update integration.rst * Update getdata.rst * Update introduction.rst * Update introduction.rst * Update README.md * Update report.rst * Update integration.rst Fix typos * Update installation.rst Fix typos * Update getdata.rst * Update initialization.rst Fix typos. * add quick start docs&fix detials * fix estimator docs & fix strategy docs * fix the cahce in data.rst * update documents * Fix Corr && Rsquare * fix data retrival example to csi300 & fix a data bug * fix filter bug * Fix data collector * Modift model args * add the log & fix README.md\quick.rst * add enviroment depend & add intoduction of qlib-server online mode * fix image center fomat & set log_only of docs is True * fix README.md format * update data preparation & readme logo image * get_data support version * Modify analysis names * Modify analysis graph * update report.rst & data.rst * commmit estimator for merge * minimal requirements * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Update READEME.md * Update READEME.md * update estimator * Fix doc urls * fix get_data.py docstring * update test_get_data.py * Upate docs * Upate docs * Upate docs Co-authored-by: bxdd <bxddream@gmail.com> Co-authored-by: zhupr <zhu.pengrong@foxmail.com> Co-authored-by: Wendi Li <wendili.academic@qq.com> Co-authored-by: Dingsu Wang <dingsu.wang@gmail.com> Co-authored-by: bxdd <45119470+bxdd@users.noreply.github.com> Co-authored-by: cslwqxx <cslwqxx@users.noreply.github.com>
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@@ -185,10 +185,10 @@ This part needs contain these fields:
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optim_type: max
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- `report_type`
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The type of the report, str type, determines which kind of report you want to use. If you want to use the backtest result type, you can choose `pred_long`, `pred_long_short`, `pred_short`, `sub_bench` and `sub_cost`. If you want to use the model result type, you can only choose `model`.
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The type of the report, str type, determines which kind of report you want to use. If you want to use the backtest result type, you can choose `pred_long`, `pred_long_short`, `pred_short`, `excess_return_without_cost` and `excess_return_with_cost`. If you want to use the model result type, you can only choose `model`.
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- `report_factor`
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The factor you want to use in the report, str type, determines which factor you want to optimize. If your `report_type` is backtest result type, you can choose `annual`, `sharpe`, `mdd`, `mean` and `std`. If your `report_type` is model result type, you can choose `model_score` and `model_pearsonr`.
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The factor you want to use in the report, str type, determines which factor you want to optimize. If your `report_type` is backtest result type, you can choose `annualized_return`, `information_ratio`, `max_drawdown`, `mean` and `std`. If your `report_type` is model result type, you can choose `model_score` and `model_pearsonr`.
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- `optim_type`
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The optimization type, str type, determines what kind of optimization you want to do. you can minimize the factor or maximize the factor, so you can choose `max`, `min` or `correlation` at this field.
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