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New Sentiment Analysis App Available on Bloomberg Professional Service

by Avi Mizrahi
  • Singapore based developer, InfoTrie announced today its FinSentS news analytics and sentiment analysis app is now available on Bloomberg's app portal, including sentiment analysis on the major FX pairs.
New Sentiment Analysis App Available on Bloomberg Professional Service
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Singapore-based developer, InfoTrie announced today its FinSentS news Analytics and sentiment analysis is now available on Bloomberg's app portal, a component of the Bloomberg professional service.

Sentiment analysis seems to be becoming more and more popular as a trading assistant tool. In 2013, Bloomberg was the first financial information platform to integrate real-time Twitter feeds directly into the investment workflows of market professionals. Last month, Thomson Reuters added that Twitter feeds have been added to its Eikon platform as well for sentiment analysis.

Sentiment analysis tools automatically read, score and transform news, blogs and tweets into numerical indicators to capture the mood of the market. Traders familiar with technical analysis can use sentiment indicators such as those of InfoTrie in a similar way to momentum indicators to track over-optimistic and over-pessimistic areas.

The FinSentS App is fed with Bloomberg's news content. It monitors in real-time the velocity at which news or rumors spread and processes about 40,000 Equities , the major FX pairs, commodities and coverage can be extended on demand.

finsents

FinSentS stands for Financial News and Sentiment Screener. Its statistical and semantic engine scans unstructured content to capture in real-time the sentiment from news, blogs and social media. Its sentiment scores can be integrated into trading strategies/algorithms, risk and compliance systems, or simply analysed to figure out the mood of any market or asset.

InfoTrie explains how the FinSentS sentiment engine works in four stages:

▪ It indexes extensively the web or any private source in a way similar to what a search engine does.

▪ Standard or bespoke sentiment algorithms read and analyze unstructured content automatically.

▪ The sentiment data is then correlated to asset prices to ensure consistency.

▪ Users are able to slice and dice through news content, to assess sentiment within a few seconds, and to feed downstream applications.

Bloomberg Logo

Singapore-based developer, InfoTrie announced today its FinSentS news Analytics and sentiment analysis is now available on Bloomberg's app portal, a component of the Bloomberg professional service.

Sentiment analysis seems to be becoming more and more popular as a trading assistant tool. In 2013, Bloomberg was the first financial information platform to integrate real-time Twitter feeds directly into the investment workflows of market professionals. Last month, Thomson Reuters added that Twitter feeds have been added to its Eikon platform as well for sentiment analysis.

Sentiment analysis tools automatically read, score and transform news, blogs and tweets into numerical indicators to capture the mood of the market. Traders familiar with technical analysis can use sentiment indicators such as those of InfoTrie in a similar way to momentum indicators to track over-optimistic and over-pessimistic areas.

The FinSentS App is fed with Bloomberg's news content. It monitors in real-time the velocity at which news or rumors spread and processes about 40,000 Equities , the major FX pairs, commodities and coverage can be extended on demand.

finsents

FinSentS stands for Financial News and Sentiment Screener. Its statistical and semantic engine scans unstructured content to capture in real-time the sentiment from news, blogs and social media. Its sentiment scores can be integrated into trading strategies/algorithms, risk and compliance systems, or simply analysed to figure out the mood of any market or asset.

InfoTrie explains how the FinSentS sentiment engine works in four stages:

▪ It indexes extensively the web or any private source in a way similar to what a search engine does.

▪ Standard or bespoke sentiment algorithms read and analyze unstructured content automatically.

▪ The sentiment data is then correlated to asset prices to ensure consistency.

▪ Users are able to slice and dice through news content, to assess sentiment within a few seconds, and to feed downstream applications.

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