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Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach

Luca Barbaglia, Christophe Croux and Ines Wilms ()

Papers from arXiv.org

Abstract: 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.

New Economics Papers: this item is included in nep-ecm, nep-ets and nep-rmg
Date: 2017-08
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http://arxiv.org/pdf/1708.02073 Latest version (application/pdf)

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Working Paper: Volatility spillovers and heavy tails: a large t-Vector AutoRegressive approach (2017) Downloads
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