Sustainable Financial Risk Modelling Fitting the SDGs: Some Reflections

Christian Walter (2020)

Sustainability, 12(18), 7789, pp. 1-28

Abstract. This article argues that any ecological finance theory devised to fit the Sustainable Development Goals (SDGs) needs a paradigm shift in the morphology of randomness underlying financial risk modelling, by integrating the characteristics of “nature” and sustainability into the modelling carried out. It extends the common diagnosis of the 2008 financial crisis with considerations on the morphology of randomness and the reasons why neoclassical finance theory is not sustainable from this perspective. It argues that the main problem with unsustainable neoclassical finance risk modelling is its underlying morphology of randomness that creates a dangerous risk culture. It presents Leibniz’s principle of continuity and Quetelet’s theory of average as cornerstones of classical risk culture in finance, acting as a mental model for financial experts and practitioners. It links the notion of sustainability with the morphology of randomness and presents a possible alternative approach to financial risk modelling defined by rough randomness. If morphology of randomness in nature is properly described by fractal and multifractal methods, hence ecological finance theory has to include fractal properties into financial risk models. The conclusion proposes a new agenda for future research.

Extract. “2.2.1. Socio-Technical Instruments: The Financialised Tools

An important aspect of the performativity of mathematical financial risk modelling is the socio-technical dimension of the mathematical models. Financial instruments derived from mathematical models and financialised evaluation play an important role in the financialisation of the economy [33–35]. To better understand how a particular risk culture is created based on a probabilistic hypothesis, it is interesting to note a detail of the dialogue between Sarah Robertson and Jared Cohen in Margin Call: Robertson’s remark “we were wrong”. The use of the word “we” denotes a form of socially elaborated and shared knowledge with a practical aim, which helps to construct a culture of models common to a financial group, the culture of “how a model works” [36]. The culture of models is based on calculation and quantification conventions [37,38]. Quantification conventions ensure the same risk culture for financial practitioners. The culture of models is an “epistemic culture” in the sense of Knorr Cetina [39], specific to each group of financial practitioners: This culture diffuses a general way of thinking about technical objects. The technical objects of finance are overloaded with probabilistic techniques. Probabilistic techniques have had an enormous influence on risk assessment and the formation of quantification conventions [40]. Much work has been carried out on the basis of these methodological premises and I take the liberty of referring the reader to the references indicated so as not to lengthen the text excessively. (p. 5)

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