Resin Price Forecaster Leverages AI, Machine Learning to Predict Trends

Resin Price Forecaster Leverages AI, Machine Learning to Predict Trends

Worldwide resin rates have been volatile of late, mostly due to the fact that of factors related to COVID-19. From a historical point of view, volatility is the rule, not the exception. It is baked into prices, sustained by various factors fixated feedstock and upstream commodity costs, according to MLT Analytics. So why is it that existing cost projections tend to be fairly direct despite historical price instability? This concern captivated the creators of MLT Analytics, who wondered if there was some rational means of presenting volatility into resin cost forecasting as observed in historic data.

The response is two-fold, according to the company:

” Long-term oil and gas price projections, from the United States Energy Information Administration, for example, absence volatility. They fall or increase, depending upon the situation, in a reasonably linear style. What we are doing is presenting volatility into our forecasts based on past feedstock patterns and assumptions of future market developments such as peak oil. This, in turn, presents volatility into the resin cost forecasts,” described Stephen Moore, co-founder and CEO of MLT Analytics. “We examine multiple feedstock and use device discovering to explore their connections with resins by type and region or country where they are sold,” included Moore, who is also a long time contributor to PlasticsToday.

” Unless the data you are feeding into the forecasting model makes sense from market and economic perspectives, your projection, regrettably, will look like a not likely outcome,” cautioned Moore. “Thats where the decades of market proficiency our team has collected ends up being of ultimate value.”

This material was originally published here.


It is baked into rates, sustained by different aspects focused on feedstock and upstream commodity rates, according to MLT Analytics. Why is it that existing cost forecasts tend to be fairly linear in spite of historic cost instability?” Long-term oil and gas price projections, from the United States Energy Information Administration, for example, absence volatility.

MLT AnalyticsWhile plastics are the beginning point for MLT Analytics, pricing for any kind of product, including non-plastic products, can be in theory forecast once historical prices are associated with information for key influencers.

When the forecasting design has been set up, the current historical data is fed into the model as it appears, which serves to further fine-tune the forecast. Further, “back-casting,” as suggested in the graphic by the part of the blue line overlapping the red historical line, is a method of verifying the validity of the forecast. A close overlap of the historical and back-casted data is evidence that the modeling is working from an analytical perspective.


Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top