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

Henry Wurts
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引用次数: 1

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.
严格信息级联的微观公司治理——以Black-Scholes-Merton模型的绩效分析为例
虽然宏观公司治理(例如,解决如何在公司结构中管理治理过程)似乎在学术文献中被广泛讨论,但关于微观公司治理(例如,评估特定模型,包括关于它们是否准确地代表公司风险暴露)的讨论似乎很少,中型公司治理(例如,模型验证过程本身,作为针对特定模型的管理过程)也是如此。公司治理(CG)的一个重要组成部分是模型验证(MV)过程,微观cgmv的一个例子是“严格的信息级联”如何影响验证过程,甚至可能建议不需要模型验证。然而,这样的级联通常不是透明的,并且通常不会被没有经过技术培训的验证者检测到。本文阐述了各种“注意力导向工具”如何作为“快速和节俭的启发式”使用,在一般的模型验证过程和识别“严格信息级联”的特定任务中提供帮助。这些工具被应用于布莱克-斯科尔斯-默顿模型(Black-Scholes-Merton Model),这是一个开创性的金融衍生品模型,即将出版50周年,并被说明可以吸取教训,应用于更复杂的模型和更复杂的金融工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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