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Analysis of Risk and Uncertainty Using Monte Carlo Simulation and its Influence on Project Realization

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  • GORAN KARANOVIC

    (University of Rijeka, Faculty of Tourism and Hospitality Management, Croatia)

  • BISERA GJOSEVSKA

    (Balkan Institute for Behavioral Research, Skopje, Macedonia)

Abstract

This paper examines the impact of risk and uncertainty on the the capital budgeting process in the modern business environment. The turbulent business surroundings, as well as the rapid technological, informational, and societal progress and scientific development add to the complexity of modern-day decision making, by exerting significant influence on the growing uncertainty during the capital budgeting process. A summary of the most common sources of risk and uncertainty in the capital budgeting process is given, as well as an overview of the most represented methods for the evaluation of financial efficiency in the capital budgeting procedure. The determination and quantification of risk and uncertainty regarding key variables is of paramount importance to the analysis in question, as is their influence on the distribution of the resulting values of the methods of evaluating capital budgeting. Exceptional attention in this paper has been given to the comparison and contrast of distribution of values procured from the use of the methods for the determination and quantification of risk and uncertainty. In the following case study — the decision regarding the construction of a hotel — the use of the Monte Carlo simulation method has been shown in the process of determining the probability distribution of net present value, as well as the forecasting of cash flows. The given example shows, through analysis and observation, the most important issues and advantages arising from the use of the Monte Carlo method as well as the shortcomings in the use of this model in business practice.

Suggested Citation

  • Goran Karanovic & Bisera Gjosevska, 2012. "Analysis of Risk and Uncertainty Using Monte Carlo Simulation and its Influence on Project Realization," Annals - Economic and Administrative Series -, Faculty of Business and Administration, University of Bucharest, vol. 6(1), pages 145-162, December.
  • Handle: RePEc:but:anneas:v:6:y:2012:i:1:p:145-162
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    References listed on IDEAS

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    1. Schall, Lawrence D & Sundem, Gary L & Geijsbeek, William R, Jr, 1978. "Survey and Analysis of Capital Budgeting Methods," Journal of Finance, American Finance Association, vol. 33(1), pages 281-287, March.
    2. Maged Ali & Ramzi El-Haddadeh & Tillal Eldabi & Ebrahim Mansour, 2010. "Simulation discounted cash flow valuation for internet companies," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 6(1), pages 18-33.
    3. Martin Hoesli & Elion Jani & André Bender, 2005. "Monte Carlo Simulations for Real Estate Valuation," FAME Research Paper Series rp148, International Center for Financial Asset Management and Engineering.
    4. Hughes, William T, 1995. "Risk Analysis and Asset Valuation: A Monte Carlo Simulation Using Stochastic Rents," The Journal of Real Estate Finance and Economics, Springer, vol. 11(2), pages 177-187, September.
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    Cited by:

    1. Oualid Benallou & Rajae Aboulaich, 2017. "Improving Capital Budgeting Through Probabilistic Approaches," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-21, September.

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