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Research on the Tencent Company Stock Price Based on ARIMA Model
- 1 Louisiana State University
- 2 University of Houston
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Abstract
This paper presents a comprehensive analysis of Tencent Holdings Limited's stock performance over the past five years. This paper explores the multifaceted factors influencing stock price volatility, including economic indicators, regulatory changes, industry developments, and technological innovations. Employing an ARIMA (0,1,0) model, this paper assesses the time series data of Tencent's stock price and scrutinize model adequacy through various statistical tests. Results suggest that the constant term in the ARIMA model may not be statistically significant, which emphasizing the need for a nuanced approach to stock price modeling. Predictive values for a 12-phase forecast reveal a declining trend in Tencent's stock price. The root-mean-square deviation (RMSD) is computed to gauge prediction accuracy. Additionally, the residual Lagrange multiplier correlation finds no significant correlation between residuals and independent variables. This analysis underscores the complexity of stock price determination and advocates for a holistic approach, consider both numerical analysis and qualitative factors. Investors are advised to maintain a long-term perspective when evaluating Tencent's market potential.
Keywords
Tencent holdings, stock price analysis, ARIMA model, volatility factors, market forecasting
[1]. Ji, X. (2022) Valuation of Tencent Holdings. Repositorio.
[2]. Che, J. (2018) Investment Analysis about China’s IT Company-The Tencent Holdings Limited. Modern Economy, 09(06), 1112–1120.
[3]. Sharma, A. K., et al. (2021) A study of trends and industrial prospects of Industry 4.0. Materials Today: Proceedings, 47.
[4]. Fu, T. (2019) China’s personal information protection in a data-driven economy: A privacy policy study of Alibaba, Baidu and Tencent. Global Media and Communication, 15(2).
[5]. Cui, J., Yan, C., Ng, A. and Hong, H. (2022) Tencent’s Corporate Strategic Organizational Digital Management and Digital Transformation: A case study. Journal of business and social sciences, 2.
[6]. Wang, Y. (2023) Impact of Tencent equity incentive on enterprise expected growth ability (Dissertation). Working paper.
[7]. Kurihara, Y. (2021) What Influences on Stock Prices Have Occurred Due to the U.S.- China Trade Dispute? Journal of Economics & Management Research, 2(3), 1–5.
[8]. Liu, H.B., and Yi, D.Y. (2007) A stock price prediction method based on wavelet analysis and fractal theory Statistics and Decision Making, 110-111.
[9]. Li, D., Su, X.H. and Ma, S.Y. (2003) A stock price prediction algorithm based on the new dimensional grey Markov model Journal of Harbin Institute of Technology, 35 (2), 5.
[10]. Yuan, D. (2009) Research on stock price prediction model based on dynamic neural network. Doctoral dissertation, Hunan University.
Cite this article
Sun,L.;Yuan,H. (2023). Research on the Tencent Company Stock Price Based on ARIMA Model. Advances in Economics, Management and Political Sciences,64,263-268.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
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