Data that moves the markets
Machine Readable News and quantitative data:a powerful combination for quants and data scientists

As the exclusive provider of Reuters news to the global financial
marketplace, LSEG’s news service gives you access to Reuters’market-moving headlines, together with agenda-setting insightand commentary. With a focus on speed of delivery, providing
stories as they break, you gain the advantage of accessing thenews that matters, every day, for every major market sector. With
its 170-year history and reputation for trust and accuracy, Reuters’
2,000+ journalists, on the ground all over the world, are at theheart of our news service. In turn, LSEG’s quantitative analytics andcontent delivers everything you need to confidently optimise yourquantitative research and modelling workflows, focus your valuable
resources, and create, test and implement better strategies.
Our powerful offering enables you to achieve your goals througha combination of leading point-in-time content, empowering you to
backtest with precision in addition to deep-insight analytics and a data
management platform offering a high-quality, fully normalised database.
In particular, our datasets are complemented with RIC identifiers andPerm ID tags to make them easy to map and be inter-operable.

Explaining Machine Readable News (MRN)
Machine Readable News allows you to transform real-time news
into a feed your machine understands. LSEG’s programmatic news
feed solution is the only one in the industry that’s powered byaward-winning, trusted Reuters News. With our ability to analyseand scan news across 35,000 companies in real time, your teamcan research a large universe of companies and take advantage oftrading opportunities anywhere in the world.
We also use Machine Learning (ML) and natural language
processing (NLP) to deliver sophisticated news analytics linked toevery article in the MRN feed; whether you’re looking to inform
event-based trading on economic releases and exclusive M&A
news breaks, optimise quantitative investment strategies using
sentiment analysis or conduct market surveillance based on raw
news and associated metadata.

On the 11 January 2024, Reuters was first to report that Bain Capital and Hellman & Friedman were both vying to acquire DocuSign Inc, theprovider of online signature services with a supposed market value of approx $12.5 billion. DocuSign shares ended trading up 9.3% on the news.

Add Machine Readable News to your quant and data science toolkit
With Machine Readable News you get access to news content delivered across the latency spectrum from lessthan 3 milliseconds for our Ultra Low Latency Headline Feed to 1 day for aggregated news items with all updates.

Exploit signals in news for quantitative strategies andsystematic trading

Use sentiment to your advantage and uncoveractionable signals for your strategy

Increasingly, data scientists are finding wider use cases for using
news from generating alpha, mitigating risks and event prediction.
Our News Analytics package utilises cutting-edge NLP to produce
outputs that measure company sentiment, relevance and noveltyof text along with other valuable metadata that can enrich tradesignal detection for quant investment strategies, aid decisionmaking and supplement market surveillance.

LSEG provides news sentiment signals for real-time systematic
trading through to stock selection.

MRN is well suited for training ML models with an archive goingback to 2003; a global universe of 35,000+ companies, 90 fieldsof metadata and 40+ C&E topics.
We provide the tools to help you integrate other content setswith alpha signals buried below the surface. Our ML toolkit
for extracting entities and other metadata can be used across
our other text feeds that capture conference call transcripts,
research reports and filings; in addition to your internal emails,
research and other unstructured data.

Mitigate risk with early insight into market-moving news
Just the presence of news for a company can drive pricevolatility and impact profitability. However, simply stopping
trading whenever there is news isn’t practical. Our news
analytics provides meaning and context:– What companies are the stories directly relevant to?
– How positive or negative are they?
– Is there new information or is it a repeat of a previous story?
– Has a broker changed a price target?

We transform unstructured, real-time news from Reuters Newsand third-party services into a machine readable feed. Eachstory is scored for author sentiment, relevance and novelty ata company or commodity level.
Furthermore, with 220 commodities reporters, Reuters breakthe key commodities stories you won’t find anywhere else –and then score them to provide you with sentiment data across
40 commodities and energy topics.

Speed up research and backtesting with deep news
and tick archives
Our historical news analytics scores with millisecond time stamps
date back to 2003. In addition, we provide 20 years of Tick
History data covering more than 45 million over the counter(OTC) and exchange-traded instruments.
With both datasets unified under common RIC identifiers, weprovide all the data you need to take you from idea generation
through to backtesting and analysis, and then onto production.

With this information, you can slow down participation or widen
spreads until your team has had an opportunity to investigate
further or price volatility has lessened.

Useful links
Machine Readable News

Quantitative Analytics and Content

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