The MachineTrader™ team likes to keep abreast of breaking news.  The headline news service we use follows 80+ business publications and provides hundreds of articles per hour, with a lag time of approximately 4 minutes. Our proprietary NLP (Natural Language Processing) technology is used to transform information into digital inputs that can be understood and processed by ML (Machine Learning) software. NLP is used to assess the positive or negative impact of a recent array of words when compared with the impact of other word arrays that have taken place in the past.  After the assessment, the sentiment of the article is scored on a -1.0 to +1.0 scale, with -1.0 being perfectly negative and +1.0 being perfectly positive. Typical range is 0.2 - 0.3.  

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As an example, our NLP technology could “listen in” on an earnings call, translate the spoken words into text arrays, and assess the position or negative impact of the text array when compared with past earnings calls. The “sentiment” of the text is recorded in a “column” of digital data with a numerical range spanning from -1.0 to +1. So a sentiment score of 0.975 would be seen as highly positive relative to past earnings calls.  A similar process is applied to news articles, assessing the text arrays, and assigning the sentiment score.  

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However, as any experienced trader knows, positive “sentiments” may or or may not translate into an increase in the price of the given equity. The job of machine learning software is to search for correlations between the digital inputs and that particular column of data in conjunction with many other data elements at that precise second of time.

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In addition to seeing MachineTrader’s news sentiment scoring on your Insight - News tab, the positive, negative, or neutral sentiment ratings are also shown on each headline and news display throughout the MachineTrader™ platform.  ‍

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