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Improved Financial Trading: Secure Data Systems Using Brain-Computer Interaction
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Author(s): Ashok Kumar Sahoo (Kalasalingam Academy of Research and Education, India), S. Gautami (Department of Management Studies, Sri Venkateswara College of Engineering, India), B. Venugopa (Indian Institute of Plantation Management, India), Vinod N. Alone (VPPCOE & VA, India), Pranjali Sharma (Shri Shankaracharya Institute of Professional Management and Technology, Raipur, India)and Ajay Bahadur (GNIOT Institute of Professional Studies, Greater Noida, India)
Copyright: 2025
Pages: 16
Source title:
Brain-Computer Interfaces and Applications in Business
Source Author(s)/Editor(s): Binay Kumar Pandey (Department of Information Technology, College of Technology, Govind Ballabh Pant University of Agriculture and Technology, India), A.Shaji George (TSM, Almarai Company, Saudi Arabia), Sameer Tiwari (George Mason University, USA), Salah A. Albermany (Kufa University, Iraq)and Ho Sy Hung (Hong Duc University, Vietnam)
DOI: 10.4018/979-8-3373-5122-3.ch006
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Abstract
Brain-Computer Interface (BCI) technology has the potential to revolutionize the decision-making processes and interactions of traders with markets when it is integrated into financial trading platforms. BCI technology allows traders to directly interact with financial software using brain impulses, thereby eliminating the necessity for traditional input devices. This is made possible by real-time neural feedback. By disclosing cognitive insights into trader behavior, emotions, and risk tolerance, this technique improves the speed and accuracy of decision-making. The implementation of adaptive trading methods in real time, optimization of risk management, and enhanced responses to volatile markets can all be facilitated by the use of BCI in trading. This paper investigates the potential of BCI to enhance financial trading systems, encompassing its benefits and drawbacks. Additionally, it accentuates the necessity of rigorous security protocols to prevent the exploitation or modification of neurological data and emphasizes the ethical implications.
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