Trading Robots: Effective but Limited in Replacing Human Traders for Short-Term Investors
- DOI
- 10.2991/978-2-38476-048-0_28How to use a DOI?
- Keywords
- Phenomenology; automatic trading; investor behavior; qualitative; psychological bias
- Abstract
This study aimed to explore how stock investors have responded to the adoption of trading robots in the capital market, particularly during the Covid-19 pandemic, and to investigate the efficacy of these robots in trading. A qualitative phenomenological approach was used to investigate investor behavior from an emic perspective. The study used in-depth interviews, observation, and content analysis to gain a comprehensive understanding of the phenomenon. The results suggest that trading robots are preferred by short-term investors who frequently trade in the market. The automation of trading effectively reduces fear and greed, allowing for more efficient decision-making. However, there are situations where trading robots are unable to replace human functions in the market. The implications of this study are that trading robots can be effective in reducing risks and maximizing returns for short-term investors, but they should not be viewed as a complete substitute for human traders.
- 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 - Sri Utami Ady AU - Mustika Winedar AU - Ilya Farida AU - Dicken Okta Sandra Susena AU - Fany Meyranda Putri PY - 2023 DA - 2023/04/27 TI - Trading Robots: Effective but Limited in Replacing Human Traders for Short-Term Investors BT - Proceedings of the International Conference on Advance Research in Social and Economic Science (ICARSE 2022) PB - Atlantis Press SP - 248 EP - 254 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-048-0_28 DO - 10.2991/978-2-38476-048-0_28 ID - Ady2023 ER -