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A University of Bath researcher has created an algorithm which aims to remove the elements of chance, bias or emotion from investment banking decisions, a development which has the potential to reduce errors in financial decision making and improve financial returns in global markets.
"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," says Dr. Arman Hassanniakalager of the university's School of Management.
Hassanniakalager - Research - Financial - Management - Association
Hassanniakalager, who will present the research at the Financial Management Association conference in Glasgow this week, says his model has been shown to result in a 3% higher return than the benchmark U.S. Federal Reserve Funds rate, based on evidence from 12 stock market indices from around the globe. An improvement of 0.5-1.0% would be regarded as significant.
The search for an all-powerful investment algorithm has stepped up in recent years and early results have been mixed. The challenge is to create a level of reliability that consistently outperforms investment bankers and financiers and a tool that can function equally well in rising and falling markets.
Development - Algorithms - Benefits - Hopes - Optimism
The continued development of algorithms and their perceived benefits are raising hopes and optimism among many in the markets. But the increasing reliance on the tools has also created some nervousness in the top tiers of the world's financial systems—and some scepticism from those who believe there will always be a role for the inspired human touch.
Hassanniakalager, whose expertise is in developing novel artificial intelligence and statistical methods for financial decision making, said his algorithm has reached the point where it is consistently outperforming both conventional methods of investment and...
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