Document Type
Call for Paper
Abstract
This study employs meta-analysis, rich pictures, timeline analysis, and causal loop diagram to explore the sustainability impacts of the SARSA-FIS hybrid method in forex trading robots. It reviews 56 references (2018-2023), using rich pictures to map AI-driven interactions. Timeline analysis traces AI’s evolution in forex, while causal loop diagram clarifies its role in market dynamics. Responsible algorithms and SRI principles mitigate risks, promoting ethical trading. SARSA-FIS enhances strategies, leveraging AI for sustainable forex practices amidst global uncertainties. The research identifies gaps and positions SARSA-FIS as a novel approach, providing a foundation for advancing AI applications in finance, particularly in forex trading.
Recommended Citation
Fat, Joni; Moengin, Parwadi; Astuti, Pudji; and Cahyati, Sally
(2025)
"Sustainability in Forex Trading: a Review in Search of The SARSA-FIS Hybrid Method as a Novelty,"
Bulletin of Monetary Economics and Banking: Vol. 28:
No.
0, Article 6.
DOI: https://doi.org/10.59091/2460-9196.2369
Available at:
https://bulletin.bmeb-bi.org/bmeb/vol28/iss0/6
First Page
71
Last Page
94
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Country
Indonesia
Affiliation
Universitas Trisakti
Included in
Finance and Financial Management Commons, Management Information Systems Commons, Management Sciences and Quantitative Methods Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Risk Analysis Commons, Technology and Innovation Commons