Risk analysis in corporate financial modelling

Abstract

Models applied in corporate finance can typically use only one segment of our knowledge about the future: expected values. In the light of this, the final results do not reflect the uncertainty related to the input parameter values. Despite having several available tools to allude to the uncertainty we were forced to hide when we are presenting the results to the decision maker, this process and the interpretation of output data often include misunderstandings and mistakes. When providing an overview of the risk analysis toolkit, this article focuses on exploring such misunderstandings and mistakes and describes other risk factors which influence the outcome of the modelling process. Based on the literature review, it seems that a kind of conversion between different risks exits: theoretically more accurate models may be more sensitive to estimation errors of input parameters and set much higher requirements towards modellers. JEL codes: C6, D8, G17, G32Decisions on corporate finance issues require information about the future, however, such information is usually far from being certain. Consequently, we can rely only on various forecasts and estimates. At the same time, almost none of the indicators and formulas supporting decisions in corporate finance use expected distributions or value ranges, but suppose the accurate knowledge of specific values. In view of the above, our expectations about the future usually have to be concentrated in one number (in most cases, in the expected value).This article examines the available means of displaying the uncertainty about input parameters in the final result of calculations in spite of the above, supporting risk-conscious decision-making. Agreeing with the main message of the study 1 Péter Juhász, Associate Professor with habilitation at Corvinus University of Budapest.