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This project studies the intrinsic relationship between the stocks’ multiple factors and the investment value of the stocks listed in China Securities Index 800 Index through the machine method. The investment system pipeline has been implemented including data acquirement, data preprocessing, model tuning and selection based on the XGBoost boosted tree model.

License: Mozilla Public License 2.0

Python 100.00%
machine-learning xgboost quantitative-finance quantitative-analysis quantitative-trading deep-learning

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stock-prediction-and-quantitative-analysis-based-on-machine-learning-method's Issues

有一个非常致命的错误如果使drop=TRUE,可能夸大回测时候的收益!!

非常感谢你的项目,写得非常好!有一点需要注意,当你在生成测试集的时候,使用drop,会使得最终生成交易列表的时候,夸大回测收益率,我经过测试,发现使用drop和不适用drop回测的时候,两者收益率差异非常大,原因也很简单,因为人为的过滤掉了一部分测试集。

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