Real Options and Monte Carlo Simulation versus Traditional DCF Valuation in Layman's Terms

2006 ◽  
pp. 75-106 ◽  
Author(s):  
Johnathan Mun
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Real Options

Superiority of Monte Carlo simulation in valuing real options within public–private partnerships

2017 ◽  
Vol 20 (1) ◽  
pp. 1-28 ◽  
Author(s):  
Ales S. Berk ◽  
Dejan Podhraski
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Real Options ◽  
Public Private Partnerships

Fuzzy Real Options for Risky Project Evaluation Using Least Squares Monte-Carlo Simulation

2011 ◽  
Vol 5 (3) ◽  
pp. 385-395 ◽  
Author(s):  
Qian Wang ◽  
D. Marc Kilgour ◽  
Keith W. Hipel
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Real Options ◽  
Least Squares ◽  
Project Evaluation ◽  
Least Squares Monte Carlo

Using Monte Carlo Simulation to Improve Ceramic R&D Investment Decisions

2010 ◽  
Vol 105-106 ◽  
pp. 798-801
Author(s):  
Bao Cheng He ◽  
Hong Tao Jiang ◽  
Shu Zhi Yao ◽  
Bao Yuan He
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Real Options ◽  
Cash Flow ◽  
Investment Decisions ◽  
Discounted Cash Flow ◽  
Valuation Model ◽  
Managerial Flexibility ◽  
D Investment

The success of ceramic companies is highly dependent on research and development (R&D). Thus, a pivotal aim of management is to allocate resources to the best scientific and financial R&D projects. But the valuation of ceramic R&D is a difficult task for managers. The conventional discounted cash flow (DCF) methods fail to consider the value of managerial flexibility provided by R&D projects. Real options Analysis (ROA) offers a superior way of capturing the value of flexibility. It enables decision-maker to value projects more accurately by incorporating managerial flexibilities into the valuation model. However, ROA can’t effectively deal with the volatility of parameters in itself under high uncertain circumstance. In view of the limitation of ROA, this paper uses Monte Carlo simulation to solve the parameters volatility problems. In the end, the case study proves that Monte Carlo simulation can improve R&D investment decisions, especially for highly unpredictable ceramic R&D projects.

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