• DocumentCode
    2853230
  • Title

    Examining the Uncertainty-Investment Relationship under Alternative Stochastic Processes

  • Author

    Wang, George Y.

  • Author_Institution
    Dept. of Int. Bus., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan
  • fYear
    2010
  • fDate
    13-15 Aug. 2010
  • Firstpage
    369
  • Lastpage
    375
  • Abstract
    This paper argues that increased uncertainty, in certain situations, may actually encourage investment. Since earlier studies mostly base their arguments on the assumption of geometric Brownian motion, the study extends the assumption to a mean-reverting process. A general approach of Monte Carlo simulation is developed to derive optimal investment trigger for the situation that the closed-form solution could not be readily obtained under the assumption of alternative process. The main finding is that the overall effect of uncertainty on investment is interpreted by the probability of investing, and the relationship appears to be an invested U-shaped curve between uncertainty and investment. The implication is that uncertainty does not always discourage investment even under several sources of uncertainty. Furthermore, high-risk projects are not always dominated by low-risk projects because the high-risk projects may have a positive realization effect on encouraging investment.
  • Keywords
    Monte Carlo methods; investment; stochastic processes; uncertainty handling; Monte Carlo simulation; alternative stochastic processes; geometric Brownian motion; high risk projects; mean reverting process; optimal investment trigger; uncertainty investment relationship; Computational modeling; Equations; Investments; Mathematical model; Monte Carlo methods; Stochastic processes; Uncertainty; geometric Brownian motion; investment; mean-reverting process; real options; uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Business Intelligence and Financial Engineering (BIFE), 2010 Third International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-7575-9
  • Type

    conf

  • DOI
    10.1109/BIFE.2010.92
  • Filename
    5621821