• DocumentCode
    523676
  • Title

    Allocation Model Construction and Empirical Research on Incremental Economic Capital of Credit Operations

  • Author

    Houqing Fang ; Jianmin He ; Li Shen

  • Author_Institution
    Sch. of Econ. & Manage., Southeast Univ., Nanjing, China
  • Volume
    1
  • fYear
    2010
  • fDate
    11-12 May 2010
  • Firstpage
    449
  • Lastpage
    452
  • Abstract
    According to current commercial bank management requirements of credit risk, this paper studies the optimization allocation model of incremental economic capital of credit businesses in commercial bank. It has the objective function of Economic Value Added (EVA) and the restrictive conditions of hurdle rate, risk adjusted return on capital (RAROC), available economic capital gross, degree of concentration and speeding-up limitation of risk exposure in credit businesses portfolio and so on. To solve shareholder´s value creation of the economic capital optimization problem, then incremental economic capital allocation model of credit operations is built up. Empirical studies have shown that the method of genetic algorithm optimization tool to solve the allocation model is scientific and feasible.
  • Keywords
    banking; economics; genetic algorithms; risk management; allocation model construction; commercial bank management requirements; credit operations; credit risk; economic capital gross; economic capital optimization problem; economic value added; empirical research; genetic algorithm optimization tool; incremental economic capital allocation model; optimization allocation model; risk adjusted return on capital; Automation; Business; Conference management; Costs; Genetic algorithms; Helium; Optimization methods; Portfolios; Risk management; Technology management; EVA; RAROC; economic capital; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-7279-6
  • Electronic_ISBN
    978-1-4244-7280-2
  • Type

    conf

  • DOI
    10.1109/ICICTA.2010.742
  • Filename
    5522798