Mixture of Distribution Hypothesis: Analyzing daily liquidity frictions and information flows

Serge Darolles, Gaelle Le Fol and Gulten Mero

Post-Print from HAL

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 flows constitute 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 flows 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 the strategies based on competing models

Keywords: C52; C51; Strategic liquidity trading; market efficiency; mixture of distributionhypothesis; information-based trading; extended Kalman Filter; G12; G14 (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (22)

Published in Journal of Econometrics, 2017, ⟨10.1016/j.jeconom.2017.08.014⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: 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)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01593402

DOI: 10.1016/j.jeconom.2017.08.014

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().