Forecasting Business Profitability by Using Multiple Regression Analysis and Back-propagation Neural Network
| Autor: | Liu, Hsing-Cheng, 劉信成 |
|---|---|
| Rok vydání: | 2018 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 Profitability is the ability of a company to increase its financial value. Profitability analysis is the relationship between the company's profits and the available assets, capital and resources. The general profitability analysis includes operating income, operating costs, operating profit and loss, post-tax profit and loss, and the ratio analysis of various profit and loss items. In addition, it often analyzes various investment returns, such as net profit after tax, earnings per share, return on assets, the rate of return on equity, etc., is a measure of the overall business performance of a company. In this study, using data to establish profitability prediction model by 104 companies in 7 industries, including Taiwan's listed semiconductors, optoelectronics, electronic zero-resistance devices, communications networks, steel, plastics, and chemical industries, were investigated and 1074 of them were disclosed in the process of profitability in the industry from 2003 to 2016. Firstly, a multiple stepwise regression analysis and correlation coefficient were used to make a selection of variables, to understand the variables that had significant influence, and to predict the relationship between corporate investment and profitability using the back-propagation neural network model. Finally, the validity of the model established by the actual verification of the three major industrial cement, rubber, and the food industry was selected. Then, the sensitivity of the output variables is analyzed on each input variable to determine the degree of influence of the input variables on the output variables. The results of this study showed that 879 training materials and 195 test data from 104 companies in 7 major industries were used to perform neural network supervised learning. There were good prediction results for different industry categories, and the company's operating margins and research and development were invested. Expenses, promotional fees, and management fees had a significant impact on the after-tax net profit and return on assets. Keywords: Profitability, Multiple stepwise regression, Correlation coefficient, Back-propagation neural network, Sensitivity analysis |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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