Data Mining and Web Intelligence in Finance: Separating Facts from Fiction

Hong Kong is one of the five major financial centers in the world. She also plays the role as the financial gateway for China to attract investment from overseas. Similarly, Hong Kong is also a financial information hub of this region that financial information and data from various financial markets in Asia are collected and processed in Hong Kong before disseminated to those who need them. The financial information or data appeared in many formats, for example, texts, time series, figures, tables, charts, or even animated heat maps that help the professional investors or fund managers to identify arbitrage opportunities. Such information used to be stored in stand-alone machines. However, with the development of the Internet, wireless technologies, and pervasive computing, such data, information, and applications can be accessed from any where, any time, and with any devices.

The major objective of this panel is to sort through the real-world state-of-the-art data engineering techniques, for example, pattern recognition, knowledge discovery, knowledge management, data mining, customer relationship management (CRM) and information retrieval, that are being used for financial applications from the razzle-dazzle science fiction-like scenarios.

The panelists will consist experts from the academic and from the industry to cover a wide range of interest in financial data engineering. More specifically, we will focus on the advanced research issues, such as, novel techniques, methodologies, variations, etc., to support the solving of the practical or applied issues, for example, system scalability, availability, dependability, information integration, data handling and manipulation, as well as database management, etc. We will also discuss new research ideas in data warehousing and financial database Extraction, Transformation, and Loading (ETL), which has become extremely important to help the banks and other financial instituted to meet new requirements, such as, the Basel II Accord.

The target audience of the panel will be researchers, practitioners in the financial markets, chief technologists, IT managers, and others who are interested in learning pressing issues of data engineering and knowledge discovery in the financial community.

There will be 5 to 6 panelists in this panel.

• 10 mins. -- The moderator will introduce the topic and the format of the panel
• 10 mins. -- Each panelist will present their view following a specific question format using PowerPoint/Demo
• 30 mins -- Open discussion with questions from the audience

Professor Irwin King, CUHK

• Jiming Liu, HKBU
• Jerome Yang, CUHK
• Indranil Bose, HKU
• Joshua Huang, HKU

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