Valuation services are gaining still more weight in the field of auditing and assurance services. Reporting standards rely more on capital value and fairness while the auditor is becoming a company’s natural consultant in capital budgeting and investment decisions. Capital value based models, like the discounted cash flow and dividend models, have traditionally been the models of choice. Lately alternative models, the so-called stochastic models, have enjoyed increasing popularity. This places much more demand on the auditor in regard to the skills and knowledge of these modern valuation techniques. The capital value based and the stochastic valuation models belong to two fundamentally various theories that try to achieve the same goal – an estimate of a company’s value. When these models are so different which models are the most suitable? This is the main question studied. The thesis is a comparative analysis of capital value based and stochastic valuation models. Models are categorized and assessed in regard to their precision, assumptions, usability and intelligibility but also to create practical guidance for auditors, students and practitioners. The first part of the thesis is a theoretical analysis which categorizes and assesses the models critically on the basis of available literature. The capital value based models are generally assessed as being practical and easy to interpret. These models however are static and deterministic and assume that all strategic decisions are locked forever. These models are therefore not valid if the company is expected to have significant managerial options (real options). The stochastic models on the other hand are often dynamic with built-in uncertainty. These models are most appropriately categorized by the method of estimation. The analytical and lattice models are not feasible for most real world applications because they are too simple. The Monte Carlo method on the other hand has many advantages. This method can handle most assumptions with multiple variables and correlations. The greatest weakness of this method is an inability to value real options. Decision trees are advantageous in valuing real options but become relatively complex with multiple variables. The Extended Least Squares Monte Carlo method is a very advanced technique that requires substantial knowledge of numerical programming and options modeling. The method is very flexible and can be applied to virtually any option constellation but the extensive knowledge and time requirements make the method impractical and this decreases usability. The second part of the thesis is a case study of three different valuation models applied to the actual company, Starbucks Corporation. This part investigates the strengths and weaknesses of the practical application of the models. First a strategic and financial statement analysis is performed. The strategic analysis is only for illustration and not in-depth. A method called the ER-model for evaluating arguments and evidence of any strategic analysis is introduced. The model may serve as a help in structuring argumentation and evidence. On the basis of the strategic analysis the company is valued with three different models. The models all have strengths and weaknesses. The case study shows that the practical application of the stochastic models is time consuming and more demanding. Stochastic models generally require extensive simplifications which increase model uncertainty. As a result the model user must balance his or her needs for precision when choosing a model.
|Educations||MSc in Auditing, (Graduate Programme) Final Thesis|
|Number of pages||110|