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Publication Title

Washington University Law Review

Abstract

Accurately and precisely modeling financial risk is somewhat of a Holy Grail for financial theorists, regulators, and market participants. But like the Holy Grail, the location of a comprehensive model of risk remains unknown; some have even suggested that such a model is a figment of financial theorists’ imaginations. Nowhere has that disaster been more fully evident than in the recent failure of risk models to adequately prepare the marketplace for the collapse of the market for mortgage-backed securities and credit derivatives, and the financial crisis that followed. Because of the mistaken assumptions associated with some risk models, otherwise vigilant market participants were blinded to the risks that brought the global financial system to the brink of collapse.

I propose a lawyer’s solution: use a form of mandatory disclosure for off-balance-sheet guarantees and over-the-counter (OTC)derivatives to provide the data necessary to describe the risk of a firm’seconomic footprint in the unlikely event of catastrophic collapse. With this data, regulators and firms could compute what I preliminarily call a Fat-Tail Risk Metric (FTRM), or a metric for determining the impact of the most financially devastating high-impact, low-probability events.Such a disclosure requirement could have three principal benefits. First, requiring mandatory disclosure of contingent liabilities — namely, derivatives and off-balance-sheet guarantees — will resolve the ongoing difficulties in record keeping that have plagued the industry. Second, a scale that measures the size of a firm’s impact upon catastrophic collapse provides a relative measure with which regulators can compare firms of equal market capitalization and/or balance sheet assets that have differing remote-risk profiles.Third, and most importantly, the FTRM will provide a steady stream of data that has, until now, been impossible to gather and could prove essential in understanding risk measurement at the firm level over the coming decades. With that information, defining ―too big to fail may simply become a question of basic econometrics.

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