The Role of Artificial Intelligence in Optimizing Investment Portfolios and Predicting Market Trends

Abstract

This paper delves into two pivotal AI applications on Wall Street, City Road, Threadneedle Street, and beyond investment portfolio optimization and predicting future market conditions. We elucidate the theoretical foundations of each, backed by a survey of pertinent current academic literature. We then delve into the limitations of AI in finance and pose some potential avenues for future research. Our focus is on the underlying theories rather than the technical intricacies of AI, such as the machine learning models used to implement these methods. A key takeaway from this paper is the promising potential of AI in finance. While we acknowledge that most applications of these technologies do not yet surpass 'traditional' methodologies, we believe that AI could revolutionize the finance industry with further research and development.

It is a well-established trend for significant financial service players to invest heavily in artificial intelligence (AI) systems. Companies like Alibaba and Ant Financial in China, Atom Bank and Revolut in the UK, and Wealthfront and Betterment in the US are leading the way. The 'basics' of AI and other data-driven technologies, such as machine learning, are being used to automate customer services before expanding into risk and compliance. In fact, according to Boston Consulting, the financial services sector is leading the charge in AI adoption, recognizing that advanced analytics can significantly boost profits.