DocumentCode
2913644
Title
Research on multi-attribute auction based on rough set in non-performing asset disposal
Author
An-Shi, Xie ; Li-huang, Huang ; Zhong-de, Chen
Author_Institution
Fudan Univ., Shanghai
fYear
2007
fDate
18-20 Nov. 2007
Firstpage
910
Lastpage
914
Abstract
The major role of Asset Management Corporation (AMC) is to purchase, manage and dispose of non-performing loans (NPLs) acquired from financial institutions. The company´s operational goal is to preserve the asset value and maximize the recovery value. Asset management corporation (AMC) will adapt suitable measures to specific conditions in NPLs and collateral disposition. Those measures include sale, exchange, restructuring, debt-equity swap, securitization and auction. Auction is the most popular one. But most auction processes are concerned with the price, among which the making process is the only attribute in the decision. It is necessary to study multi-attributes auction in which we conduct auction with more attributes. But the traditional methods have obvious shortcomings. So many attributes lead to heaven work burden and the individual factors affect the allocation of attribute. This paper firstly presents an approach based on rough sets to solve the problem of attribute reduction and setting weight in multi-attributes decision making of asset disposal.
Keywords
decision making; decision theory; financial management; operations research; rough set theory; Asset Management Corporation; collateral disposition; financial institution; multiattribute auction process; multiattribute decision making; nonperforming asset disposal; nonperforming loan purchasing; rough set theory; Asset management; Conference management; Decision making; Financial management; Game theory; Intelligent systems; Internet; Marketing and sales; Rough sets; Waste management;
fLanguage
English
Publisher
ieee
Conference_Titel
Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-1294-5
Electronic_ISBN
978-1-4244-1294-5
Type
conf
DOI
10.1109/GSIS.2007.4443405
Filename
4443405
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