More than $3 trillion total value of assets managed by hedge funds worldwide in 2019
More than 50 percent of marketleading hedge fund managers use seven or more alternative data sets
$1.7 billion estimated spending on alternative data by fund managers in 2020, up from $400 million four years ago
Hedge funds are always seeking alpha. But these days, potential profits may be driven more by data and analytics than by financial fundamentals.
That’s why the need for both data and high-speed analytics for hedge funds has exploded in the past few years. This is especially true with hedge funds’ use of big data, alternative data, and data-powered investing. Analyses of increasingly large sets of alternative data, from social media posts to news reports—and just about anything else—can have a big impact on investment decisions. They can also highlight important economic trends that provide new opportunities.
Faster analytics and processing capabilities and more-flexible data strategies are required to capitalize on the massive amounts of alternative data. They need to enable fund managers and analysts to easily work with billions of rows of data in near real time. Hedge funds need to be able to rapidly onboard information from both local and cloud-based sources in a scalable and consistent way. And analysts need to be able to use that data to quickly explore new ideas, create new models, and make faster decisions.
Even hedge funds that don’t rely on alternative data are falling behind the competition when it comes to real-time analytics. Market volume has exploded. For everything from daily order processing to reporting and Order Audit Trail Systems (OATS) and Consolidated Audit Trail (CATS) compliance, getting reports or critical analysis completed in ever-tighter timeframes is becoming increasingly difficult with most existing hedge fund systems. At the same time, controlling and managing risk has never been more important, or more difficult.
Legacy platforms are too expensive, and vendors of conventional cloud data warehouses offer unpredictable consumption-based pricing and have no incentive to provide good performance.
Yellowbrick Data Warehouse is an advanced MPP SQL analytic database for demanding batch, real-time, ad hoc, and mixed workloads. Built from scratch for best price/performance, its adaptive “cut-through” architecture takes best advantage of any physical (e.g., optimized instances) or virtualized (e.g., Kubernetes) infrastructure—delivering 100x performance for thousands of users at a fraction of the cost of alternative data warehouses. On top of that, we add a modern, industry-standard database interface (PostgreSQL) that’s familiar to users for ecosystem compatibility. The result is a modern, quickly provisioned, and easy-to-use solution that blows the doors off rivals in price/performance economics and that can be deployed anywhere across distributed clouds (private, public, and edge networks).
Additional Yellowbrick advantages include:
Yellowbrick is compliant with industry standards for plugging seamlessly into existing environments that include common data integration, BI, and identity management tools. Migrations are fast and easy from any legacy platform, and we’ll work with you to validate your use cases and success metrics along the way.
A top hedge fund and market maker found its existing database and analytics infrastructure unable to keep pace with current requirements in a variety of ways. The company knew it needed to modernize its SAP Sybase IQ legacy technology to keep up with modern-day market volumes. The legacy system was overly complex and provided poor performance. In addition, the company was struggling with timely OATS and CATS compliance reporting.
After evaluating a range of options, the hedge fund selected Yellowbrick for its solution and achieved significant results:
A major top-10 hedge fund faced multiple challenges with its existing analytics platform. The company needed more speed and fl exibility from the platform, which wasn’t keeping up with current business needs. The legacy Microsoft SQL Server and KDB proprietary database for time-series Trades and Quotes (TAQ ) data was unable to meet critical performance requirements. In addition, the new solution needed to leverage standard SQL and standard tools for seamless analytics by existing users. And the solution needed to support a hybrid environment, with the ability to deploy both on premises and in the cloud.
After evaluating both KDB and SQL Server upgrades, the hedge fund selected Yellowbrick for its new analytical platform for the following reasons:
Yellowbrick Data empowers companies to make faster decisions with all of their data. Built for enterprises and the hybrid cloud, the Yellowbrick Data Warehouse deploys powerful analytics anywhere, with best in-class economics.