Hong Kong, Hong Kong S.A.R., September 08, 2017 --(PR.com
)-- The Award Presentation Ceremony (the “Ceremony”) of the First Computational Finance Competition (the “Competition”) jointly organized by Hong Kong based Global eSolutions (HK) Limited (“GES”), a leading financial trading platform provider, and the IEEE (Hong Kong) Computational Intelligence Chapter (IEEE (HK) CI Chapter) successfully took place on 26 August, 2017 at the Lecture Theatre A, Chow Yei Ching Building, the University of Hong Kong. Apart from the award presentation, the organizer invited several guests to deliver a speech, including Professor Edward P.K. Tsang, the School of Computer Science & Electronic Engineering, University of Essex and Mr. Ken So, Senior Quantitative Developer of GES, who shared their research and insights on computational finance and algo trading. Eminent figures in the academic sector and notable guests supported the event and exchanged the ideas of computation finance and algo trading.
Since the Competition was held by GES and IEEE (HK) CI Chapter for the first time this year, it aims to foster the pursuit of algo trading among university students. The Competition has received an overwhelming response of entries, with more than 60 participants in 35 teams. Awarded teams in the Ceremony come from various academic departments, ranging from Electrical and Electronic Engineering, Computer Science and Computer Engineering. A total of 9 awards were presented, the winners include both undergraduate and postgraduate from (name listed in no particular order) The Department of Electrical and Electronic Engineering, the University of Hong Kong; The Department of Computer Science, the University of Hong Kong; The Department of Computer Science, Hong Kong Baptist University; and The Department of Electronic & Computer Engineering, Hong Kong University of Science and Technology.
At the Ceremony, Dr. Vincent Tam, Chairman of IEEE (HK) CI Chapter, said, “Thanks to the keen supports of the Executive Committee members of the IEEE (HK) CI Chapter, and the Computational Finance and Economics Technical Committee (CFETC) of the Computational Intelligence Society (CIS), the Competition has been successfully launched and has received overwhelming response so far. The Competition is certainly one of the most meaningful investment competitions in the academic sector, allowing students to put investment theories into practice and gain the valuable experience of trading simulation in the real investment world.”
Mr. Ken Chung, Director of GES, said, “Although Hong Kong is known to be an international financial hub, its development and application of innovative technology such as algo trading and artificial intelligence in the financial industry still falls behind the capital markets in Europe and the United States. One significant advantage of algo trading is automation, which leads to a relatively rational trading behavior. Any pre-setting trading strategies can be automatically executed in specified time, price and trading volume through computer, avoiding irrational decisions made by manual trading. Auton serves as a virtual trading platform in this Competition and is a truly multi-asset platform which supports FX, Bullion, CFDs, Equities, Futures and Stock Options. Its built-in algo trading kit allows traders to deploy existing trading strategies or script their own one in the platform. By allowing algo backtesting and forward-testing with historical data and live data respectively, Auton helps traders to develop the unique trading strategy that will work best for them.
About the First Computational Finance Competition
This first Computational Finance Competition was organized by GES and IEEE (Hong Kong) Computational Intelligence Chapter (“IEEE (HK) CI Chapter”), which invited undergraduates and postgraduates students from renowned universities in Hong Kong to foster the pursuit of algo trading among university students in Hong Kong. It was initiated with a vision to promote the use of Computational Intelligence in the area of finance, identify algo trading talents at top universities and provide top performers with potential career opportunities.