DocumentCode
481709
Title
An Improved Model of Executive Stock Option Based on Rough Set and Support Vector Machines
Author
Jia, Zhengyuan ; Han, Jia
Author_Institution
Bus. & Manage. Dept., North China Electr. Power Univ., Baoding
Volume
1
fYear
2008
fDate
19-20 Dec. 2008
Firstpage
256
Lastpage
261
Abstract
This paper shows that share price could be confirmed accurately by the assessment model of stock price based on rough set (RS) and support vector machines (SVM). This model can remove the impact of "bull" and "bear" market and avoid controlling share price from executives effectively at the exercising date. According to the case analysis, the model is proved to be more exercisable, and it paves the way for actualizing executive stock option (ESO) in listed company.
Keywords
pricing; rough set theory; share prices; support vector machines; executive stock option; rough set; share price; stock price; support vector machines; Computational intelligence; Computer industry; Conferences; Decision making; Energy management; Large-scale systems; Neural networks; Share prices; Support vector machine classification; Support vector machines; Executive Stock Option; Rough set; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3490-9
Type
conf
DOI
10.1109/PACIIA.2008.160
Filename
4756563
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