Application Of Wavelet-ARMA-SVM Model In New Energy Power Battery Enterprise Value Evaluation

Focusing power battery industry,this paper found that through the analysis of the driving factors of the industry is in the period of rapid expansion of the scale of the industry enterprises,which depends on the scale expansion policy tilt,such as government subsidies and tax breaks,but because the industry is from the policy orientation to market orientation,its cash flows appear some volatility.In addition,such enterprises do not form a stable market demand,the imbalance of production capacity structure,policy bias driven capital influx,market competition intensified.High-tech enterprises,which are supported by technology,are faced with greater risk of replacement.At the same time,they should avoid environmental protection problems caused by enterprise expansion.If it goes against the original intention of the development of new energy industry,it may backfire on the development of enterprises.At the same time,the enterprise’s own research and development,inventory and other funds occupy a large,will also increase its financial risk.Therefore,under the influence of the above factors,the cash flow of power battery new energy enterprises is non-stationary,and the traditional linear cash flow prediction method has lost its function.Therefore,it is urgent to seek a prediction method for non-stationary cash flow.In this paper,by using the wavelet model through decomposition reconstruction of nonstationary cash flow of the enterprise to obtain its trend sequence,and detail coupled with smooth ARMA model and SVM model respectively for the details of the sequence and the trend of the nonstationary sequence multi-scale prediction,finally through the trend and detail sequences to predict the results of the integration of enterprise free cash flow forecast.By comparing and analyzing the cash flow forecast results of the case enterprise in 2019,it is found that the cash flow forecast results of the model used in this paper deviate from the actual value by-5.11%,while the traditional linear forecast method deviates from the actual value by-205.49%.Therefore,the model used in this paper has high reliability and applicability from the perspective of the degree of deviation.At the same time,the cash flow forecast results reveal that there is a certain cash flow pressure in the enterprise,so it is necessary to strengthen inventory turnover and accounts receivable management to ensure the stability of cash flow.This paper uses the earnings method to evaluate the value of the case enterprise,like the conclusion: from the perspective of earnings ratio,the current valuation of Yiwei lithium energy earnings ratio has not reached the market general expectation,the future should pay attention to the stability and sustainability of earnings.At the same time,we should be alert to the uncertainty of future earnings caused by industry risks,and judge the "valuation bubble" caused by the excessive enthusiasm of the market.In conclusion,by combining theoretical research with case analysis,this paper builds a wavelet-ARMA-SVM non-stationary cash flow prediction model to predict the cash flow of enterprises,and evaluates the case enterprises through the income method,providing a new idea for the valuation of power battery enterprises.