The objective of this study has been to include Monte Carlo simulation into the discounted cash flow (DCF) model and investigate the effect on risk transparency in the valuation result. When valuing investment projects using the DCF method to estimate a net present value and the Capital Asset Pricing Model in order to estimate the systematic risk, the inclusion of financial risks is of great significance. The traditional the DCF model is set up based on most likely values presented as single point estimates, and can potentially hide valuable information since many input estimates in reality can undertake a broad spectrum of values. Further, only including risk in an adjusted discount rate or in overly conservative input estimates, results in a final valuation output that conceals information to the decision maker. To assess this problem and increase the level of transparency in project valuation when using the DCF model, this thesis evaluates how Monte Carlo Simulations can increase the level of information if included in the DCF model. The thesis is built around two similar investment projects in the form of a case study. The case projects, provided by DONG Energy A/S, were valued based on both the traditional DCF approach with point estimates and the simulation based approach where the point estimates are replaced by probability distributions. Under this research method the two valuation approaches are compared based on the cases and found various potential benefits by including Monte Carlo simulations in the DCF model. The main finding was that the simulation based valuation approach is potentially enables the valuation to be better aligned with the CAPM theory and the division of risk into systematic and non-systematic, as the need to adjust the discount rate decreases. Further, this methodology provides a clearer picture of the project risk profile and stimulates an improved input estimation procedure with improved discussions between personnel involved in the valuation process, compared to the DCF model with static inputs. Lastly the simulation approach provides usable information when comparing different investment opportunities. The result in this thesis has not previously been found in the academic literature, and thus adds a new perspective to the existing ongoing discussion concerning the risk assessment in capital budgeting. Based on the findings in the study and we feel confident in recommending the usage of the Monte Carlo method to managers, who wish to increase the level of information in the DCF valuation and better reveal and assess the risk profile of potential investments.
|Educations||MSc in Applied Economics and Finance, (Graduate Programme) Final Thesis|
|Number of pages||169|