Unleashing the Power of Multi-Agent Reinforcement Learning for Algorithmic Trading in the Digital Financial Frontier and Enterprise Information Systems

被引：3

作者：

Sarin, Saket ^{[1
]}

Singh, Sunil K. ^{[1
]}

Kumar, Sudhakar ^{[1
]}

Goyal, Shivam ^{[1
]}

Gupta, Brij Bhooshan ^{[2
,3
,4
,8
]}

Alhalabi, Wadee ^{[5
]}

Arya, Varsha ^{[6
,7
]}

机构：

[1] Chandigarh Coll Engn & Technol, Chandigarh 160019, India

[2] Asia Univ, Dept Comp Sci & Informat Engn, Taichung 413, Taiwan

[3] Symbiosis Int Univ, Symbiosis Ctr Informat Technol SCIT, Pune 411057, India

[4] Univ Petr & Energy Studies UPES, Ctr Interdisciplinary Res, Dehra Dun 248007, India

[5] King Abdulaziz Univ, Dept Comp Sci, Immers Virtual Real Res Grp, Jeddah 21589, Saudi Arabia

[6] Asia Univ, Dept Business Adm, Taichung 413, Taiwan

[7] Lebanese Amer Univ, Dept Elect & Comp Engn, Beirut 11022801, Lebanon

[8] Chandigarh Univ, UCRD, Chandigarh 140413, India

来源：

CMC-COMPUTERS MATERIALS & CONTINUA | 2024年 / 80卷 / 02期

关键词：

Neurodynamic; Fintech; multi-agent reinforcement learning; algorithmic trading; digital financial frontier;

D O I：

10.32604/cmc.2024.051599

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the rapidly evolving landscape of today's digital economy, Financial Technology (Fintech) emerges as a trans- formative force, propelled by the dynamic synergy between Artificial Intelligence (AI) and Algorithmic Trading. Our in-depth investigation delves into the intricacies of merging Multi-Agent Reinforcement Learning (MARL) and Explainable AI (XAI) within Fintech, aiming to refine Algorithmic Trading strategies. Through meticulous examination, we uncover the nuanced interactions of AI-driven agents as they collaborate and compete within the financial realm, employing sophisticated deep learning techniques to enhance the clarity and adaptability of trading decisions. These AI-infused Fintech platforms harness collective intelligence to unearth trends, mitigate risks, and provide tailored financial guidance, fostering benefits for individuals and enterprises navigating the digital landscape. Our research holds the potential to revolutionize finance, opening doors to fresh avenues for investment and asset management in the digital age. Additionally, our statistical evaluation yields encouraging results, with metrics such as Accuracy = 0.85, Precision = 0.88, and F1 Score = 0.86, reaffirming the efficacy of our approach within Fintech and emphasizing its reliability and innovative prowess.

引用

页码：3123 / 3138

页数：16

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