MLiq a meta liquidity measure

Serge Darolles, Jérémy Dudek and Gaelle Le Fol
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Jérémy Dudek: DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique

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Abstract: The last crisis sheds light on the importance to consider liquidity risk in the financial industry. Indeed, liquidity had a predominant role in propagating the turmoil. In contrast, controlling for liquidity is a difficult task. The definition of liquidity links different dimensions that are impossible to fully capture together. As a consequence, there exist a lot of liquidity measures and we find in the literature some solutions to take into account more than one dimension of liquidity but also liquidity measures considering a long lasting liquidity problem. In this paper, we focus on drastic illiquidity events, i.e liquidity problems reported by several liquidity measures simultaneously. We propose a Meta-Measure of liquidity called MLiq and defined as the probability to be in a state of high liquidity risk. We use a multivariate model allowing to measure correlations between liquidity measures jointly with a state-space model that endogenously defines the illiquid periods.

Keywords: Liquidity; Liquidity measure; Liquidity Risk Management; Correlations; Regime Switching models.; Regime Switching models (search for similar items in EconPapers)
Date: 2012-12-01
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Published in Computational and Financial Econometrics (CFE'12), Dec 2012, Oviedo, Spain

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Working Paper: MLiq a meta liquidity measure (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-00877026

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