Affiliation:
1. VIPS, Guru Gobind Singh Indraprastha University, India
2. Delhi University, India
Abstract
This chapter talks about how artificial intelligence has evolved into the minds of investors. Owing to the transformation in technology, machines have become increasingly capable. This will help to predict market movements using the behavioral aspect of the investors. There are also challenges in using AI in behavioral finance, such as the need for high-quality data, the potential for bias in AI algorithms themselves, and ethical considerations around using AI to make investment decisions. How these challenges will have an impact on investment decision-making is also discussed in this chapter. Further, the chapter talks about the interaction of behavioral finance and artificial intelligence and in turn enabling investors to be future-ready with fewer biases and efficient decision-making.
Reference62 articles.
1. Accenture. (2020). Retrieved from https://www.accenture.com/us-en/insights/capital-markets/wealth-management-artificial-intelligence
2. Editorial—Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research
3. Effect of Emotional Biases on Investor’s Decision Making in Nigeria
4. Effect of cognitive and emotional biases on investor decisions: An analytical study of the iraq stock exchange. International Journal of Innovation;N. S. H.Al-Dahan;Creativity and Change,2019
5. AN EMPIRICAL ANALYSIS OF BEHAVIORAL FINANCE IN THE SAUDI STOCK MARKET: EVIDENCE OF OVERCONFIDENCE BEHAVIOR