Academic believes solution will improve financial decisions, market returns
The use of artificial intelligence could improve investment banking by removing some key elements of human decisions.
The algorithm takes out chance, bias, and emotion from decisions and could mean fewer errors in financial decisions and improve financial returns in global markets.
It’s the brainchild of University of Bath researcher Dr Arman Hassanniakalager of the university’s School of Management.
“There is a global race to find a viable solution to create more reliable – and better performing - investment decisions in financial trading. Our model offers consistently higher returns compared to others developed to date,” he said..
Hassanniakalager boasts that his algorithm has shown to result in 3% higher return than the benchmark US Federal Reserve Funds rate, based on evidence from 12 stock market indices from around the globe. An improvement of 0.5-1.0% would typically be regarded as significant.
With the growth of digital investment solutions including robo-advisors, there is a race to find the ultimate model that can consistently outperform investment bankers and adapt to market volatility. This has proved elusive.
But Hassanniakalager says his model is outperforming both conventional investment techniques and algorithmic tools.
“There is a lot of theoretical thinking and aspirations around about such investment tools but the key question is solving how to make them work in the real world. We think we have addressed that question,” he said.
The algorithm can be linked to artificial intelligence, which will learn from investment decisions and fine-tune itself automatically. He envisages a black-box solution for investment managers who will be able to run complex alternative investment scenarios in real time.
“Whoever succeeds in this has the potential to transform financial markets and particularly investment banking and equities trading. There will be winners and losers - it isn’t hard to imagine the radical impact on employment at the highest banking levels if investment decisions are increasingly automated,” Hassanniakalager concludes.
NEWS: A University of Bath researcher from @BathSofM has created an algorithm which aims to remove the elements of chance, bias or emotion from #investment banking decisions. https://t.co/LbB51Q67Cn pic.twitter.com/TFwWae641j
— University of Bath (@UniofBath) June 12, 2019
