Abstract
This thesis aims to assess whether the consideration paid by JBT in its voluntary takeover of Marel can be justified by the expected synergies, using real options valuation (ROV) as a valuation method. In addition, ROV’s applicability in mergers and acquisitions (M&A) contexts is explored. The simulation-based Datar-Mathews method was chosen to estimate the value of the expected synergies. Traditional valuation methods, such as the discounted cash flow (DCF) model, are commonly employed to estimate a company's enterprise value. However, they can be limited in their ability to capture uncertainty and managerial flexibility, which are two distinct characteristics of synergies in M&A. Synergies are often one of the main justifications for a merger or acquisition, yet they are highly uncertain and can therefore be difficult to estimate using traditional methods. Real options valuation, on the other hand, gives firms the flexibility to adapt, delay, expand, or abandon projects as uncertainty unfolds, making it well-suited for synergy valuation. Despite this, ROV is rarely applied in M&A contexts. In this thesis, the expected synergies from the JBT and Marel merger were divided into two categories: revenue-enhancing and cost-reducing. These were evaluated using the Datar-Mathews method to estimate the real option value of the synergies. The findings show that the present value of the expected synergies from the merger amounts to $623,8 million. To compare this to the consideration paid by JBT, Marel’s stand-alone value was added to the expected synergies, resulting in a total value acquired in the merger estimated at $3,93 billion. This exceeds the total consideration paid by JBT, which was $3,02 billion, indicating that the merger is financially justified based on expected synergies. The thesis concludes that ROV, particularly the Datar-Mathews method, can be a useful complement to traditional models when valuing synergies.
| Educations | MSc in Finance and Strategic Management, (Graduate Programme) Final Thesis |
|---|---|
| Language | English |
| Publication date | 2025 |
| Number of pages | 87 |