Metal Price Forecasting – An Econometric Modelling Method

Metal Price Forecasting – An Econometric Modelling Approach

Steel price forecasting is relatively elementary to all financial commitment decisions in the iron and metal sector. Latest volatility in metal price ranges even so has been unparalleled. The global metal marketplaces noticed selling prices for hot rolled steel coil – really much a ‘benchmark’ steel product – increase from below $600/tonne in the 1st quarter of 2008 to virtually ~$1000/tonne by mid-2008. Just a handful of months afterwards, by early 2009, the warm rolled coil price was under $500/tonne, with similar price oscillations observed for reinforcing steel bar. This kind of wild and unexpected swings in the global metal price have seldom if ever been witnessed in advance of.

Price expectations

For some months immediately after the onset of the crisis, it was felt that it would be many decades or even for a longer time just before costs would return to the heady ranges of mid-2008. But in the January 2011, conversations once more turned to benchmark metal selling prices hitting $1000/tonne inside a issue of months. The scene is established hence for what may perhaps be really substantially extra variability in steel pricing in the long run than has been evident in the previous. In these instances, the means to correctly choose long term steel price actions turns into nonetheless more challenging.

An econometric price forecasting model

A statistical strategy to price forecasting can be manufactured, employing econometric modelling approaches. Econometrics are defined as the software of mathematics and statistical solutions to the evaluation of economic details, so the solution ought to be perfectly suited to the job. On this foundation, a mathematical model was formulated by MCI whereby:

  • regular historic selling prices for hot rolled steel coil and reinforcing bar ended up gathered across a 16 12 months time horizon
  • month-to-month charges were also collected for a selection of commodities, which includes crude oil (as an indicator of commodity prices, frequently), natural fuel (as an significant electric power source for metal pants), thermal coal (as an essential gasoline e.g. for steel power plants), metallurgical coal (used in the blast furnace), electrical power price ranges (made use of to power electrical arc furnaces), iron ore (as a dominant source of iron units for fundamental oxygen steel producing), ferrous scrap (as a dominant resource of iron units for electric steel making)
  • statistical correlations (i.e. the mathematical model) ended up proven in between the metal items on the a person hand and the commodity costs on the other.

Correlating variables

The methods previously mentioned authorized a model to be produced amongst historic price of warm rolled steel coil and rebar and the other commodity selling prices. The strategy showed that some components this sort of as coal and scrap prices correlated incredibly properly with the historic steel price, even though other price factors (e.g. electrical energy rates) did not.

Searching forward

Hunting ahead, unbiased estimates of long run commodity rates had been received from foremost resources this kind of as the World Bank and the Strength Facts Administration. These forecasts ended up then plugged into the mathematical model received over. The end result of this econometric modelling solution suggests that:

  • the forward projection is for taken care of somewhat high upcoming scorching rolled coil and metal rebar prices, with
  • regular rates remaining nicely higher than pre-crisis concentrations from now to 2015
  • prices keeping reasonably continual throughout 2011 to 2013
  • additional price rises expected in 2014 and 2015, which will elevate f.o.b. very hot rolled coil / reinforcing costs some $150 for each tonne in the medium-term
  • but with out return to a scenario involving f.o.b. steel price ranges at $1000-$1100/tonne [prior to 2016].

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