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Trading

Saïd Business School launches online Algorithmic Trading Programme
Saïd Business School launches online Algorithmic Trading Programme

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Algorithmic, or systematic, trading is gaining momentum as funds benefit from market efficiencies and performance of investments improve. With algorithmic trading estimated to account for 20% of hedge funds, traders are looking to understand how to engage with funds and manage for risk.

Recognising these emerging trends Saïd Business School, University of Oxford has launched the Oxford Algorithmic Trading Programme, the first of its kind worldwide.

It will provide an understanding of the rules that drive successful algorithmic trading strategies and give participants the ability to decide whether a fund is worth investing in.

Programme Convener Nir Vulkan, Associate Professor of Business Economics at Oxford Saïd commented: ‘Algorithmic trading is a significant part of hedge fund management and it is growing in share and size. If you’re starting in this industry or planning to stay in it, now is the time to educate yourself on algorithmic trading.

‘This is an area where technology, big data and finance collide. There hasn’t been a course of this nature before, that combines different disciplines. It’s relevant now more than ever, because of the increase of automation and because systematic funds have been gaining more momentum and becoming more popular, while AI and machine learning are getting better.’

The programme will be delivered online over 6 weeks giving finance professionals a thorough understanding of the behavioural finance theory that identifies patterns in human behaviour that can be replicated by algorithms. ‘Good traders follow good rules. The next logical step is to keep the rules but remove human bias and emotions completely from decisions, making algo funds potentially stronger,’ said Vulkan.

The programme will explore the history of trading, how to engage and evaluate systems trading, and enable participants to get their hands dirty and see how a simple trading model is built. Alongside Professor Vulkan, programme participants will hear from a variety of industry professionals, including Martin Leuck, Director of Research, Aspect Capital; Matthew Sargaison, co-CEO, MAN AHL; Susi Gorbey, Director of Quantitative Strategies Oversight, Tudor Capital Europe; Euan Kirk, CIO GAM Systematic; and Steve Mobbs, Partner, Oxford Asset Management, as well as academics leading research in the field.

Peter Tufano, Peter Moores Dean at Saïd Business School, commented: ‘Research suggests that some professional careers might be challenged as technology rapidly transforms markets, institutions, and business models. Supported by our partner GetSmarter, our suite of online programmes that includes fintech, blockchain strategy, and now algorithmic trading, will help entrepreneurs and executives future-proof their careers as they navigate the changing landscape.’

The programme comes after a British financial watchdog recently urged algorithmic trading firms to tighten controls. The British Financial Conduct Authority report warned ‘firms need to do more work to identify and reduce potential conduct risks created by their algorithmic trading strategies.’

The report continued ‘some firms lacked a suitable process to identify algorithmic trading across their business and did not have appropriate documentation in place to demonstrate suitable development and testing procedures are maintained.’

The online programme will begin on 25 July 2018, and will run for 6 weeks.

Uma Rajagopal has been managing the posting of content for multiple platforms since 2021, including Global Banking & Finance Review, Asset Digest, Biz Dispatch, Blockchain Tribune, Business Express, Brands Journal, Companies Digest, Economy Standard, Entrepreneur Tribune, Finance Digest, Fintech Herald, Global Islamic Finance Magazine, International Releases, Online World News, Luxury Adviser, Palmbay Herald, Startup Observer, Technology Dispatch, Trading Herald, and Wealth Tribune. Her role ensures that content is published accurately and efficiently across these diverse publications.

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