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Transactions: INTERNATIONAL JOURNAL of COMPUTERS
Transactions ID Number: 19-444
Full Name: Shu Ling Lin
Position: Associate Professor
Age: ON
Sex: Female
Address: 1, Sec. 3, Chung-Hsiao E. Rd., Taipei, 10608, Taiwan, R.O.C.
Country: TAIWAN
Tel: 886-2-2771-2171 ext. 3426
Tel prefix: 886-2
Fax: 886-2-2776-3964
E-mail address: shuling@ntut.edu.tw
Other E-mails: shulingntut@gmail.com
Title of the Paper: an intelligent web-based gra/cointegration analysis for systematic risk
Authors as they appear in the Paper: shu ling lin, shun-jyh wu
Email addresses of all the authors: shuling@ntut.edu.tw, shulingntut@gmail.com, shundywu@gmail.com,shundy@mail.sju.edu.tw
Number of paper pages: 12
Abstract: A new intelligent web-based grey relational analysis (GRA)/cointegration analysis is proposed to examine the effects of cross-border bank M&As on the systematic risk that took place in the American, Asia, Europe, Africa and Middle East of banks in this paper. The potential diversification gains that arise from geographic or cross-border diversification are studied using a database that includes deals and bank stock return information for 114 cross-border M&As during 1998-2005. Cointegration analysis is first developed to obtain the relationship between financial variables and web-based GRA is then applied to establish the ranking and clustering of all acquirer events. The findings have important regulatory policy implications in that, the potential diversification gains have obtained in home country. Consequently, regulators in home countries may be less concerned with a rise in systematic risk following cross-border M&As, and no need to impose barriers to restrict!
the cross-border M&As activity. Grey relational analysis is demonstrated to be well developed to the clustering and ranking of cross-border M&As events. This study suggests that the proposed intelligent web-based GRA/cointegration analysis is effective and robust.
Keywords: Cross-border Mergers and Acquisitions (M&As), Cointegration, Grey relational analysis (GRA), Systematic risk.
EXTENSION of the file: .doc
Special (Invited) Session: an intelligent fuzzy/cointegration analysis for systematic risk
Organizer of the Session: 647-208
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