BibTeX
@MISC{_measuringliquidity,
author = {},
title = {Measuring Liquidity Mismatch in the Banking Sector},
year = {}
}
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Abstract
This paper implements a liquidity measure proposed by Brunnermeier, Gorton and Krishnamurthy (2011), "the Liquidity Mismatch Index (LMI), " to measure the mismatch between the market liquidity of assets and the funding liquidity of liabilities. In the LMI each asset and liability has a contract-specific time-varying liquidity sensitivity weight which is driven by contract terms and market prices. Using bank regulatory report and repo transaction data, we construct the LMI for 2870 bank holding companies during 2002-2013 and investigate its time-series and cross-sectional patterns. The LMI can be aggregated across firms to measure the aggregate liquidity shortfall in the U.S. banking sector. We find that the aggregate banking sector LMI worsens from around [negative] $2 trillion in 2004 to $4.5 trillion in 2008, before reversing back to $2 trillion in 2009. In the cross section, we find that banks with more liquidity mismatch (i) experience more negative stock returns during the crisis, and more positive stock returns pre-crisis, and (ii) experience more negative stock returns on events corresponding to a liquidity run, and more positive stock returns on events corresponding to liquidity provision by the government. We also demonstrate that the LMI can serve as an effective tool in liquidity stress tests. 1 1
Keyphrases
liquidity mismatch banking sector negative stock return liquidity provision bank regulatory report market price positive stock return liquidity measure liquidity mismatch index aggregate banking sector lmi funding liquidity positive stock return pre-crisis market liquidity liquidity run contract-specific time-varying liquidity sensitivity weight aggregate liquidity shortfall negative $2 cross section liquidity stress test contract term u.s. banking sector cross-sectional pattern repo transaction data effective tool
