Article Sidebar
Published:
Aug 5, 2022Article Details
Authors who publish in this journal agree to the following terms:
- The authors retain copyright and grant the journal the right of first publication, with the work then available concurrently, under a Creative Commons Attribution License allowing others to share the work while acknowledging authorship and initial publication in this journal.
- Authors may enter into additional and separate contractual agreements for the non-exclusive distribution of the printed version of the work by the journal (e.g., institutional deposit or publication in a book), together with an acknowledgment acknowledging its publication initial in this review.
- Authors have the right and are encouraged to publish their work online (e.g., in an institutional repository or on an institution's website) before and during the submission process, as this can lead to meaningful exchanges as well than to more, more quickly, references to the published work (See The Effect of Open Access ).
Main Article Content
Modélisation de la volatilité des rendements Bitcoin par les modèles GARCH non paramétriques
Abstract
Objectif: L’objectif de cet article est de mettre en évidence l'efficacité du modèle GARCH non paramétrique pour la prédiction des prix futurs du Bitcoin.
Méthodologie: L’utilisation de modèles GARCH paramétriques pour caractériser la volatilité des rendements Bitcoin est très utilisé dans la littérature empirique. Alternativement, nous considérons une approche non paramétrique pour modéliser et prévoir la volatilité des rendements Bitcoin.
Résultats: Nous montrons que la prévision de volatilité du modèle GARCH non paramétrique donne des performances supérieures par rapport à une classe étendue de modèles GARCH paramétriques.
Originalité/pertinence : L’amélioration de la précision des prévisions de la volatilité des rendements Bitcoin basée sur le modèle GARCH non paramétrique suggère que cette méthode offre une alternative attrayante et viable par rapport aux modèles paramétriques GARCH couramment utilisés.
English title: Modelling the volatility of Bitcoin returns using Nonparametric GARCH models
Objective: The purpose of this paper is to demonstrate the effectiveness of the nonparametric GARCH model for the prediction of future Bitcoin prices.
Methodology: The use of parametric GARCH models to characterize the volatility of Bitcoin returns iswidely used in the empirical literature. Alternatively, we consider a non-parametric approach to model and forecast the volatility of Bitcoin returns.
Results: We show that the volatility forecast of the nonparametric GARCH model yields superiorperformance compared to an extended class of parametric GARCH models.
Originality / relevance: The improved accuracy of forecasting the volatility of Bitcoin returns based on the nonparametric GARCH model suggests that this method offers an attractive and viable alternative to commonly used GARCH parametric models..
