Traditional valuation of companies is subject to a number of assumptions and uncertainties. It is a fact that equity analysts, professors, students and others are unable to predict the exact performance of any company in the future. This thesis examines how Monte Carlo simulations provide greater insight into the implications of forecast assumptions in company valuation.
To carry out the various Monte Carlo simulations, I have chosen a case study as research design. Using the listed Danish company Royal Unibrew, I analyze both independent- and dependent scenarios, each of which highlights significant relationships within the traditional valuation framework. The independent scenarios value the stock price through random forecasting without correlation between the forecast assumptions. The dependent scenarios incorporate correlations between the forecast assumptions.
Through five different scenarios, the analysis shows how stock price distributions are affected by forecast assumptions, including probability distributions, the level of discount rate (WACC) and incorporated correlations between significant forecast assumptions.
The use of Monte Carlo simulations in this study does not offer a conclusion on Royal Unibrew’s stock price. However, the various scenarios provide insight on how different forecast assumptions impact the fundamental value of the stock.
|Educations||MSc in Finance and Accounting, (Graduate Programme) Final Thesis|
|Number of pages||107|