Z-Score Model Financial Prediction for Listed Companies Based on Improved FOA Algorithm
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    Abstract:

    In order to improve the prediction ability of the traditional Z-Score financial prediction model, this paper proposes a financial prediction model of Z-Score for listed companies based on improved Fruit fly Optimization Algorithm (FOA) by combining the good searching ability of improved FOA algorithm and the Z-Score financial prediction model. The Root Mean Square Error (RMSE) between the predicted value and target value is reduced by improved FOA algorithm being applied to optimize the parameters of Z-Score model. We compare the predicted value and target value of the financial data of listed companies to test the accuracy of financial prediction. The experimental results are as follows:accuracies of the traditional Z-Score financial prediction model, FOA algorithm optimized Z-Score model, and improved FOA algorithm optimized Z-Score model are 65%, 70%, and 80%, respectively. Experiments show that the improved algorithm significantly improves the predictive ability of Z-Score financial prediction model, it is also illustrated the validity of the algorithm.

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康彩红,王秋萍,肖燕婷.基于改进FOA算法的上市公司Z-Score模型财务预警.计算机系统应用,2018,27(11):198-204

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  • Received:April 03,2018
  • Revised:April 24,2018
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  • Online: October 24,2018
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