Proceedings of the International Conference on Advance Research in Social and Economic Science (ICARSE 2022)

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Trading Robots: Effective but Limited in Replacing Human Traders for Short-Term Investors

Authors
Sri Utami Ady1, *, Mustika Winedar1, Ilya Farida1, Dicken Okta Sandra Susena1, Fany Meyranda Putri1
1Economic and Business Faculty, Universitas Dr. Soetomo, Surabaya, Indonesia
*Corresponding author. Email: sri.utami@unitomo.ac.id
Corresponding Author
Sri Utami Ady
Available Online 27 April 2023.
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.

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Volume Title
Proceedings of the International Conference on Advance Research in Social and Economic Science (ICARSE 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
27 April 2023
ISBN
10.2991/978-2-38476-048-0_28
ISSN
2352-5398
DOI
10.2991/978-2-38476-048-0_28How to use a DOI?
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

risenwbib
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  -