Title: Volatility spillovers and heavy tails: A large t-vector autoregressive approach
Authors: Luca Barbaglia - KU Leuven (Belgium) [presenting]
Christophe Croux - Edhec Business School (France)
Ines Wilms - Maastricht University (Netherlands)
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, with important implications for portfolio management. 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 a large number of energy, biofuel and agricultural commodities. Using network analysis, we reveal bidirectional volatility spillovers between energy and biofuel, and between energy and agriculture commodities.