Forecasting the intra-day effective bid ask spread by combining density forecasts

Malick Fall (), Waël Louhichi () and Jean-Laurent Viviani ()
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Malick Fall: CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique
Waël Louhichi: ESSCA Research Lab - ESSCA - ESSCA – École supérieure des sciences commerciales d'Angers = ESSCA Business School
Jean-Laurent Viviani: CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique

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Abstract: The bid-ask spread refers to the tightness dimension of liquidity and can be used as a proxy for transaction costs. Despite the importance of the bid-ask spread in the financial literature, few studies have investigated its forecastability. We propose a new methodology to predict the bid ask spread by combining density forecasts of two types of models: Multiplicative Errors Models and ARMA-GARCH models. Our method is employed to predict the effective intra-day bid-ask spread series of all shares pertaining to the CAC40 index. Using a one-step-ahead out-of-sample framework, we resort on the Model Confidence Set procedure of Hansen et al. (2004) to classify models and we found that the proposed model appears to beat all the benchmark specifications.

Keywords: Effective bid-ask spread; High-Frequency; Multiplicative Errors Models; Forecasting (search for similar items in EconPapers)
Date: 2021-10-27
New Economics Papers: this item is included in nep-cwa, nep-for, nep-mst and nep-ore
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Published in Applied Economics, 2021, 53 (50), pp.5772-5792. ⟨10.1080/00036846.2021.1929821⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03257268

DOI: 10.1080/00036846.2021.1929821

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