The Impact of 5G-Relevant Factors on the Stock of Media Industry Based on Multivariate Regression
- DOI
- 10.2991/978-94-6463-030-5_78How to use a DOI?
- Keywords
- 5G Industry; Stock Prediction; Multivariate Regression
- Abstract
Contemporarily, the 5G technology is rapidly, and the media industry (e.g., Tiktok and micro-blog software) are growing rapidly and playing an increasingly important role in society. Intrinsically, the media and 5G technology industries might have a strong correlation with each other in stock market. On this basis, we analyze the time-series data of the corresponding underlying assets to investigate the relationship in deep. Based on the regression analysis, there is a positive correlation between the income impact of 5G network sector stocks and media sector stocks. To quantitively explore and analyze the situation of the media sector in the stock market, multivariate regression models are constructed. According to the statistical metrics, the factors will greatly affect the stock price and can be used to improve the performance of the corresponding models. Overall, these results shed light on stock price prediction of media industry in terms of the 5G relevant information.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Hongbin Shi AU - Xiaoyang Yuan PY - 2022 DA - 2022/12/20 TI - The Impact of 5G-Relevant Factors on the Stock of Media Industry Based on Multivariate Regression BT - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022) PB - Atlantis Press SP - 791 EP - 799 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-030-5_78 DO - 10.2991/978-94-6463-030-5_78 ID - Shi2022 ER -