On the Micro-Corporate-Governance of a Strictly Informational Cascade, As Illustrated with Analysis of the Performativity of the Black-Scholes-Merton Model

83 Pages Posted: 3 Jun 2021 Last revised: 23 Jun 2021

Date Written: June 7, 2021

Abstract

While macro-corporate-governance (e.g., addressing how a governance process should be administered within a corporate structure) seems to be widely discussed in academic literature, a discussion of micro-corporate-governance (e.g., assessing specific models, including regarding whether they accurately represent a corporate risk exposure) seems sparse, as does midi-corporate-governance (e.g., the model validation process itself, as an administered process toward specific models). An important part of corporate governance (CG) is the model validation (MV) process, with one example of micro-CGMV being how “strictly informational cascades” can influence a validation process, even perhaps suggesting that model validation is not required. Yet, such cascades are not often transparent, and not often detected by validators who are not technically trained. This paper illustrates how a variety of “attention directing tools” used as “fast and frugal heuristics” can help in the model validation process in general and the specific task of identifying “strictly informational cascades.” The tools are applied toward the Black-Scholes-Merton Model, a seminal financial derivatives model that is approaching a 50th anniversary of publication, and are illustrated to demonstrate that lessons can be learned to apply to more-complex models and more-complex financial instruments.

Keywords: corporate governance, model validation, strictly informational cascade, CGMV, micro-CGMV, performativity, Black-Scholes-Merton (BSM) Model, Bad Creativity

JEL Classification: G3, G32, G12, G13, B26, C52

Suggested Citation

Wurts, Henry, On the Micro-Corporate-Governance of a Strictly Informational Cascade, As Illustrated with Analysis of the Performativity of the Black-Scholes-Merton Model (June 7, 2021). Available at SSRN: https://ssrn.com/abstract=3857857 or http://dx.doi.org/10.2139/ssrn.3857857

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