The Method of Real Options to Evaluate Innovative Startups

This article delves into an in-depth analysis of the real options method, examining its effectiveness in evaluating innovative startup projects characterized by high levels of uncertainty. It draws a comparison between this method and the traditional approaches to startup valuation and startup uncertainty, highlighting the evolving necessity for more advanced methods in appraising startups and innovative projects.

The findings of this research contributed to the recently published book "When Businesses Test Hypotheses..." (Columbia University Press, Ibidem Press) and the Hypothesis Testing Method. This spot the light on a startup uncertainty and startup risk, embedded investment and managerial options, and enables more comprehensive and accurate evaluation of innovative startups.

One of the key focal points of the article is the exploration of the real options method’s advantages. This method stands out because it incorporates the ability of investors to make pivotal managerial decisions during the development of innovative products or projects. The inclusion of this flexibility in decision-making adds a critical dimension to project valuation.

The article emphasizes the need for enriching the scientific and practical literature regarding the use of complex options for project evaluation. To bring a practical perspective to these concepts, it walks through a three-year simple deferral option, elucidating its financial benefits in the context of investment decision-making. This practical illustration underscores the method’s value, particularly in terms of making sound investment choices at each stage of uncertainty resolution, thereby reflecting on the crucial impact of accurate investment decisions in the unpredictable journey of innovation.

Publisher: Business-Inform, (2), pp. 102–108.

The full manuscript of the "The Method of Real Options to Evaluate Innovative Projects" article is available at: https://doi.org/10.32983/2222-4459-2019-2-102-108.

Dmytro Shestakov, 2019