Comparative Research of Investment Value of Three Technology Companies

Banghao Zhu

doi:10.62051/cg3r6t61

Authors

Banghao Zhu

DOI:

https://doi.org/10.62051/cg3r6t61

Keywords:

Stock; Technology; Risk; Profitability; Ratio.

Abstract

This article provides a detailed financial analysis of Intel, Northrop Grumman, and Qualcomm. The aim of this study is to gain insights into the effective investment strategies of these companies. The study included the analysis of the companies’ recent financial figures, such as exploring the meaning of various data, and exploring the asset selection challenges faced by four different investor types (including value, PEG, index, and momentum investors). By collecting, analyzing and comparing these data, this paper summarizes the trend of stock investment changes in the past and future. Leveraging established model, value investor tends to buy Intel, PEG investor will buy none of them, Index investor tend to buy Intel and Qualcomm, Momentum investor tends to buy NOC and Qualcomm. Furthermore, the insights gained from these analyses help develop tailored investment strategies, ultimately aiming to optimize financial gains in the technology sector and maximize returns on investment.

Downloads

Download data is not yet available.

References

[1] T. Irinamaria. A Genetic Algorithm (GA) Approach to the Portfolio Design Based on Market Movements and Asset Valuations. IEEE Access. 8 (2020).

[2] S. Lim, M. J. Kim, C. W. Ahn. A Genetic Algorithm (GA) Approach to the Portfolio Design Based on Market Movements and Asset Valuations. IEEE Access. 8 (2020).

[3] T. Irinamaria, T. An Analysis of Semiconductor Stocks as an Opportunity for Portfolio Diversification. Proceedings of the International Conference on Business Excellence. 17 (2023) 458–467.

[4] K. Ioannis, X. Dennis. AI Will Transform the Semiconductor Industry. Electronics Weekly. 2845 (2023) 20–21.

[5] T. Roh, J. Hwang, B. Park. M&A Successes: Breadth, Depth, and Deal Completion Time in the US Semiconductor Industry. BRQ Business Research Quarterly. 26 (2023) 297–312.

[6] K. Qi, X. R. Lin, Y. T. Zhang. National security, technological power and the US semiconductor domestic revival strategy. Diplomatic Review (Journal of China Foreign Affairs University). (2024) 1-25+165.

[7] X. Hu. Application of Moore’s Law in Semiconductor and Integrated Circuits Intelligent Manufacturing. IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA). (2022).964–968.

[8] T. W. Hall, K. A. Shriver. Econometric properties of asset valuation rules under price movement and measurement errors: An empirical test. Accounting Review. (1990) 537-556.

[9] H. Ni. Comparative Analysis of Three Semiconductor Technology Companies. Highlights in Business, Economics and Management. 24 (2024) 891-895.

[10] Y. H. Chou, Y. C. Jiang, S. Y. Kuo. Portfolio optimization in both long and short selling trading using trend ratios and quantum-inspired evolutionary algorithms. IEEE Access. 9 (2021) 152115-152130.