Financial Forecasting With Multivariate Adaptive Regression Splines And Queen Genetic Algorithm-Support Vector Regression
IEEE Access(2019)
摘要
In consideration of the financial indicators of financial structure, solvency, operating ability, profitability, and cash flow as well as the non-financial indicators of firm size and corporate governance, the algorithms of multivariate adaptive regression splines (MARS) and queen genetic algorithm-support vector regression (QGA-SVR) are used in this study to create a comprehensive financial forecast of operating revenue, earnings per share, free cash flow, and net working capital to help enterprises forecast their future financial situation and offer investors and creditors a reference for investment decision-making. This study's objectives are achieved through the following steps: (i) establishment of feature indicators for financial forecasting, (ii) development of a financial forecasting method, and (iii) demonstration of the proposed method and comparison with existing methods.
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关键词
Financial forecasting,multivariate adaptive regression splines (MARS),queen genetic algorithm (QGA),support vector regression (SVR)
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