Risk measurement in valuation

The measurement of value is inherently related to the measurement of risk because we refer to future events, i.e. forecasted factors.

According to a unanimous view, value in the economic sense is the amount of money that must be paid today for the stream of future benefits that can be generated thanks to the ownership or use of the object of valuation.

The term "risk" (Definition according to David Vose, "Risk analysis - a quantitative guide", Wiley & Sons, 2008) means "a random event that may occur and, if it occurs, will have a significant negative impact on the achievement of the objectives of the action." The consequence of adopting such a definition is the assumption that there are real event scenarios about the estimable probabilities of implementing individual scenarios, about the possibility of estimating the strength and direction of the impact of the effects of events on the implementation of goals (value or distribution of values of variables indicating the degree of achievement of goals).

Risk measurement for the valuation process is critical in the case of the valuation of rights to technology at an early stage of commercialization, designing provisions of license or franchise agreements, designing brand development strategies, etc.

Our perception of risk, including the ability to measure it, depends mainly on the model of reality we accept. Historically, the cause-and-effect analysis of phenomena led to the construction of an extreme model (developed in the form of "Laplace's demon or machine"), according to which having all the information about specific objects would allow for confident prediction of their behaviour in the future. Therefore, the effectiveness of planning would only be limited by incomplete information. As business practice shows, information gaps are an inseparable companion of the decision-making process. We use this insight today by defining one of the critical risk factors called "uncertainty". There are methods to measure the level of uncertainty to estimate the value of obtaining additional information. We can limit the risk by reducing uncertainty, e.g. by conducting new market research and providing another portion of information. The supporters of the "Laplace machine" perceived reality according to a model that could be described as "deterministic" or fatalistic.

The deterministic model did not stand the test of time, and the conclusions drawn from the "Heisenberg uncertainty principle" pointed to the random nature of phenomena and contributed to developing the "non-deterministic model" of perceiving reality. As a consequence of adopting this model, planning can also be effective in conditions of incomplete information and high variability of phenomena, but this requires building stochastic planning models. As a result, stochastic analysis and practical applications of simulation analysis have developed. It was accepted that variability, along with uncertainty, is a crucial source of risk. Variability is a feature of a given system and cannot be limited by obtaining subsequent information, as with uncertainty. Reducing variability for risk management, e.g. in a license contract, requires intervention in the system, i.e. entering the necessary clauses or options in the contract.

Based on the concepts presented, modern methods of identifying and measuring risk in qualitative and quantitative terms have been developed in valuation practice. The needs of the valuation process carried out in specific economic conditions will determine which risk measurement methods will be used in practice when the need to measure risk is included in the valuation process; reality is complex and multi-threaded with systems with high variability of phenomena and events; there is a need to make decisions in conditions of uncertainty; an assessment using random variables leading to a result with a specific probability distribution (range of values) is more desirable than a "single-value point assessment".

In a decision-making process involving significant risk, the identification of risk-generating events and the measurement of the probability of their occurrence will allow the use of stochastic models in the valuation process, which creates the possibility of correct risk implementation (model built taking into account identified stochastic processes and using probabilistic methods).