• Media type: E-Book
  • Title: Volatility Spillovers and Heavy Tails : A Large T-Vector Autoregressive Approach
  • Contributor: Barbaglia, Luca [Author]; Croux, Christophe [Other]; Wilms, Ines [Other]
  • Published: [S.l.]: SSRN, [2017]
  • Published in: KBI_1716
  • Extent: 1 Online-Ressource (27 p)
  • Language: English
  • DOI: 10.2139/ssrn.3068730
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments August 2017 erstellt
  • Description: Volatility is a key measure of risk in financial analysis. The high volatility of one financial asset today could affect the volatility of another asset tomorrow. These lagged effects among volatilities - which we call volatility spillovers - are studied using the Vector AutoRegressive (VAR) model. We account for the possible fat-tailed distribution of the VAR model errors using a VAR model with errors following a multivariate Student t-distribution with unknown degrees of freedom. Moreover, we study volatility spillovers among a large number of assets. To this end, we use penalized estimation of the VAR model with t-distributed errors. We study volatility spillovers among energy, biofuel and agricultural commodities and reveal bidirectional volatility spillovers between energy and biofuel, and between energy and agricultural commodities
  • Access State: Open Access