Steel Price Forecasting – An Econometric Modelling ApproachOn November 14, 2016 by abah guru
Steel price forecasting is somewhat fundamental to all investment decisions in the iron and steel sector. Recent volatility in steel prices however has been unprecedented. The international steel markets saw prices for hot rolled steel coil – very much a ‘benchmark’ steel product – rise from under $600/tonne in the first quarter of 2008 to almost ~$1000/tonne by mid-2008. Just a few months later, by early 2009, the hot rolled coil price was under $500/tonne, with similar price oscillations seen for reinforcing steel bar. Such wild and sudden swings in the international steel price have rarely if ever been witnessed before.
For some months after the onset of the crisis, it was felt that it would be several years or even longer before prices would return to the heady levels of mid-2008. But in the January 2011, discussions again turned to benchmark steel prices hitting $1000/tonne within a matter of months. The scene is set therefore for what may be very much more variability in steel pricing in the future than has been evident in the past. In these circumstances, the ability to correctly judge future steel price movements becomes yet more difficult.
An econometric price forecasting model
A statistical approach to price forecasting can be made, using econometric modelling techniques. Econometrics are defined as the application of mathematics and statistical methods to the analysis of economic data, so the approach should be well suited to the task. On this basis, a mathematical model was developed by MCI whereby:
- monthly historic prices for hot rolled steel coil and reinforcing bar were gathered across a 16 year time horizon
- monthly prices were also gathered for a range of commodities, including crude oil (as an indicator of commodity prices, generally), natural gas (as an important power source for steel pants), thermal coal (as an important fuel e.g. for steel power plants), metallurgical coal (used in the blast furnace), electricity prices (used to power electric arc furnaces), iron ore (as a dominant source of iron units for basic oxygen steel making), ferrous scrap (as a dominant source of iron units for electric steel making)
- statistical correlations (i.e. the mathematical model) were established between the steel products on the one hand; and the commodity prices on the other.
The steps above allowed a model to be developed between historic price of hot rolled steel coil and rebar; and the other commodity prices. The approach showed that some factors such as coal and scrap prices correlated very well with the historic steel price, whilst other price factors (e.g. electricity prices) did not.
Looking forward, independent estimates of future commodity prices were obtained from leading sources such as the World Bank and the Energy Information Administration. These forecasts were then plugged into the mathematical model obtained above. The result of this econometric modelling approach indicates that:
- the forward projection is for maintained relatively high future hot rolled coil and steel rebar prices, with
- average prices remaining well above pre-crisis levels from now to 2015
- prices staying relatively constant across 2011 to 2013
- further price rises expected in 2014 and 2015, which will raise f.o.b. hot rolled coil / reinforcing prices some $150 per tonne in the medium-term
- but without return to a scenario involving f.o.b. steel prices at $1000-$1100/tonne [prior to 2016].