• 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