Open Access
| Issue |
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 | |
| DOI | https://doi.org/10.1051/matecconf/202337702006 | |
| Published online | 17 April 2023 | |
- 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]
- Barberis, N. (2013). The psychology of tail events: progress and challenges. American Economic Review, 103(3):611–616. [CrossRef] [Google Scholar]
- Brealey, R. A., Myers, S. C., Allen, F., and Mohanty, P. (2020). Principles of corporate finance. Tata McGraw-Hill Education. [Google Scholar]
- 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]
- Contessi, S. and De Pace, P. (2021). The international spread of covid-19 stock market collapses. Finance Research Letters, 42:101894. [CrossRef] [Google Scholar]
- 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]
- Gupta, T. and Kelly, B. (2019). Factor momentum everywhere. The Journal of Portfolio Management, 45(3):13–36. [CrossRef] [Google Scholar]
- Hull, J. (2021). Machine Learning in Business: An Introduction to the World of Data Science. Indepen- dently Published. [Google Scholar]
- Klaas, J. (2019). Machine learning for finance: principles and practice for financial insiders. Packt Publishing Ltd. [Google Scholar]
- Marvin, K. (2015). Creating diversified portfolios using cluster analysis. Princeton University. [Google Scholar]
- 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]
- Ndikum, P. (2020). Machine learning algorithms for financial asset price forecasting. arXiv preprint arXiv:2004.01504. [Google Scholar]
- Ren, Z. (2005). Portfolio construction using clustering methods. PhD thesis, Worcester Polytechnic Institute Worcester. [Google Scholar]
- 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]
- 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]
- 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]
- 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]
- 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]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.