Evaluation of company investment value based on machine learning

Junfeng Hu, Xiaosa Li, Yuru Xu, Shaowu Wu and Bin Zheng

Papers from arXiv.org

Abstract: In this paper, company investment value evaluation models are established based on comprehensive company information. After data mining and extracting a set of 436 feature parameters, an optimal subset of features is obtained by dimension reduction through tree-based feature selection, followed by the 5-fold cross-validation using XGBoost and LightGBM models. The results show that the Root-Mean-Square Error (RMSE) reached 3.098 and 3.059, respectively. In order to further improve the stability and generalization capability, Bayesian Ridge Regression has been used to train a stacking model based on the XGBoost and LightGBM models. The corresponding RMSE is up to 3.047. Finally, the importance of different features to the LightGBM model is analysed.

Date: 2020-09
New Economics Papers: this item is included in nep-big and nep-cmp
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