RavenPack Analytics transforms unstructured big data sets, such as traditional and social media, into structured data and indicators to help financial services firms improve their performance. The product serves to overcome the challenges posed by the characteristics of big data - volume, variety, veracity and velocity - by converting unstructured content into a format that can be more effectively analyzed, manipulated and deployed in financial applications.
Whether the objective is generating more alpha, managing event risk more effectively, cutting false positives in market surveillance or generating trading ideas, RavenPack Analytics can improve performance.Systematic analysis of traditional & social media for finance. Publishers include Dow Jones Newswires, the Wall Street Journal, Direct Regulatory and PR feeds and over 19,000 other traditional and social media sites.
RavenPack structures data into five key dimensions:
- Entities: Systematic detection of global companies, currencies, commodities, financially relevant organisations, positions and key geographical locations when they are mentioned in unstructured data
- Events: RavenPack detects when these entities are involved in key scheduled and unexpected corporate, macroeconomic and geopolitical events or themes
- Relevance: The technology can differentiate between an entity being involved in an event, and how deeply, or if it’s just being mentioned
- Novelty: These metrics allow the user to tell, across all data sources, whether a detected event is new, a repeat, or a continuation of a pre-existing event or theme
- Sentiment: RavenPack applies both traditional natural language processing and proprietary techniques to determine entity-specific sentiment
✔ Asset Management: RavenPack provides granular structured data and indicators that are designed to help investment managers generate superior risk-adjusted returns. The data can be deployed in quantitative applications, or in portfolio construction tools with a discretionary overlay.
✔ Brokerage & Market-Making: RavenPack’s real-time event detection capabilities mean clients can create circuit breakers for use in systematic market making and algorithmic execution applications. Discretionary and online brokers can also use RavenPack's sentiment data and indicators to suggest or confirm trading ideas and portfolios.
✔ Risk & Compliance: RavenPack data helps risk managers locate accumulations of risk and volatility, or changes in liquidity - with event-based sentiment serving to identify regime shifts, or indicators triggering alerts at extremes. Event detection also helps condition market abuse alerts and reduce the number of false positives received by surveillance analysts.
✔ Research: Independent research firms, sell-side analysts and academics enhance their output by using RavenPack Analytics in their work. The data can be explored in quantitative research to show how to enhance portfolio performance, in fundamental research investigating how traditional factors can be conditioned with sentiment, or controlling for news and social media in academic research.
✔ Software / Data Vendor: Providers of financial technology, such as complex event processors, order management systems, automated trading or surveillance solutions can enhance their users’ experience and innovator position using RavenPackAnalytics.
✔ Media: Big data analytics provide unique, innovative insights and visualizations which will enhance the traffic to a website or to a particular article. Studies can range from news discovery to event studies and charted sentiment analytics at a company level.