About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Low Latency – It’s All About Big Fast Data

Subscribe to our newsletter

When one hears the term ‘Big Data’ one is drawn to thinking about batch analysis of vast datasets, such as web logs, click streams and, apparently, phone records. Technologies like Hadoop and NoSQL are mentioned, already in the context of their lack of performance, and murky ROI. But in the financial markets, the world of big data is different: it’s real-time, it’s high velocity, and it packs enormous value. Which is why we’re continuing to focus on how low-latency technologies are converging with the big data world to move beyond simple – and increasingly obsolete – ‘fastest execution’ trading models.

Indeed, October 8 in London (and November 12 in New York City) will see our Low-Latency Summit focus on “Big Fast Data for Automated Trading” … and already we have defined a set of morning ‘big picture’ plenary panels to explore different facets of the emerging convergence:

Low-Latency: No Longer a Strategy. So What Is?

Outright speed is no longer enough, even if one can afford it. Intelligent trading, aka smart trading, is the new focus. It means making better trading decisions through data-driven analytics, and executing with competitive latency, at an affordable cost. What are the best approaches to participating in the intelligent trading marketplace?

News and Social Media for Trading – Analytics over Latency?

Trading strategies driven at least in part by news and social media updates are being increasingly adopted, and generating investment returns that many are taking note of. What sources of information are suitable for what trading strategies, and what approaches are available for connecting to and processing this potentially lucrative Big Data world?

In-Memory in The Real World – Your Competitors are Already There

RAM is up to 100,000 times faster than disk, so its use to minimize I/O latency for storage is well understood. Recent hardware/software advances have made in-memory computing more usable for large amounts of data, making it an approach that is relevant to both low-latency and big data processing. How is in-memory playing out for trading applications?

And that’s just the morning. In the afternoon, specific technologies and approaches will be explored in a number of ‘drill down’ workshops.  More to come on those.

Check out the in-progress London event information here, and register in advance, as space is limited. If you work for a financial institution, then we might invite you for free – email ron@a-teamgroup.com to see whether you qualify and get the free code.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: The Role of Data Fabric and Data Mesh in Modern Trading Infrastructures

The demands on trading infrastructure are intensifying. Increasing data volumes, the necessity for real-time processing, and stringent regulatory requirements are exposing the limitations of legacy data architectures. In response, firms are re-evaluating their data strategies to improve agility, scalability, and governance. Two architectural models central to this conversation are Data Fabric and Data Mesh. This...

BLOG

Nasdaq and AWS Deepen Partnership to Offer Calypso as a Managed Service

Nasdaq and Amazon Web Services (AWS) have expanded their strategic partnership, announcing that Nasdaq’s Calypso platform will now be available as a fully managed service on AWS. The move aims to provide financial institutions with a modernised, resilient, and scalable infrastructure for their capital markets and treasury operations. The offering sees Nasdaq managing the underlying...

EVENT

Eagle Alpha Alternative Data Conference, Fall, New York, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

Entity Data Management

Entity data management has historically been a rather overlooked area of the reference data landscape, but with the increase focus on managing risk, the industry is finally taking notice. It is now generally agreed to be critical to every financial institution; although the rewards for investment in entity data management appear to be rather small,...