Stock price prediction for new energy vehicle enterprises: An integrated method based on time series and cloud models

Wang, Meng-xian; Xiao, Zhi; Peng, Hong-gang; Wang, Xiaokang; Wang, Jianqiang

doi:10.1016/j.eswa.2022.118125

Cited by 20 publications

(6 citation statements)

References 45 publications

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“…The authors tried to integrate the time series and cloud models to seek a new method to predict the stock price. As the mainstream that new energy vehicles will replace fuel vehicles, the article provided suggestions for investors to build a portfolio from the aspect of future stock price [9]. Zeng et al gave an analysis of the NEV market in China.…”

Section: Related Researchmentioning

confidence: 99%

Application of WACC in Automobile Enterprises

Tan

2023

AEMPS

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With the global promotion of energy conservation and emission reduction in recent years, some new energy vehicle enterprises are emerging in the market. To avoid potential risks in the new energy vehicle market with over-investment, the paper selects Tesla, BYD, and Toyota as examples, and uses CAPM and WACC to calculate and analyze the risks of three automobile enterprises based on the financial data in 2022. The result shows that Tesla owned the largest WACC and risks due to the calculation, and Toyota had the smallest WACC and risks. According to the analysis of data combined with the market situation of three companies, the author finds unique risks for each enterprise and provides a feasible direction for the development of three enterprises. It shows that the development of electric vehicles, guarantee of production, good product quality, and reasonable allocation of funds can help automobile enterprises avoid risks in the future.

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Section: Related Researchmentioning

confidence: 99%

Application of WACC in Automobile Enterprises

Tan

2023

AEMPS

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“…Environmental protection and energy security have drawn increasing attention as a result of the fast expansion of global economy. The new energy vehicle (NEV) is a powerful tool for easing the world's energy crisis, increasing energy efficiency, and lowering environmental pollution [10]. Current research has covered a wide range of NEV-related topics in depth.…”

Section: Introductionmentioning

confidence: 99%

“…Current research has covered a wide range of NEV-related topics in depth. However, Wang et al stated that there has not been much research on NEV enterprise stock price prediction, which is crucial for NEV enterprise equity financing, risk assessment, and policy formation [10].…”

Section: Introductionmentioning

confidence: 99%

Momentum Strategy Performances in New Energy Vehicle Industry

Zhou¹

2023

BCPBM

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The automotive industry is now actively working toward the strategic goal of developing new energy vehicles (NEVs). As a common strategy, momentum strategy is suitable for variation stocks. On this basis, this article focuses on new energy vehicle stocks and explores some variations of the current momentum strategies. This article provides proof that the momentum strategy exists in a certain stock. The sensitivity of the strategy return to stock market volatility will vary with varied lengths of lookback periods. The affected Sharpe ratio of the strategy shows that the transaction cost has some impact on the return of the momentum approach. Given that fossil fuels are being replaced by new energy sources today, research into NEV manufacturers is worthwhile. The significance of this research is providing a greater understanding of momentum strategy and investigating its feature in real data. These results shed light on guiding further exploration of implementations and applications of momentum strategy.

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“…Compared with the conventional model predictive control, the degradation cost of the battery is reduced by 4.2%. Wang [ 22 ] proposed a prediction model combining time series and cloud models to perform stock price prediction for new energy car companies. This approach is validated using the stock prices of new energy vehicle companies as an example.…”

Section: Introductionmentioning

confidence: 99%

Research on Multistate Variable Prediction of a Master‐Slave Electric‐Hydraulic Hybrid Vehicle Based on CNN‐LSTM Model with Attention Mechanism

Chen,

Zhang,

Zhang

et al. 2023

Energy Tech

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This paper utilizes a convolutional neural network and long short‐term memory with attention mechanism (CLA) prediction model for time series forecasting. An innovative master‐slave electric‐hydraulic hybrid vehicle (MSEHV) is introduced. It simplifies the drivetrain structure by utilizing planetary gears for energy transfer and coupling to transform electrical, mechanical, and hydraulic energy. This paper conducts simulation verification using existing control strategies. It combines the velocity time series information with the hydraulic accumulator pressure time series information to create a unified time series. Some of the more popular machine learning and neural network algorithms are considered, and the mean square error, mean absolute error, and coefficient of determination evaluation metrics are calculated for validation. The research presents a developed battery state of charge regression prediction model based on genetic algorithm‐backpropagation by combining the predicted results of composite time series with the current discharge depth of the battery. The validation results indicate that the CLA time series prediction model proposed in this paper for MSEHV has higher prediction accuracy compared to other prediction models.

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Stock price prediction for new energy vehicle enterprises: An integrated method based on time series and cloud models

Cited by 20 publications

References 45 publications

Application of WACC in Automobile Enterprises

Application of WACC in Automobile Enterprises

Momentum Strategy Performances in New Energy Vehicle Industry

Research on Multistate Variable Prediction of a Master‐Slave Electric‐Hydraulic Hybrid Vehicle Based on CNN‐LSTM Model with Attention Mechanism

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