Concerns regarding the prevalence of manipulation of closing prices have prompted substantial changes to the mechanisms used to close trading at stock exchanges around the world. Nicholas Cordi USYD, CIFR / CMCRC Honours Scholarship Program 2014 Sean Foley USYD Keywords: Close price, Random Auction Ending, Manipulation Closing prices are important for, among others, benchmarking
Speaker: Bo Han (RedMarker/Kaplan Professional) Seminar Date: Tuesday November 28 12:00pm Brief abstract: Social media has become a gold mine of insights into the people, opinions and events. However, this massive amount of data also challenges the efficiency and effectiveness of existing machine learning algorithms. One way to approach this problem is “divide-and-conquer”. You can partition the data into
Speaker: Tom Osborn Seminar Date: Tuesday November 21 12:00pm Brief abstract: Active learning is a branch of semi-supervised machine learning for domains where data is expensive and where precise understanding is critical. Traditionally, active learning builds a model of a domain with a trade-off between exploration and exploitation probing of a domain to generate labelled data usefully. Earlier applications
Evidence from UK interest rate futures market reveals that traders have been “drowning” the market with oversized orders, increasing their allocation under a pure pro-rata matching algorithm. The 2007 introduction of a time element to the order matching mechanism has modified the behaviour of traders. No longer is the order book drowned with orders which
Speaker: Michael Sheng Seminar Date: Tuesday October 10 12:00pm Short Bio: Michael Sheng is a professor at Macquarie University, Sydney, since 1 January 2017. Dr. Michael Sheng was a full Professor and Deputy Head of the School of Computer Science at the University of Adelaide. Michael holds a PhD degree in computer science from the University of New South
Speaker: Tim Shaw Seminar Date: Tuesday September 26 12:00pm Short Bio: Tim is the inaugural Professor of eHealth and Director of Research in Implementation Science and eHealth Group (RISe) in the Faculty of Health Sciences at the University of Sydney. He is an internationally recognised leader in the impact of technology on healthcare and translation of evidence into practice
A new study by CMCRC researchers suggests that companies may be able to influence the level of algorithmic trading (AT) by adjusting their price level. The research shows that, stocks with lower relative tick size experience faster cancelation, deletion or trade times and higher order to trade ratios vis-à-vis firms with larger relative ticks. The
A new study by CMCRC researchers James Melouney and Dr. Matthew Clifton report that a trading strategy based on short-selling information can be used to develop several stock portfolios, achieving annual returns ranging from 0.2118% to 6.3015% after transaction costs. Short-selling refers to the selling of stocks one does not currently own and subsequently purchasing