Open Access
MATEC Web Conf.
Volume 377, 2023
Curtin Global Campus Higher Degree by Research Colloquium (CGCHDRC 2022)
Article Number 02006
Number of page(s) 9
Section Social, Economic, and Health Transformations in a Post-Pandemic Future
Published online 17 April 2023
  1. Aslam, B. and Zhang, C. (2022). A strengthened solution to option manipulation. INFOR: Information Systems and Operational Research, 60(3):407–427. [CrossRef] [Google Scholar]
  2. Barberis, N. (2013). The psychology of tail events: progress and challenges. American Economic Review, 103(3):611–616. [CrossRef] [Google Scholar]
  3. Brealey, R. A., Myers, S. C., Allen, F., and Mohanty, P. (2020). Principles of corporate finance. Tata McGraw-Hill Education. [Google Scholar]
  4. Cao, J., Han, B., and Wang, Q. (2017). Institutional investment constraints and stock prices. Journal of Financial and Quantitative Analysis, 52(2):465–489. [CrossRef] [Google Scholar]
  5. Contessi, S. and De Pace, P. (2021). The international spread of covid-19 stock market collapses. Finance Research Letters, 42:101894. [CrossRef] [Google Scholar]
  6. Guerard, J. B., Markowitza, H., and Xu, G. (2020). Earnings forecasting in a global stock selection model and efficient portfolio construction and management. In Handbook of Applied Investment Research, pages 75–85. World Scientific. [CrossRef] [Google Scholar]
  7. Gupta, T. and Kelly, B. (2019). Factor momentum everywhere. The Journal of Portfolio Management, 45(3):13–36. [CrossRef] [Google Scholar]
  8. Hull, J. (2021). Machine Learning in Business: An Introduction to the World of Data Science. Indepen- dently Published. [Google Scholar]
  9. Klaas, J. (2019). Machine learning for finance: principles and practice for financial insiders. Packt Publishing Ltd. [Google Scholar]
  10. Marvin, K. (2015). Creating diversified portfolios using cluster analysis. Princeton University. [Google Scholar]
  11. Mondal, S. S., Mohanty, S. P., Harlander, B., Koseoglu, M., Rane, L., Romanov, K., Liu, W.-K., Hatwar, P., Salathe, M., and Byrum, J. (2019). Investment ranking challenge: Identifying the best performing stocks based on their semi-annual returns. [Google Scholar]
  12. Ndikum, P. (2020). Machine learning algorithms for financial asset price forecasting. arXiv preprint arXiv:2004.01504. [Google Scholar]
  13. Ren, Z. (2005). Portfolio construction using clustering methods. PhD thesis, Worcester Polytechnic Institute Worcester. [Google Scholar]
  14. Rozin, P. and Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and social psychology review, 5(4):296–320. [CrossRef] [Google Scholar]
  15. Soleymani, F. and Vasighi, M. (2022). Efficient portfolio construction by means of CVaR and k- means++ clustering analysis: Evidence from the NYSE. International Journal of Finance & Economics, 27(3):3679–3693. [CrossRef] [Google Scholar]
  16. Tan, Z., Yan, Z., and Zhu, G. (2019). Stock selection with random forest: An exploitation of excess return in the Chinese stock market. Heliyon, 5(8):e02310. [CrossRef] [Google Scholar]
  17. Wiest, T. (2022). Momentum: what do we know 30 years after Jegadeesh and Titman’s seminal paper? Financial Markets and Portfolio Management, pages 1–20. [Google Scholar]
  18. Wu, D., Wang, X., and Wu, S. (2022). Construction of stock portfolios based on k-means clustering of continuous trend features. Knowledge-Based Systems, 252:109358. [CrossRef] [Google Scholar]

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