hal.structure.identifier | Dauphine Recherches en Management [DRM] | |
dc.contributor.author | Le Fol, Gaëlle | |
dc.date.accessioned | 2021-10-02T09:54:05Z | |
dc.date.available | 2021-10-02T09:54:05Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | https://basepub.dauphine.psl.eu/handle/123456789/21915 | |
dc.language.iso | en | en |
dc.subject.ddc | 332 | en |
dc.subject.classificationjel | E.E4.E44 | en |
dc.subject.classificationjel | C.C5.C53 | en |
dc.title | Forecasting Intra-daily Liquidity in Large Panels | en |
dc.type | Communication / Conférence | |
dc.description.abstracten | In this work we propose a forecasting methodology suitable for large panels of liquidity measures based on exploiting the cross-sectional commonality structure of volume. We begin by providing a number of stylized facts for a panel comprising the CAC40 constituents. We document the presence of a strong common component that is correlated with market volatility. Moreover, after the common component is filtered out, we find evidence of dependence across a number of ticker pairs. These stylized facts motivate us to propose a hybrid forecasting model that is made up of a factor and sparse vector-autoregressive components. We estimate such a model by combining PCA (Principal Component Analysis) and LASSO (Least Absolute Shrinkage and Selection Operator) estimation. We apply our methodology to forecast the intra-daily liquidity of the CAC40 constituents across different intra-daily frequencies. Results show that our approach systematically improves forecasting accuracy over a number of univariate and multivariate benchmarks. | en |
dc.subject.ddclabel | Bourse, Marchés financiers. Taux d’intérêt – Stocks options – Optimisation mathématique – Analyse financière | en |
dc.relation.conftitle | AMF | en |
dc.relation.confdate | 2019-06 | |
dc.relation.confcity | Paris | en |
dc.relation.confcountry | France | en |
dc.relation.forthcoming | non | en |
dc.description.ssrncandidate | non | |
dc.description.halcandidate | oui | en |
dc.description.readership | non-recherche | en |
dc.description.audience | International | en |
dc.relation.Isversionofjnlpeerreviewed | non | en |
dc.date.updated | 2021-09-29T15:55:34Z | |
dc.subject.classificationjelHAL | E - Macroeconomics and Monetary Economics::E4 - Money and Interest Rates::E44 - Financial Markets and the Macroeconomy | en |
dc.subject.classificationjelHAL | C - Mathematical and Quantitative Methods::C5 - Econometric Modeling::C53 - Forecasting and Prediction Methods; Simulation Methods | en |
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