This paper aims to examine the impacts of oil-price shocks on China's price levels. To that end, we develop a partial transmission input-output model that captures the uniqueness of the Chinese market. We hypothesize and simulate price control, market factors and technology substitution - the...

We develop a Bayesian Structural VAR (SVAR) model to study the relationship between different kinds of energy shocks and inflation dynamics in Europe. Specifically, we include in our specification two separate energy markets (oil and natural gas) and two target macroeconomic variables, measuring...

This paper develops a two-block Structural Vector Autoregression featuring time-varying parameters and stochastic volatility to estimate the changing spillover of global oil shocks into the Maltese economy during the period that goes from January 2008 to March 2022. The model is estimated by...

In this paper I have used copula functions to forecast the Value-at-Risk (VaR) of an equally weighted portfolio comprising a small cap stock index and a large cap stock index for the oil and gas industry. The following empirical questions have been analyzed: (i) are there nonnormalities in the...

This paper evaluates how different types of speculation affect the volatility of commodities' futures prices. We adopt four indexes of speculation: Working's T, the market share of non-commercial traders, the percentage of net long speculators over total open interest in future markets, which...

We study the effects of crude oil price shocks on the stock market volatility of the G7 economies. We rely on a structural VAR model to identify the causes underlying the oil price shocks and gauge the differential impact that oil supply and oil demand innovations have on financial volatility....

We study the impact of oil price shocks on US stock market volatility. We derive three different structural oil shock variables (i.e. aggregate demand, oil-supply, and oil-demand shocks) and relate them to stock market volatility, using bivariate structural VAR models, one for each oil price...

This paper analyses futures prices for four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) and five agricultural commodities (corn, oats, soybean oil, soybeans and wheat), over the period 1986-2010. Using CCC and DCC multivariate GARCH models, we find that...

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...

Since Russia's invasion of Ukraine, many countries have pledged to end or restrict their oil and gas imports to curtail Moscow's revenues and hinder its war effort. Thus, the European ministers agreed to trigger a cap on the gas price. To detect the importance of the price cap for gas, we...