Words to Trade By
Going beneath the headlines to help traders, quants and asset managers create predictive and profitable trading strategies. Dow Jones and The Wall Street Journal move markets every day around the world with breaking news. But executing trades based on only headlines is just part of the opportunity. What about the trends that lie behind the news and beneath the headlines? What if you could add news to existing trading strategies or build entirely new ones by analyzing hidden patterns in the news―the kind of discovery that merely reading headlines as they arrive can’t produce? Dow Jones Lexicon allows you to find new opportunities that others miss.
Beneath the Headlines: News Is More Than Words
Dow Jones Lexicon, powered by derived data technology, gives institutional salespeople, traders, portfolio managers and asset managers the building blocks to add news into their own trading models. It consists of:
An intelligent engine that processes Dow Jones content
"Dictionaries"―word lists that are configured for positive, negative and neutral sentiment and are passed across Dow Jones content
Derived data technology allows you to look at content in a quantitative way. As a news story is published, words are coded based on sentiment (positive, negative or neutral); strong words vs. weak words; uncertain words and words that are litigious. As these words appear in news stories, they are analyzed to see how frequently and where they are used. Institutional salespeople and traders take these numbers to build their own indicators and use them as part of trading models.
Portfolio and asset managers can also benefit from Dow Jones Lexicon. This quantitative tool gives them the ability to add news to their multi-factor models, increasing the profitability of their electronic trading strategies and, in turn, their clients’ portfolios.
Pairing
Lexicon with News Feeds
Dow Jones Lexicon is available as an XML-based feed in real-time or as a batch at the end of the day and is sold as an add-on to Dow Jones News & Archives.
Going beneath the headlines to help traders, quants and asset managers create predictive and profitable trading strategies. Dow Jones and The Wall Street Journal move markets every day around the world with breaking news. But executing trades based on only headlines is just part of the opportunity. What about the trends that lie behind the news and beneath the headlines? What if you could add news to existing trading strategies or build entirely new ones by analyzing hidden patterns in the news―the kind of discovery that merely reading headlines as they arrive can’t produce? Dow Jones Lexicon allows you to find new opportunities that others miss.
Beneath the Headlines: News Is More Than Words
Dow Jones Lexicon, powered by derived data technology, gives institutional salespeople, traders, portfolio managers and asset managers the building blocks to add news into their own trading models. It consists of:
An intelligent engine that processes Dow Jones content
"Dictionaries"―word lists that are configured for positive, negative and neutral sentiment and are passed across Dow Jones content
Derived data technology allows you to look at content in a quantitative way. As a news story is published, words are coded based on sentiment (positive, negative or neutral); strong words vs. weak words; uncertain words and words that are litigious. As these words appear in news stories, they are analyzed to see how frequently and where they are used. Institutional salespeople and traders take these numbers to build their own indicators and use them as part of trading models.
Portfolio and asset managers can also benefit from Dow Jones Lexicon. This quantitative tool gives them the ability to add news to their multi-factor models, increasing the profitability of their electronic trading strategies and, in turn, their clients’ portfolios.
Pairing
Lexicon with News FeedsDow Jones Lexicon is available as an XML-based feed in real-time or as a batch at the end of the day and is sold as an add-on to Dow Jones News & Archives.










