Non-parametric news impact curve: a variational approach - HAL-SHS - Sciences de l'Homme et de la Société Accéder directement au contenu
Autre Publication Scientifique Année : 2017

Non-parametric news impact curve: a variational approach

Matthieu Garcin
Clément Goulet
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Résumé

In this paper, we propose an innovative methodology for modelling the news impact curve. The news impact curve provides a non-linear relation between past returns and current volatility and thus enables to forecast volatility. Our news impact curve is the solution of a dynamic optimization problem based on variational calculus. Consequently, it is a non-parametric and smooth curve. To our knowledge, this is the first time that such a method is used for volatility modelling. Applications on simulated heteroskedastic processes as well as on financial data show a better accuracy in estimation and forecast for this approach than for standard parametric (symmetric or asymmetric ARCH) or non-parametric (Kernel-ARCH) econometric techniques.
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Dates et versions

halshs-01244292 , version 1 (15-12-2015)
halshs-01244292 , version 2 (27-01-2017)
halshs-01244292 , version 3 (06-03-2017)

Identifiants

  • HAL Id : halshs-01244292 , version 3

Citer

Matthieu Garcin, Clément Goulet. Non-parametric news impact curve: a variational approach. 2017. ⟨halshs-01244292v3⟩
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