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Non-parametric news impact curve: a variational approach

Abstract : 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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Submitted on : Monday, March 6, 2017 - 3:24:42 PM
Last modification on : Sunday, January 19, 2020 - 6:38:27 PM
Long-term archiving on: : Wednesday, June 7, 2017 - 2:32:21 PM


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  • HAL Id : halshs-01244292, version 3



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



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