Understanding the EV/EBITDA Multiple: The Role of Value Drivers and Behavioral Finance

Abstract

This thesis examines how technology firms are valued in the market by considering the EV/EBITDA multiple through selected quantifiable value drivers and the framework of over-confidence and representativeness. This research is motivated by the recently observed vola-tility in the valuations of technology firms. Additionally, determining the actual value of tech-nology firms can be highly complex because many of them exhibit high growth, negative earn-ings in the early stages, and hold substantial value in intangible assets that may not be re-flected in the balance sheet. Altogether, this has created an interest in exploring whether it is possible to increase the understanding of the valuation of technology firms.

In pursuit of increasing the understanding, the thesis conducts a series of multiple linear re-gressions with EV/EBITDA as the dependent variable and growth, profitability, risk, and intangible assets as the independent variables. The utilized samples are based on firms from the American Information Technology sector from March 31, 2019, to March 31, 2023, thus providing a current perspective considering recent market developments. Furthermore, the findings from the multiple linear regressions are discussed concerning the behavioral heuristics of overconfidence and representativeness. Lastly, the assumption of an efficient market is dis-cussed in relation to the technology sector motivated by potential behavioral biases and fre-quent fluctuations in valuations.

Previous studies have performed regressions on valuation multiples to examine the accuracy of one or more particular multiples and the relationship between the underlying factors and the respective multiple. However, only few have conducted a thorough analysis of a single sector, and incorporated the field of behavioral finance to discuss their empirical findings. Hence, this thesis contributes to the existing literature by shedding light on some of the various factors that influence the EV/EBITDA multiple for American technology firms.

The empirical findings suggest that growth and intangible assets are important factors to consider when evaluating technology firms, while the reliance on profitability and risk as driv-ers of value may be less significant. Moreover, the importance of these value drivers is found to vary over time and across firm size. In addition, the frameworks of overconfidence and representativeness are used to discuss whether there have been overly optimistic growth ex-pectations in the technology sector during the considered period. Overconfidence is further applied to discuss the possible neglection of risk by technology investors, while the observed fluctuations in valuations are discussed in the light of representativeness. However, the pres-ence of the two behavioral biases is only discussed and not proven, as it would require further empirical investigation. Further, it is discussed whether there could be potential challenges to market efficiency or whether it is just the market moods changing. Finally, the discussion highlights the challenges of applying relative valuation under market inefficiency.