Entity Recognition


The NLP process identifies stock symbols, company names, abbreviations of names, and relevant financial events in every message. By this method each message can be assigned to one or more financial titles which can be securities, indices, currency pairs or commodities like gold or oil. The noise level is drastically reduced by using curated “title-handle maps” which provide information about source-title relationships. About 70 percent of the messages are filtered which improves data quality by reducing noise.

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StockPulse analyzes communication on financial topics in publicly accessible social media and news sources. Software evaluates hundreds of thousands of opinions and news articles every day and shows at a glance, how much and in what kind of mood people discuss about financial markets. Using latest Big Data technology, communication on stocks, indices, commodities, currency pairs and major market events is monitored and evaluated in real-time 24/7. Moreover, the software automatically generates buy and sell signals for different asset classes. By now, the database of StockPulse contains historical data of more than six years, enabling comprehensive backtestings. The software and trading models created by StockPulse were reviewed and confirmed by independent scientific studies.\n

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