The purpose of this master thesis is to estimate the value of the BMW AG at 1 February 2015 and apply a Monte Carlo simulation on the value drivers in the proforma statements. The Monte Carlo simulation was applied to take into account uncertainties of the estimates in the proforma statements of the DCF model. The strategic analysis conducted was built through an external analysis consisting of a PET and a Porters five forces analysis and an internal analysis based on a VRIN analysis. The societal findings of the PET analysis showed that BMW is highly dependent on the development of the economy in the different markets. It also showed that government policy and regulations is an important factor and is expected to be so in the future, pushing the automakers towards a greener future in their production and products. The competitive intensity of the premium car industry was identified as medium as a result of three manufactures with strong brands dominating the market being pushed by each other and buyer power. The internal analysis showed a competitive advantage due to the strategy of standardized production, minimizing costs compared to the Audi and Daimler. It also means cheaper and faster development of new products but comes in the price of higher risk in products recalls. In the financial analysis the financial services segment was separated so the focus is on the core activities from the automobile segment. The results showed a strong positive development where ROE primarily was driven by ROIC. Audi performed best of the peers spite BMW’s advantage in the production coming in second with Daimler third. The findings in the strategic and financial analysis served as the foundation for the revenue driven proforma statement that provided the future cash flows. The market value of BMW AG was estimated to 107.594 mio. € which is equivalent to stock price in the base case of 163,84 € indicating an underestimated of the official stock price of 103,4 € corresponding to upside potential of 58 %. The Monte Carlo simulation focused on the terminal period of the value drivers and the results from running 50.000 trials showed base case at the 74% percentile in the cumulative frequency chart. The average at 149,48 meant a right skewed figure with an interval of 114,01 – 207,31 at a 95% confidence interval, were the EBITDA margin, Growth and WACC had the largest impact on the result. The results indicated that the base case was at the optimistic side, though it didn’t change that undervalued conclusion of the official stock price of 103,4 €. It was argued that the Monte Carlo simulation was based on the GIGO-principle (garbage in garbage out) and the original estimates were therefore changed to examine the impact I would have. The results indicated as predicted distinctive changes in the estimated stock price. The base case was now moved to the 90 % percentile in the cumulative frequency chart with an average at 133,81 and an interval from 99,06-192,47. The value drivers’ impact also changed drastically, where WACC and invested capital in the terminal period had the most significant changes, though EBITDA margin and Growth also saw significant less impact on the model. The Monte Carlo simulation showed great potential as a tool in valuation purposes, but the later analysis emphasized the importance of the conditions and assumptions of the model and the influence they have.
|Educations||MSc in Finance and Accounting, (Graduate Programme) Final Thesis|
|Number of pages||121|