Quantitative research and trading

Quantitative Research and Trading

Apply scientific methods to your quantitative research and trading, and discover new ways of viewing and analyzing data.

Our range of content, analytical tools and expertise is designed to help you develop and implement winning mathematical models, whether for the pricing of derivatives, assessment of risk, or prediction of market movements.

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Quantitative Research and Trading

The content we provide is global, and covers all the financial data you need for your quantitative research to take an idea from idea generation, to back-testing and analysis, and then on to production. Beyond economic and financial data, however, we give you access to breaking news, environmental, social and governance performance, and corporate guidance.

Our own team of quantitative analysts creates extra value with weighted analyst consensus estimates, predictive analyst revision and earnings quality models, and long-term earnings projections that drive company valuations.

  • Market analysis
  • Data management solutions
  • Predictive modeling
  • Machine Readable News and MarketPsych Indices
  • Backtest systematic investment models
  • Historical tick data
  • Investment alpha

Quantitative Management

Market analysis for better modeling decisions

Develop sophisticated quantitative analyses using the industry’s most comprehensive and detailed market, economic and company data.

We provide a full range of high-quality standard and specialized content sets, delivered as part of the QA Direct platform or via direct feed for integration into your proprietary platform.

  • Macroeconomic data — the largest and most comprehensive collection of global macroeconomic time series content in the industry.
  • Market data and pricing — real-time feeds covering more than 350 exchange-traded and OTC markets accompanied by full tick data history.
  • I/B/E/S Estimates — the industry standard, offering more history, contributing brokers and company coverage than any other provider.
  • Fundamentals — standardized and company specific fundamentals data for more than 50,000 active global companies.
  • News analytics — automatically analyze thousands of company-related news inputs in real time and feed the results into your quantitative strategies.

Powerful quantitative data management solutions

QA Direct maps information from all data vendors and your own proprietary data to a single, unchanging, unique identifier, so you have the transparency into the data and the flexibility you need for accurate and sophisticated analysis.

Broad and deep content — direct access to best-of-breed, integrated data from multiple vendors.

Advanced database structure — utilize Microsoft SQL Server or Oracle with fully documented database schema and diagrams.

Integrated data offerings — each vendor set is interlinked through our proprietary mapping system. Plus, our database is designed to be fully expandable for additional content sets.

View latest data updates — access data update log tables to easily view changes.

Flexible access — QA Direct can be easily linked to statistical and portfolio optimization packages, such as SAS, MATLAB, R and S-PLUS®.

Delivering deeper insight

Thomson Reuters StarMine has a long and proven track record in successful predictive modeling. We leverage factors that others overlook, and the result is simple: better alpha generation. 

StarMine is dedicated to making investment research smarter. Analytics and equity research tools like our suite of Quantitative Models help investment professionals around the globe generate alpha and process equity information more efficiently so they can get ideas to market faster. StarMine Quantitative Models are stock selection factors grounded in sound economic intuition and developed using best of breed modeling techniques. These robust models span across regions, sectors and market environments to help investors achieve higher returns across a spectrum of investment styles. Powerful modeling techniques, combined with the depth and breadth of Thomson Reuters content, give investors the tools they need to generate unique insight.

Exploit signals in news

News flow and sentiment are important sources of signals in quantitative stock selection and systematic trading. However news and social media data is unstructured and there is a lot of it. Is it positive or negative? New, old or recycled? Relevant to a company?

With Thomson Reuters Machine Readable News and MarketPsych Indices you can:

  • Uncover actionable signals for your strategy
  • Scan and analyze across thousands of companies in real time
  • Speed up research and backtesting with deep news and tick archives
  • Mitigate risk with an early warning of volatility
  • Get an edge with unique specialist commodities coverage
  • Find signals in your unstructured data sets with our text analytics toolkit
  • Convert the volume and variety of professional news and social media into manageable information flows that drive sharper decisions.

Utilize quantitative approaches in making investment decisions

Portfolio managers and analysts continue to look for new ways to optimize the risk / return profile of their investment strategies, including the use of quantitative models.

Thomson Reuters QA Point is a cloud-based platform for backtesting systematic investment models that allows professional investors to introduce cutting edge quantitative research and analytics to fund management. You don't need to be a highly skilled developer or 'quant' to take advantage of advanced quantitative investment strategies and data science.

QA Point simplifies workflows, making it easy to construct, validate, and deploy multi-factor quantitative investment strategies – in a fraction of the time it takes using traditional quant tools.

Introducing Thomson Reuters QA Point (2:24)

Historical tick data

The quality and reliability of data within your research processes determines the validity and investible integrity of tradable outputs. A strong back-test with high-quality data allows you to research, test and optimise strategies, and validates and demonstrates your trading strategy.

Use Thomson Reuters Tick History to access tick-level data across global asset classes. With it, you can effectively manage compliance requirements in today’s fluid regulatory environment, perform quantitative research and analytics, and employ real-time algorithmic trading strategies in a cost-efficient manner.

Data is recorded from our real-time feeds covering both OTC and exchange-traded instruments across over 400 trading venues and third-party contributed data.

Generate alpha-signals from unstructured content

The quest for investment alpha is transitioning away from traditional logicized and structured sources of alpha. As a result, there is a need for advanced technologies like natural language processing and meta-data tags to derive structure, and then use downstream in alpha-mining quant and investment research models.

With Thomson Reuters Intelligent Tagging you can define your text inputs, leverage a rich taxonomy, and use PermID to link to other content. As a result, you have the opportunity to analyze text in a new and unique way to differentiate and generate alpha.