Ekuota predicited it. But let’s go in order.
The purchase decisions of the raw materials are associated with a prospective analysis of their quotations on the international markets. The techniques used for forecasting of future prices are the most disparate.
Some are effective, others less.
Those of Ekuota are effective: we apply prospective scenario evaluation intruments based on probabilistic methodologies. It is a statistical model that produces accurate, robust and scientifically valid estimates.
The estimates that Ekuota provides to companies are the support to make effective operational decisions for the purchase of raw materials, in terms of:
- timing (when to make the purchase).
What did we foresee?
How can one evaluate the accuracy of predictive estimates? There are two basic parameters: the scientific validity of the estimation generation model and how transparent and timely the information is.
On a monthly basis, Ekuota publishes the forecast scenario for metal prices quoted on the LME (the service also provides forecasts on the trend of currencies).
In the January 2018 report, we made forecasts for copper, aluminum, nickel, and zinc for the beginning of February.
Let’s compare the estimate (ex ante) on the trend of the price of copper, with what was actually realized on the market (ex post).
Ekuota had foreseen a price range between 6,458 and 8,065 (quotation Cash USD / Ton).
The probabilistic scenario is represented in the image aside, where a probability is associated for each level of quotation. The price range is divided into tenth, fiftieth and ninetieth percentiles. Furthermore, the final indication of Ekuota was of a neutral Outlook (the short-term vision was expected to be stable).
What happened on the market?
Short digression. We have just seen the ex-ante estimates made public by Ekuota. Remember? “How can one evaluate the accuracy of predictive estimates?” One of the parameters is transparency: ex ante, Ekuota has publicly exposed its forecasts.
At the beginning of January, we gave stable market indicators. The company could therefore have maintained a neutral attitude: as no significant price increases were expected, it would not have been necessary to stipulate hedges. On the other hand, as no declines were hypothesized, it would not have been necessary to postpone purchases.
The indication of Ekuota was therefore to distribute the purchases evenly over the month.
But to test the facts, what really happened on the copper market?
Forecast fulfilled. In January, the average price of copper was 7.074.
The company that followed the indication to dilute purchases benefited. Specifically, it saved 1.5%, that is the difference between 7,181 USD / Ton (price of 2 January) and the average price of the month of January.
WE TOLD YOU!
Why was Ekuota’s forecast accurate?
As already explained, we apply assessment tools for the prospective scenario, based on probabilistic methodologies. It is a statistical model that produces accurate, robust and scientifically validated estimates. In summary, that work and are useful.
In the case just seen of the estimates on the price of metals, the reliability of the instrument (and therefore the quality and reliability of the forecast) is given by two indicators:
- The Mape (the mean of absolute error);
- The accuracy of the estimate (1-MAPE).
In the table below, we show the estimates published monthly in the Ekuota reports.
Verba volant, scripta manent. On the proof of the facts, the data (ex ante estimates & real ex post prices) demonstrate the quality and reliability of our forecasts. Target centered.
The tool developed by Ekuota can be directly used online.
It is a service that offers constantly updated estimates on metals and currencies markets.
It is a service that allows companies to improve their financial and economic margins.
… and do not say that we didn’t tell you!