• DocumentCode
    2797223
  • Title

    A multi-factor decision-making model based on option games

  • Author

    Yu Dong-ping

  • Author_Institution
    Inst. of Nat. Defense Econ. & Manage., Central Univ. of Finance & Econ., Beijing, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    2252
  • Lastpage
    2257
  • Abstract
    This paper provides a framework of asymmetric duopoly option game and discusses the optimal strategy decision rules in corporate investment under the stochastic conditions of both product demand and operation cost which are correlative. We analyze especially the equilibrium rules of optimal strategy and its conditions and make comparative static analyses to the influence of each parameter to optimal thresholds after reducing investment value function and optimal investment threshold. The results show that the increase of uncertainty is not always to rise the optimal threshold when considering multi stochastic factors which are correlative. At last, some significant conclusions are made and explained, and the analytical result in theory is further verified and enriched by a numerical example, in which the influences of cost asymmetry, first mover advantage and correlation of stochastic factors to the optimal threshold and the equilibrium result are analyzed respectively and deeply.
  • Keywords
    decision making; game theory; investment; asymmetric duopoly option game; corporate investment; cost asymmetry; equilibrium rules; investment value function; multifactor decision-making model; optimal investment threshold; optimal strategy decision rules; stochastic condition; Cost function; Decision making; Finance; Financial management; Game theory; Investments; Stochastic processes; Uncertainty; Duopoly; Investment Decision; Option Games; Real Options;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5192680
  • Filename
    5192680