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How the maths can help you understand the price behaviour of base metals

It is often difficult to forecast a metal or commodity price accurately on past price history alone. However the underlying drivers that influence a metal or commodity price, like stock levels and the global industrial production cycle, can often be determined with a much greater degree of accuracy. For this reason, factor models on reliable forecast-able drivers tend to outperform other methods of forecasting like ARIMA which look at price history alone.

Factor models are also very helpful in scenario analysis where one can make different assumptions to the drivers and then see what effect they have on the modelled price.

Metal Price Analytics builds factor models for base metals and other commodities which then can be used to calculate the price from the underlying driver forecasts.

Metal Price Analytics delivers the models as an interactive Excel workbook containing the factor model with a base case forecast for each of the underlying drivers to give the forecast metal or commodity price up to 2023.

As  the models are interactive,  the user can enter his/her own driver forecast values and see how that will effect the metal or commodity price.