Abstract
Purpose – The objective of this research is to establish a link between risk models and the paradigms of organizational studies. Design/methodology/approach – To achieve this goal, a discussion about risk in organizations was presented, based on organizational studies. Additionally, an illustration was provided to evaluate how organizational paradigms influence risk models. Findings – There are three main organizational perspectives: Modernist, Postmodernist, and Neo-modernist. Based on the empirical analysis, it was observed that the use of unrealistic assumptions (Modernist perspective) in risk management increases model risk, and is thus not suitable for risk model estimation. However, the absolute lack of measurement of the Postmodernist paradigm can be too radical in the sense that, in the practical field, there is a crucial need for quantitative information to enable financial institutions and investors to protect their investments. Thus, it was found that the solution is the Neo-modernist paradigm, which employs more realistic assumptions about data behavior. Originality/value – The main contribution of this research is to raise the influence of other attributes of financial risk estimation that go beyond mathematical and statistical grounds. Previous studies do not relate the traditional literature on financial risk management estimation with literature focused on the sociological issues of organizational studies. Hence, this study can help build a bridge for future integration between these two related research subjects.
Highlights
Risk is one of the most important financial concepts, perhaps the most important
This paper establishes a connection between the assumptions of risk models and the paradigms of organizational studies
A discussion was presented on risk in organizations, based on organizational studies
Summary
Risk is one of the most important financial concepts, perhaps the most important. Every time financial stress occurs, including the recent crises and collapses in the financial system, the focus on risk management is raised. In periods of greater instability, the models tend to be least reliable This occurs because the fundamental assumption in most statistical risk modeling is that the basic statistical properties of financial data during stable periods remain (almost) the same as during crisis periods (Daníelsson, 2002; Daníelsson, 2008). In this modeling, the quality of the assumptions is of key importance. An illustration is presented with real data to show how risk models are influenced by organizational paradigms and the way this affects estimation results.
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