Empirical Determinants of Enterprise Value in M&A Transactions A Cross-Sector Regression Analysis of U.S. Small-Cap Public Company Deals (2005–2025)

dc.contributor.authorEkelind, Jonathan
dc.contributor.authorLundborg, Pontus
dc.contributor.authorOlausson, Jacob
dc.contributor.authorKajanus, Viktor
dc.contributor.authorLöwing, Hampus
dc.contributor.authorTönder, Erik
dc.contributor.departmentChalmers tekniska högskola / Institutionen för teknikens ekonomi och organisationsv
dc.contributor.departmentChalmers University of Technology / Department of Technology Management and Economicsen
dc.contributor.examinerLöwstedt, Martin
dc.contributor.supervisorLjungwall, Christer
dc.date.accessioned2025-09-23T11:28:56Z
dc.date.issued2025
dc.date.submitted
dc.description.abstractExisting methods for calculating a firm’s enterprise value (EV) inherently depend on subjective estimates and assumptions leading to variability based on the practi- tioner’s judgment. This thesis uses a deductive, quantitative approach to investigate which factors influence EV in mergers and acquisitions (M&A). The analysis is based on secondary data from Capital IQ, covering U.S. small-cap public M&A transac- tions between 2005 and 2025. Using ordinary least squares (OLS) regression , the results show that market capitalization, net debt, and total assets are significant pre- dictors of EV. These findings suggest that these financial variables play a key role in determining the value of a company in M&A deals. This data-driven valuation method offers a more objective alternative to traditional approaches.
dc.identifier.coursecodeTEKX18
dc.identifier.urihttp://hdl.handle.net/20.500.12380/310506
dc.language.isoeng
dc.relation.ispartofseriesTEKX18-25-13
dc.setspec.uppsokTechnology
dc.subjectEnterprise Value
dc.subjectMergers and Acquisition
dc.subjectTotal Assets
dc.subjectNet Debt
dc.subjectMarket Capitalization
dc.subjectRegression Analysis
dc.subjectOrdinary Least Squares
dc.titleEmpirical Determinants of Enterprise Value in M&A Transactions A Cross-Sector Regression Analysis of U.S. Small-Cap Public Company Deals (2005–2025)
dc.type.degreeExamensarbete på kandidatnivåsv
dc.type.degreeBachelor Thesisen
dc.type.uppsokM2
local.programmeIndustriell ekonomi 300 hp (civilingenjör)

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