Toward an on-demand option rating service for e-Business

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publicationProceedings - ICEBE 2007: IEEE International Conference on e-Business Engineering - Workshops: SOAIC 2007; SOSE 2007; SOKM 2007
Pages414-417
Publication statusPublished - 2007

Conference

TitleIEEE International Conference on e-Business Engineering (ICEBE 2007) ; IEEE International Workshop on Service-Oriented Applications, Integration and Collaboration (SOAIC 2007) ; IEEE International Workshop on Service-Oriented System Engineering (SOSE 2007) ; IEEE International Workshop on Service-Oriented Knowledge Management (SOKM 2007)
PlaceChina
CityHong Kong
Period24 - 26 October 2007

Abstract

With the fast-growing financial markets in Hong Kong and mainland China, corporate or individual investors have to make many important financial investment decisions on a daily basis. To make proper investment decisions, investors usually need to collect and analyze a huge amount of financial data beforehand. Nevertheless, human cognitive power is too limited to extract relevant information from the huge amount of raw data and to develop correct decisions in real-time. This paper illustrates the design and implementation of an open Web services based on-demand financial investment system which specializes in option trading. Corporate or individual Investors can subscribe to the aforementioned financial investment services so as to receive prompt advice for specific types of investment options. The proposed financial investment Web services can autonomously collect large amount of real-time data from various on-line sources and develop accurate predictions according to rigorous investment appraisal models. Based on a user profile, the system can provide personalized recommendation with reference to the specific risk-return trade-off of a subscriber. According to our empirical testing, the proposed option rating service can provide more accurate real-time predictions about the prices of options when compared with the online option calculator provided by a well-known financial investment company. © 2007 IEEE.

Research Area(s)

  • Black-scholes model, E-Business, Financial services, Option trading, Personalization, Web services

Citation Format(s)

Toward an on-demand option rating service for e-Business. / Lau, Raymond Y.K.; Wong, K. S.; Fung, K. F. et al.
Proceedings - ICEBE 2007: IEEE International Conference on e-Business Engineering - Workshops: SOAIC 2007; SOSE 2007; SOKM 2007. 2007. p. 414-417 4402127.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review