Valuation of a Young Tech Firm: Trustpilot. Bringing Theory and Practice Together.

Eveliina Laura Sofia Arokivi

Student thesis: Master thesis

Abstract

This paper provides a detailed valuation of a tech firm at the early stage of its life. It explores how valuation approaches can explain the discrepancy of investors trading the share of a young tech firm at the higher range following its IPO even though the firm in question has only made losses. The firm of our case study, Trustpilot, provides an innovative service in the online review market that is relatively new but growing. Given the firm's early age, limited past financial information and only a handful of similar firms, we describe certain challenges related to valuing a newly listed tech firm like Trustpilot. The valuation is done from the perspective of a potential investor and augments public financial and non-financial information on Trustpilot. This information includes market data and company-specific information. The information is first analysed with financial and strategic frameworks to create profound forecasting. To estimate Trustpilot’s share price, we use three approaches - discounted cash flow, relative valuation and contingent claim valuation – and compare the results to the observed share price and its development. Our findings are that applying only one valuation approach proves insufficient. The valuation results reveal that the classic discounted cash flow (DCF) model provides a good foundation for a newly listed firm like Trustpilot. However, we identified three situations where either option theory, relative valuation or a DCF with an acquisition price as a terminal value can better explain the observed share price. For investors, our results imply that multiple valuation methods should be applied to capture and understand all the drivers of the share price. To management in firms similar to our case company, our results suggest that investor communication should activilely support efficient use of multiple valuation methods.

EducationsMSc in Applied Economics and Finance, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date2022
Number of pages86