Optimization and statistical methods for high frequency finance

Marc Hoffmann (), Mauricio Labadie, Charles-Albert Lehalle, Gilles Pagès (), Huyên Pham and Mathieu Rosenbaum ()
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Marc Hoffmann: CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Mauricio Labadie: Quantitative Research - EXQIM - EXclusive Quantitative Investment Management - EXQIM
Gilles Pagès: LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique
Huyên Pham: LMAP - Laboratoire de Mathématiques et de leurs Applications [Pau] - UPPA - Université de Pau et des Pays de l'Adour - CNRS - Centre National de la Recherche Scientifique
Mathieu Rosenbaum: LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique

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Abstract: High Frequency finance has recently evolved from statistical modeling and analysis of financial data – where the initial goal was to reproduce stylized facts and develop appropriate inference tools – toward trading optimization, where an agent seeks to execute an order (or a series of orders) in a stochastic environment that may react to the trading algorithm of the agent (market impact, invoentory). This context poses new scientific challenges addressed by the minisymposium OPSTAHF.

Date: 2013-05-27
Note: View the original document on HAL open archive server: https://hal.science/hal-01102785v1
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Published in SMAI 2013, May 2013, Seignosse, France. pp.219 - 228, ⟨10.1051/proc/201445022⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01102785

DOI: 10.1051/proc/201445022

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