How Intratec Primary Commodity Prices is powered by Artificil Inteligence
About Our AI Powered Products
Intratec relies upon machine learning and cloud computing to extract and process a vast amount of official trade data automatically. All data pulled together is thoroughly double checked by Intratec team, so that reliable series are presented to help subscribers evaluate prices and identify trends in key markets.
When dealing with huge amounts of data, some tasks cannot be done by humans because it is not reliable. Intratec Primary Commodity Prices rely on heavy use of the latest techniques in data processing and data science to save time and effort during data manipulation, so our analysts can focus on the analyses that are critical for data quality. This combination ensures the most accurate data possible.
A robust automatic system was developed over years to prevent human errors on data collection. Data are automatically extracted from sources whenever possible. Some specific sources do not support automatic collection. In such cases, advanced data processing schemes are used to check data manually collected and alarm if, by any reason, there seems to have been errors during collection. Whenever this happens, the collected data is double checked by a second person and data are collected again if the error is confirmed.
When collecting and reconciling data from various sources, it is not unusual to find inconsistencies among the data collected. Statistical analyses techniques are employed to find and alarm inconsistency issues. These issues are reviewed by our analysts and resolved, either by
Recollecting data from a source;
Using further statistical analysis techniques to reconcile the data; or
Using market expertise and research to reconcile the data.
Since Intratec Primary Commodity Prices relies on official trade statistics released by national institutions, some issues need to be overcome. The main issue relates to the time gap between transactions and trade statistics release. The trade statistics related to a given month are released from one to three months after it ends. That means recent data may lack and that can be a critical issue to market analysis derived thereof.
Therefore, Intratec Primary Commodity Prices relies on predictive modelling to estimate recent prices while sources do not release official statistics. Whenever a price is obtained through a predictive model, it is indicated as preliminary. Preliminary prices are reviewed upon the release of official trade statistics by the respective sources. Predictive modelling is employed for price forecasting as well.
Predictive models use a combination of statistical analysis and machine learning algorithms based on the expertise of Intratec analysts to predict prices from historical data gathered over the past 15 years. The models consider a host of market fundamentals that surround the commodities prices, including, for instance, raw material prices, energy costs, inflation rates.
Moreover, the models employed can learn from past outcomes. As new data are released, they are incorporated into the models so they can learn over time and become more and more accurate. Therefore, Intratec Primary Commodity Prices subscribers can benefit from estimates that will continuously improve over time.
Updated on: 01/30/2023