Valuation Prediction Of China's Electrwc Power Listed Enterprises

Electric power industry is one of the pillar industries of China's national economy.With the continuous change of economic situation,China's electric power industry is currently in a period of adjustment,and the growth rate is slowing down.Faced with the new situation,how to correctly judge and evaluate the actual value of Listed Companies in the power industry is particularly important.Firstly,the background and significance of this topic are elaborated.The facts show that the reasonable valuation of Listed Companies in power industry can provide decision-making reference for investors,managers and decision-makers.Based on the foreign modern enterprise value theory,this paper systematically summarizes the research status at home and abroad.Starting from the macroeconomic environment,industrial policy and the characteristics of the power industry,this paper studies the relevant factors affecting the valuation of the power industry,and preliminarily understands the valuation objects at the macro and micro levels.In the process of valuation and capital market development,EVA economic value-added model is selected to analyze the fundamentals of Datang Electric Power Company.Considering that the support vector machine has good modeling theory,there is no need to systematically explore the mathematical model.Based on the data fitting,the principle of structural risk minimization is applied and the training efficiency is excellent.In this paper,the combination of daily opening stock and information granulation of power listed companies is predicted and discriminated by regression.At the same time,the theory of support vector machine and information granulation is summarized in depth,and three parameter optimization algorithms,genetic algorithm,particle swarm optimization and grid search algorithm,are constructed to optimize the kernel function for the original data,and the data regression effect is compared and normalized.After that,the stock regression prediction of Datang Electric Power Company is carried out by using the Fuzzy Granulation Support Vector Machine Model.The forecasting results show that the model has good forecasting results for the listed electric power companies.This paper also uses the trapezoidal interval two-type fuzzy system to deepen the forecasting results and achieve better forecasting results.This paper can provide policy makers and strategic executives with better forecasting results.Effective data support and predictive valuation provide important theoretical basis for strategic adjustment of enterprises and for China's power industry to enter overseas.