Nav: Home

Algorithm to transform investment banking with higher returns

June 12, 2019

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, 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.

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 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," Hassanniakalager 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.

The primary use would be in trading rooms, in particular in the technical analysis field, assessing how stock markets react to company news or in gauging the performance of derivative instruments and offering different investment paths to managers.

The tool will change the decision-making process and potentially the market landscape itself - the days of multiple screens in trading rooms and managers seeking to make sense of an increasingly complex multitude of real-time and historic data may be numbered.

There may even be a question mark over the future of decision-makers themselves.

"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 says.

The algorithm, which Hassanniakalager describes as universal, may have applications beyond financial markets. "If you learn what is changing statistically, you can apply that to other fields, such as genetics. That's the beauty of statistics," he says.

Hassanniakalager will present the findings of the research team, which includes academics from the Universities of Glasgow and St Andrews, on Friday 14 June at the FMA International conference at the University of Strathclyde.
-end-
Media contacts and resources

* For further information or to arrange interviews with Arman Hassanniakalager please contact Tony Roddam or Alison Jones at the University of Bath press office via press@bath.ac.uk or on +44 (0)1225 386319

The School of Management is one of the UK's leading business schools, the school is ranked first for Marketing, 2nd for Business and Management Studies and 6th for Accounting and Finance (the Complete University Guide 2020). It is a leading centre for management research, placed 8th in the UK in the latest research evaluation exercise.

The University of Bath is one of the UK's leading universities both in terms of research and our reputation for excellence in teaching, learning and graduate prospects.The University is rated Gold in the Teaching Excellence Framework (TEF), the Government's assessment of teaching quality in universities, meaning its teaching is of the highest quality in the UK.

In the Research Excellence Framework (REF) 2014 research assessment 87 per cent of our research was defined as 'world-leading' or 'internationally excellent'. From developing fuel efficient cars of the future, to identifying infectious diseases more quickly, or working to improve the lives of female farmers in West Africa, research from Bath is making a difference around the world. Find out more: http://www.bath.ac.uk/research/

Well established as a nurturing environment for enterprising minds, Bath is ranked highly in all national league tables. We are ranked 6th in the UK by The Guardian University Guide 2019, 5th for graduate employment in The Times & Sunday Times Good University Guide 2019, and 9th out of 131 UK universities in the Complete University Guide 2020.

University of Bath

Related Algorithm Articles:

Scientists use algorithm to peer through opaque brains
A new algorithm helps scientists record the activity of individual neurons within a volume of brain tissue.
Algorithm generates origami folding patterns for any shape
A new algorithm generates practical paper-folding patterns to produce any 3-D structure.
New algorithm tracks neurons in bendy brain of freely crawling worm
Scientists at Princeton University have developed a new algorithm to track neurons in the brain of the worm Caenorhabditis elegans while it crawls.
Does my algorithm work? There's no shortcut for community detection
Community detection is an important tool for scientists studying networks, but a new paper published in Science Advances calls into question the common practice of using metadata for ground truth validation.
'Cyclops' algorithm spots daily rhythms in cells
Humans, like virtually all other complex organisms on Earth, have adapted to their planet's 24-hour cycle of sunlight and darkness.
An algorithm that knows when you'll get bored with your favorite mobile game
Researchers from the Tokyo-based company Silicon Studio, led by Spanish data scientist África Periáñez, have developed a new algorithm that predicts when a user will leave a mobile game.
Algorithm identified Trump as 'not-married'
Scientists from Russia and Singapore created an algorithm that predicts user marital status with 86% precision using data from three social networks instead of one.
A novel positioning algorithm based on self-adaptive algorithm
Much attention has been paid to the Taylor series expansion (TSE) method these years, which has been extensively used for solving nonlinear equations for its good robustness and accuracy of positioning.
Algorithm can create a bridge between Clinton and Trump supporters
The article that received the best student-paper award in the Tenth International Conference on Web Search and Data Mining (WSDM 2017) builds algorithmic techniques to mitigate the rising polarization by connecting people with opposing views -- and evaluates them on Twitter.
Deep learning algorithm does as well as dermatologists in identifying skin cancer
In hopes of creating better access to medical care, Stanford researchers have trained an algorithm to diagnose skin cancer.

Related Algorithm Reading:

Best Science Podcasts 2019

We have hand picked the best science podcasts for 2019. Sit back and enjoy new science podcasts updated daily from your favorite science news services and scientists.
Now Playing: TED Radio Hour

Climate Crisis
There's no greater threat to humanity than climate change. What can we do to stop the worst consequences? This hour, TED speakers explore how we can save our planet and whether we can do it in time. Guests include climate activist Greta Thunberg, chemical engineer Jennifer Wilcox, research scientist Sean Davis, food innovator Bruce Friedrich, and psychologist Per Espen Stoknes.
Now Playing: Science for the People

#527 Honey I CRISPR'd the Kids
This week we're coming to you from Awesome Con in Washington, D.C. There, host Bethany Brookshire led a panel of three amazing guests to talk about the promise and perils of CRISPR, and what happens now that CRISPR babies have (maybe?) been born. Featuring science writer Tina Saey, molecular biologist Anne Simon, and bioethicist Alan Regenberg. A Nobel Prize winner argues banning CRISPR babies won’t work Geneticists push for a 5-year global ban on gene-edited babies A CRISPR spin-off causes unintended typos in DNA News of the first gene-edited babies ignited a firestorm The researcher who created CRISPR twins defends...