In the first half of 2018 Ekuota has published reports on currencies and metal prices with indications on the expected future scenarios of quotations. The analysis contain indications on the expected trend (neutral, increase, decrease) and on the main risk indicators.
Ekuota bases its analysis on advanced statistical models that use financial market data to obtain useful indications for taking the right decisions on financial strategies. The statistical models generate future probability distributions for market quotations. Ekuota provides its customers with direct access, via the platform, to reports and forecasting tools.
How can we evaluate the goodness of predictive estimates? There are two fundamental parameters:
- the scientific validity of the estimates generation model
- the transparency and the precision of the information.
The Ekuota algorithms determine a range within which exchange rates are expected to fluctuate. Graphs 1 and 2 represent the expected range for the Euro/USD exchange rate and for the copper price in the Ekuota analyzes for the first half of 2018.
The expected range is a price range consisting of a minimum level, a maximum level and an average value (10th, 50th and 90th percentile). It is a forecast with an horizon of one month after the date of publication. That is the estimate valid until the end of the month following the date of publication.
Graph 1: a comparison between the range provided by Ekuota and the actual value of the Euro/Dollar exchange rate (in the period 19/01/18 – 04/07/18).
Graph 2: a comparison between the range provided by Ekuota and the actual price of copper (in the period 19/01/18 – 04/07/18) Source: LME cash $/ton.
It is clear that the actual values of the Euro-Dollar exchange rate and the copper price have always remained within the expected ranges. The price ranges set by Ekuota for each month have always been met.
Graphs 3 and 4 show the expected one-month moving averages (Average expected value – 50th percentile) and the realized moving averages (MM20) for the period.
Graph 3 shows that for the Euro / USD exchange rate the expected moving average was in every period close to the one achieved. The best result was recorded in April, with a difference of just 0,0027 between the expected average value and the realized moving average, while the worst result has been equal to 0,0253 (May).
Graph 3: a comparison between the average forecasted by Ekuota and the actual value of the Moving Average for the Euro/Dollar exchange rate (in the period 19/01/18 – 04/07/18).
Graph 4: a comparison between the average forecasted by Ekuota and the actual value of the Moving Average for the copper price (in the period 19/01/18 – 04/07/18) Source: LME cash $/ton.
For the copper price (see graph 4), the expected moving average was in every period very close to the one realised. The best result was recorded in March, with a difference of just 58 Dollars per ton between the expected average value and the realized moving average, while the worst result has been equal to 176 $/ton (May).
On the proof of the facts, Ekuota’s analysis has proved to be extremely accurate: deviations between the forecasts and the actual values are minimal.
Being reliable and transparent is our distinctive element.
That’s why we are proud to show the accuracy of our forecasts.
The goodness of our insights
Once we have checked the accuracy and reliability of our instruments, let’s focus on their usefulness.
Graph 5: a comparison among the average forecasted by Ekuota, the actual value of the Moving Average and the daily copper price (in the period 19/01/18 – 04/07/18) Source: LME cash $/ton.
When the forecast provided by Ekuota is higher than the price of the day, the indication is to buy.
Graph 6: the strategy provided by Ekuota recommends to buy when the price is below the expected average (Average Expected Value – 50th percentile).
Let’s look at copper: in January, the average forecast was equal to $ 7.139 but the market price has been lower for 18 days. Buying copper in the days in which the market price has been lower than the average monthly estimate, produced a monthly savings of $ 14.47 per ton. In the six months considered, the total savings amounted to $ 333.7 / ton (see table below).
Every month, Ekuota publishes a report with a list of selected covers based on the best odds of positive results. The validity of these forecasts is measurable: the month following the publication, it is possible to compare the results to see what happened and how accurate the suggested hedging strategies were.
Requesting accuracy and expecting effectiveness is the need of modern, competitive companies that do not want to passively undergo the fluctuations of the financial markets. And that’s why we make transparency our absolute priority: ex ante, Ekuota publicly exposes its forecast to allow our customers to evaluate our work.
In conclusion, it can be said that the estimates provided by Ekuota have a considerable effectiveness.
Read the full report here
