We estimate dynamic conditional correlations between 10 commodities futures returns in energy, metals and agriculture markets over the period 1998-2014 with a DCC-GARCH model. We look at the factors influencing those correlations, adopting a pooled mean group (PMG) estimator. Macroeconomic...

We present a weekly structural Vector Autoregressive (VAR) model of the US crude oil market. Exploiting weekly data we can explain short-run crude oil price dynamics, including those related with the COVID-19 pandemic and with the Russia's invasion of Ukraine. The model is set identified with a...

This study investigates the effects of oil price shocks on volatility of selected agricultural and metal commodities. To achieve this goal, we decompose an oil price shock to its underlying components, including macroeconomics and oil specific shocks. The applied methodology is the structural...

The identification of the forces that drive stock returns and the dynamics of their associated volatilities is a major concern in empirical economics and finance. This analysis is particularly relevant for determining optimal hedging strategies based on whether shocks to the volatilities of...

This paper provides an analysis of the link between the global market for crude oil and oil futures risk premium at the aggregate level. It off ers empirical evidence on whether the compensation for risk required by the speculators depends on the type of the structural shock of interest....

This study investigates the price volatility of metals, using the GARCH and GJR models. First we examine the persistence of volatility and the leverage effect across metal markets taking into account the presence of outliers, and second we estimate the effects of oil price shocks on the price...