  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.

Statistical Finance