Adam Smith, the renowned philosopher once wrote: âall money is a matter of belief.â1
In 1906, Marcus Goldman took this insight and monetized it, when he sought to raise capital for the United Cigar company. At that time, Goldman gave a more concrete definition to valuation, with his development of the ground-breaking technique of using a companyâs future earnings potential to establish a valuation of a firm and attract long-term equity investments.
The successful sale of United Cigarâs common shares based on this principle became a model for future industrial and retail transactions, and was used by the leading retailers at the time. After World War I, financial valuation grew into an academically and market-validated concept, becoming the gold standard for establishing the value of and raising capital for new companies in industries that were asset-poor and precedent-lacking, yet rich in potential.
Decades later, and valuations have become a standard in almost all financial activity, from mergers and acquisitions of publicly traded firms to the allocation of shares in a private firm and for the meeting of basic needs. In recent years, with technology companies emerging and becoming a vital part of investorsâ portfolio, the challenge has arisen of adapting valuation tools to be able to evaluate these assets and assess the potential of new developments.
From the viewpoint of large companies, valuation is based on forecasts of free cash flow. In technologically driven industries, the pipeline or the products that a given firm has in its portfolio can represent a large fraction of market capitalization. The situation is even more critical for small companies committed to a single idea, as all of their value is linked to a single project and based on their intellectual property (IP). Any business transaction in which innovative projects or products are being valued or exchanged requires a realistic valuation of those items, as does any internal proposal to initiate or terminate an R&D project. Moreover, different projects have very different dynamics. Pharmaceuticals have very long lead times and are dependent on patents as well as on out-licensing deals. And while software can be developed very quickly, IP is difficult to value.
This work is intended to provide a practical guide for entrepreneurs, investors, and financial advisors for constructing and understanding valuations of technology companies, mainly startups , in rapidly shifting industries, focusing on life sciences (pharmaceuticals), cyber security, and renewable energy.
While this book focuses primarily on the financial aspects of valuation, it also draws on a number of interdisciplinary approaches, especially with respect to the issues encountered when evaluating early-stage ventures. Of particular importance is our analysis of psychological insights into investor and entrepreneur behavior at different intervals throughout the valuation process. Until now, the normative approach to economic modeling has been based on traditional assumptions of economic rationality. This approach is now being increasingly tempered by new insights into the psychological aspects of decision-making.
The many traditional models of rational decision-making view the mind as if it were an omnipotent being. However, the perceptions of all human creatures about the world, and their ensuing decisions are affected by limitations of time, knowledge, and decision-making abilities. Most âreal-lifeâ areas, such as capital markets, involve uncertainty, which leads to investorsâ âbounded rationality,â meaning that they actually can see and assess only an incomplete and possibly even misleading snapshot of reality. If one desires to understand how human minds work, he must look not only at how our reasoning is âlimitedâ in comparison to an ideal model, but also at how our minds are adapted to real-world environments.2
Herbert Simon, Nobel Prize Laureate and father of behavioral finance, viewed bounded rationality as consisting of two elements that are inextricably intertwined. The first is the inherent limits on the way the human mind functions, and the second is the nature of the environments or areas in which the individual must make judgments. With respect to the inherent limits of the human mind, the argument is that models of human judgment and decision-making should be built on what we actually know about the mindâs capacities rather than on conjectures that may have no basis in reality. In many actual situations, it is impossible to know what the optimal strategy is. Even in a game such as chess, where an optimal (best) move does in fact exist at every point, there is no strategy, whether generated by a person or a machine, for determining the perfect move in a reasonable amount of time, despite the well-defined nature of the possibilities to be searched. There is even less of a possibility of finding an optimal strategy in the real world with less defined and more dynamic conditions. As a result of this and the mindâs inherent limitations, people humans use approximate methods to handle most tasks.
These methods include recognition processes that largely allow people to eliminate the need to search for further information. The second method involves decision-making processes for making a search and determining when sufficient information has been accumulated to make a determination. Finally, people turn to and even subliminally use simple decision-making rules that they apply to the information found. After clarifying the elements of a valuation and how they are applied to a company, the general issues that need to be addressed when making a valuation about the company itself and its market environment, and the special challenges of making valuations for new technology and startup companies, it becomes clear that not all valuations âare created equal,â given that emotional and irrational factors influence the judgments made by everybody, including financial professionals.
To help professionals and laymen alike, this book presents some examples taken from actual valuations of life science, cybersecurity, and renewable energy companies. These examples illustrate how the rules and theories discussed throughout the fir...