Abstract

In recent years, new energy vehicles have become one of the mainstream trends in the global auto market. By analyzing the valuation of the stock price of the new energy automobile industry, the actual value of its stock can be found, thus providing a specific reference for investors. Based on this, this paper investigates the fluctuation of daily average stock prices using the HP-ARIMA method, and performs predictive analysis, robustness test and heterogeneity analysis on the given data. After separating the short-term fluctuations and long-term trends of daily average stock prices based on the HP filtering method, the predictions were made by the ARIMA model. The predicted results were tested for robustness by OLS regression and Tobit model, respectively, and the following findings were obtained: (1) Through the analysis of HP filtering method, the cyclical fluctuation of the stock price of the new energy automobile industry is relatively large, and upstream enterprises affect the middle and downstream enterprises to a certain extent. (2) The prediction analysis by ARIMA shows that the prediction accuracy of upstream enterprises' share prices is relatively high, and the prediction results have good robustness. (3) The regression analysis shows that the fit is good for upstream and downstream enterprises, and the change trend shows a positive correlation, while the midstream enterprises show the opposite trend.

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