VS-LTGARCHX: A Flexible Variable Selection in Log-TGARCHX Models

Samir Orujov, Victor Elvira (), Audrey Poterie (), Farid Rajabov and Francois Septier ()
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Samir Orujov: LMBA - Laboratoire de Mathématiques de Bretagne Atlantique - UBS - Université de Bretagne Sud - UBO EPE - Université de Brest - CNRS - Centre National de la Recherche Scientifique
Victor Elvira: The University of Edinburgh
Audrey Poterie: LMBA - Laboratoire de Mathématiques de Bretagne Atlantique - UBS - Université de Bretagne Sud - UBO EPE - Université de Brest - CNRS - Centre National de la Recherche Scientifique
Farid Rajabov: UCL - University College London [UCL]
Francois Septier: LMBA - Laboratoire de Mathématiques de Bretagne Atlantique - UBS - Université de Bretagne Sud - UBO EPE - Université de Brest - CNRS - Centre National de la Recherche Scientifique, UBS - Université de Bretagne Sud

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Abstract: The log-TGARCHX model is less restrictive in terms of the inclusion of exogenous variables and asymmetry lags compared to the GARCHX model. Nevertheless, adding less (or more) covariates than necessary may lead to under- or overfitting, respectively. In this context, we propose a new algorithm, called VS-LTGARCHX, which incorporates a variable selection procedure into the log-TGARCHX estimation process. Furthermore, the VS-LTGARCHX algorithm is applied to extremely volatile BTC markets using 42 conditioning variables. Interestingly, our results show that the VS-LTGARCHX models outperform benchmark models, namely the log-GARCH(1,1) and log-TGARCHX(1,1) models, in one-step-ahead forecasting.

Keywords: variable selection; Bitcoin volatility; log-GARCHX; GARCH (search for similar items in EconPapers)
Date: 2025-05-16
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-mac
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Published in Journal of Time Series Econometrics, 2025, pp.1-34. ⟨10.1515/jtse-2023-0035⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04283159

DOI: 10.1515/jtse-2023-0035

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