Mixture of distribution hypothesis: Analyzing daily liquidity frictions and information flows

Serge Darolles, Gaelle Le Fol and Gulten Mero

Journal of Econometrics, 2017, vol. 201, issue 2, 367-383

Abstract: The mixture of distribution hypothesis (MDH) model offers an appealing explanation for the positive relation between trading volume and volatility of returns. In this specification, the information flow constitutes the only mixing variable responsible for all changes. However, this single static latent mixing variable cannot account for the observed short-run dynamics of volume and volatility. In this paper, we propose a dynamic extension of the MDH that specifies the impact of information arrival on market characteristics in the context of liquidity frictions. We distinguish between short-term and long-term liquidity frictions. Our results highlight the economic value and statistical accuracy of our specification. First, based on some goodness of fit tests, we show that our dynamic two-latent factor model outperforms all competing specifications. Second, the information flow latent variable can be used to propose a new momentum strategy. We show that this signal improves once we allow for a second signal – the liquidity frictions latent variable – as the momentum strategies based on our model present better performance than those based on competing models.

Keywords: Strategic liquidity trading; Market efficiency; Mixture of distribution hypothesis; Information-based trading; Extended Kalman Filter (search for similar items in EconPapers)
JEL-codes: C51 C52 G12 G14 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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Related works:
Working Paper: Mixture of Distribution Hypothesis: Analyzing daily liquidity frictions and information flows (2017)
Working Paper: Mixture of distribution hypothesis: Analyzing daily liquidity frictions and information flows (2016)
Working Paper: Mixture of distribution hypothesis: Analyzing daily liquidity frictions and information flows (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:201:y:2017:i:2:p:367-383

DOI: 10.1016/j.jeconom.2017.08.014

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