Valuing an agricultural technology startup using real options

Abstract

There has been substantial growth in investments for startup firms to develop agricultural technology. Although investing in startups can produce significant returns, the risk of failure is high, and the commercial strategies are largely unknown. Traditional valuation methodologies, such as discounted cash flow (DCF) and multiples, are not well suited for startups. Real options provide a methodology to quantify the value of growth opportunities and managerial flexibility, two critical features of startups. This study develops a model that integrates decision trees and a stochastic binomial lattice to quantify the value of growth opportunities and managerial flexibility in a prerevenue AgTech startup. Utilizing a binomial lattice and decision trees allows for the quantification of private and market risk. The result is a valuation that quantifies the upside optionality that other methodologies disregard.

New product development in micro, small, and medium-sized enterprise-based agriculture products: a valuation technology approach

“…With this value, technology developed as a consequence of research efforts requiring an investment of time, money, and knowledge will receive just financial compensation [9]. This incentive can be utilized by innovators to do long-term research in the same field, i.e., to create technology that is consistently more competitive and generates income as a result of putting their research findings to use [10].…”