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- Financial markets (3)
- Financial innovation (2)
- Algorithmic trading (1)
- Artificial intelligence (1)
- Asian region (1)
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- Business Processes (1)
- Equity markets (1)
- Financial IS and technology (1)
- High-frequency trading (1)
- High-frequency trading (HFT) (1)
- Industry Ready (1)
- Integrated Curriculum (1)
- Learner Centered Learning (1)
- Learning Framework (1)
- Learning systems (1)
- Market transformation (1)
- Mean reversion (1)
- Moving average reversion (1)
- On-line learning (1)
- Online portfolios (1)
- Paths of influence (1)
- Portfolio selection (1)
- Technological innovation (1)
- Technology ecosystems (1)
- Technology-based innovation (1)
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Innovations In Financial Is And Technology Ecosystems: High-Frequency Trading Systems In The Equity Market, Robert J. Kauffman, Jun Liu, Dan Ma
Innovations In Financial Is And Technology Ecosystems: High-Frequency Trading Systems In The Equity Market, Robert J. Kauffman, Jun Liu, Dan Ma
Research Collection School Of Computing and Information Systems
Technology-based financial innovations over the past four decades have led to transformations in the financial markets. Understanding technological innovations in financial information systems (IS) and technologies has been challenging for technology consultants and financial industry practitioners due to the underlying complexities though. In this article, we propose an ecosystem analysis approach by extending the technology ecosystem paths of influence model (Adomavicius et al., 2008a) to incorporate stakeholder actions, considering both supply-side and demand-side forces for technological change. Our ecosystem model brings together three original core elements: technology components, technology-based services, and technology-supported business infrastructures. We also contribute a fourth new …
Learning Of Business Processes & Application: An Industry-Ready Approach, Yi Meng Lau, Yu Yee Poon, Mike Wee
Learning Of Business Processes & Application: An Industry-Ready Approach, Yi Meng Lau, Yu Yee Poon, Mike Wee
Research Collection School Of Computing and Information Systems
The Learning Framework for Business Processes was developed by lectures from School of InfoComm Technology (ICT)to support their students’ learning in the Diploma of Financial Informatics. This framework leverage on the use of learning approaches such as Inquiry based learning to create opportunities for students to be engaged, explore, explain and apply their learning. This framework was presented at International Symposium on Advances in Technology Education (ISATE) 2015 in Nagaoka, Japan.
Will High-Frequency Trading Practices Transform The Financial Markets In The Asia Pacific Region?, Robert John Kauffman, Yuzhou Hu, Dan Ma
Will High-Frequency Trading Practices Transform The Financial Markets In The Asia Pacific Region?, Robert John Kauffman, Yuzhou Hu, Dan Ma
Research Collection School Of Computing and Information Systems
High-frequency trading (HFT) practices in the global financial markets involve the use of information and communication technologies (ICT), especially the capabilities of high-speed networks, rapid computation, and algorithmic detection of changing information and prices that create opportunities for computers to effect low-latency trades that can be accomplished in milliseconds. HFT practices exist because a variety of new technologies have made them possible, and because financial market infrastructure capabilities have also been changing so rapidly. The U.S. markets, such as the National Association for Securities Dealers Automated Quote (NASDAQ) market and the New York Stock Exchange (NYSE), have maintained relevance and …
Moving Average Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Doyen Sahoo, Zhi-Yong Liu
Moving Average Reversion Strategy For On-Line Portfolio Selection, Bin Li, Steven C. H. Hoi, Doyen Sahoo, Zhi-Yong Liu
Research Collection School Of Computing and Information Systems
On-line portfolio selection, a fundamental problem in computational finance, has attracted increasing interest from artificial intelligence and machine learning communities in recent years. Empirical evidence shows that stock's high and low prices are temporary and stock prices are likely to follow the mean reversion phenomenon. While existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied, leading to poor performance in certain real datasets. To overcome this limitation, this article proposes a multiple-period mean reversion, or so-called "Moving Average Reversion" (MAR), and …
Semi-Universal Portfolios With Transaction Costs, Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C. H. Hoi
Semi-Universal Portfolios With Transaction Costs, Dingjiang Huang, Yan Zhu, Bin Li, Shuigeng Zhou, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Online portfolio selection (PS) has been extensively studied in artificial intelligence and machine learning communities in recent years. An important practical issue of online PS is transaction cost, which is unavoidable and nontrivial in real financial trading markets. Most existing strategies, such as universal portfolio (UP) based strategies, often rebalance their target portfolio vectors at every investment period, and thus the total transaction cost increases rapidly and the final cumulative wealth degrades severely. To overcome the limitation, in this paper we investigate new investment strategies that rebalances its portfolio only at some selected instants. Specifically, we design a novel on-line …