Article ID Journal Published Year Pages File Type
1140282 Mathematics and Computers in Simulation 2008 13 Pages PDF
Abstract
Within the industrial metals industry, there has been a great deal of interest surrounding trends in metals market volatility over time. This paper uses a rolling AR(1)-GARCH(1,1) model to estimate and forecast the volatility processes for daily returns on the futures prices of two important non-ferrous metals, namely aluminium and copper. The rolling models are used to examine how the processes driving aluminium and copper returns volatility have evolved over a long sample. The variation over time seen in the volatility processes, as modelled by GARCH, suggest that, while volatility in returns has not necessarily increased, the conditional volatility process in metals markets is itself time-varying when analysed over a long horizon.
Related Topics
Physical Sciences and Engineering Engineering Control and Systems Engineering
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