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Do Labyrinthine Legal Limits on Leverage Lessen the Likelihood of Losses?: An Analytical Framework

36 Pages Posted: 30 May 2012 Last revised: 5 Sep 2012

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Thomas J. Brennan

Harvard Law School

Date Written: May 29, 2012

Abstract

A common theme in the regulation of financial institutions and transactions is leverage constraints. Although such constraints are implemented in various ways — from minimum net capital rules to margin requirements to credit limits — the basic motivation is the same: to limit the potential losses of certain counterparties. However, the emergence of dynamic trading strategies, derivative securities, and other financial innovations poses new challenges to these constraints. We propose a simple analytical framework for specifying leverage constraints that addresses this challenge by explicitly linking the likelihood of financial loss to the behavior of the financial entity under supervision and prevailing market conditions. An immediate implication of this framework is that not all leverage is created equal, and any fixed numerical limit can lead to dramatically different loss probabilities over time and across assets and investment styles. This framework can also be used to investigate the macroprudential policy implications of microprudential regulations through the general-equilibrium impact of leverage constraints on market parameters such as volatility and tail probabilities.

Keywords: Leverage, Liquidity, Financial Regulation, Capital Requirements, Macroprudential Policies, Net Capital Rules

JEL Classification: G12, G29, C51, E58, E51

Suggested Citation

Lo, Andrew W. and Brennan, Thomas J., Do Labyrinthine Legal Limits on Leverage Lessen the Likelihood of Losses?: An Analytical Framework (May 29, 2012). Texas Law Review, Vol. 90, No. 7, 2012. Available at SSRN: https://ssrn.com/abstract=2070408 or http://dx.doi.org/10.2139/ssrn.2070408

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

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E62-618
Cambridge, MA 02142
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617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
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Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Stata Center
Cambridge, MA 02142
United States

Thomas J. Brennan

Harvard Law School ( email )

1557 Massachusetts Ave
6 Ever
Cambridge, MA 02138
United States
617-495-3141 (Phone)

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