Showing 1 - 8 of 8
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...
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static forecasts, as well as different measures of forecast errors. Finally, we propose a new class of models which combine …
Persistent link: https://www.econbiz.de/10009382869
distribution by asking whether ethanol returns can be used to forecast different parts of field crops returns distribution, or vice … Squares. Forecast evaluation relies on quantile-weighed scoring rules, which identify regions of the distribution of interest … by using field crops returns. On the contrary, there is no evidence that ethanol can be used to forecast any region of …
Persistent link: https://www.econbiz.de/10009737363
Putting a price on carbon - with taxes or developing carbon markets - is a widely used policy measure to achieve the target of net-zero emissions by 2050. This paper tackles the issue of producing point, direction-of-change, and density forecasts for the monthly real price of carbon within the...
Persistent link: https://www.econbiz.de/10014470036
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....
Persistent link: https://www.econbiz.de/10011438638
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...
Persistent link: https://www.econbiz.de/10013254444