October 22, 2018
RavenPack, the leading provider of big data analytics to financial institutions, today launched for its customers a new tool that allows users to search across 20 years of news, social media, and other textual content and generate insights for investing and trading, risk management and compliance.
New York - October 22, 2018
RavenPack Analytics Search can be used for comparative keyword research and to discover event-triggered spikes across billions of articles. Combined with RavenPack’s sentiment scoring and analytics generated through Natural Language Processing (NLP), users can measure interest in a particular topic across thousands of sources from around the globe, right down to the sentence level.
Clients can easily determine how many times people mention a topic over a certain period of time to identify trends. They can learn which companies or products are mentioned with given keywords or what topics might be driving interest. For example, a user can enter the keyword “blockchain” and get back all US companies in the last month involved with blockchain technology.
RavenPack Analytics Search is a powerful tool for financial professionals because it can allow them to explore the magnitude of different events and how markets might react to them. Investors and traders can quickly examine interest in a particular topic over time, where it’s most mentioned, with which other entities, and the related issues that are being discussed. Knowing what people are talking about provides a unique perspective on what they are currently interested in and influenced by.
“Data trends can provide a powerful lens into what investors are curious about and how people around the world react to important events,” said Armando Gonzalez, CEO of RavenPack. “RavenPack gives clients the flexibility to customize their queries to discover and analyze what really matters to them at any moment.”
The output of any search query performed by RavenPack users can be shared as a compelling data visualization including charts and treemaps, as an alert delivered via email or Slack Messenger, or as a structured dataset for the client’s data science team to run deeper analyses. All search queries are performed in the RavenPack cloud and analytics are delivered in real-time.
In addition to Search, Alerts are now available for everyone: you can configure real-time notifications on email and Slack when a stock or portfolio is connected with a defined keyword or is subject to abnormal media attention or sentiment changes.
In 2018, RavenPack was awarded "Best
Supplier" by Intelligent Trading Technology (IIT) and crowned winner for “Most Innovative New Product” for our
solution at the Technical Analyst Awards.
RavenPack is a leading big data analytics provider for financial services. Financial professionals rely on RavenPack for its speed and accuracy in analyzing large amounts of unstructured textual content. The company’s products allow clients to enhance returns, reduce risk and increase efficiency by systematically incorporating data-driven insights on news, social media and proprietary textual content in their models or workflows. RavenPack’s clients include some of the largest hedge funds, banks, and asset management firms around the globe.
Please use your business email. If you don't have one, please email us at firstname.lastname@example.org.
We will process your personal data with the purpose of managing your personal account on
RavenPack and offering our services. You can exercise your rights of access, rectification,
erasure, restriction of processing, data portability and objection by emailing us at email@example.com. For more information, you can
Your request has been recorded and a team member will be in touch soon.
High inflation has returned in developed markets after decades of lying low. In our latest paper, we show how to build an inflation-based asset allocation strategy using sentiment data and we illustrate that sentiment-based strategies outperform models that depend merely on past observed inflation values.
This year's RavenPack Research Symposium brought two intense days of knowledge sharing in London and New York, from 25 top experts in natural language processing, quantitative investing and machine learning. Together, we explored how firms can leverage new language models to generate alpha, better manage risk and respond to calls for more sustainable investment practices.
Human capital is at the heart of value creation. Our latest research demonstrates how unprecedented workforce insights, sourced from over 200 million job postings, can generate more alpha.