Rapid transmission of data is the heartbeat of high-frequency trading (HFT).
For each and every trade, real-time data from exchanges is received and quickly analyzed to enable buy or sell decision-making, and then trade orders are fired back to exchanges for execution and confirmation. These large volumes of financial data that flow at lightning speeds between HFT firms and exchanges are the lifeblood of the trading industry, and those that succeed in earning the greatest financial returns have the tools to rapidly convert it into strategic insight.
Before electronic trading became the norm, it could take even the most seasoned trader up to a minute or two to execute each individual trade. Today, machines perform these same tasks in less than a half a millionth of a second, over one million times faster than the human brain can make a decision.
High performance computing solutions built specifically for high-frequency trading operations have initiated a paradigm shift in the industry, and trading is now a starkly different process than it was just a few years ago. Supercomputers now execute hundreds of trades per millisecond using financial algorithms built from Big Data insights.
In this fast-paced era of finance where the only difference between you and your closest competitor might be a fraction of a second, there’s no such thing as “fast enough” for high-frequency traders.
Computing infrastructures that are flexible, scalable – but above all, fast – are must-haves for traders looking to extract value from massive data volumes in order to make informed decisions and react in real-time to changing market conditions.
The advent of high-frequency trading has produced vast quantities of data which must be processed and analyzed fast to drive trade decision-making that happens thousands of times per second. The speed and quality of analysis made possible by Big Data is more important to the trading industry than ever before, and computing infrastructures capable of managing high-frequency trading workloads and reducing latency have become critical to survival.
Methods for increasing transactions speed are aggressively sought after by high-frequency traders, and high performance computing has made fast processing capabilities available to even the most modest financial firms.
End-to-end computing solutions that optimize transactions for speed and volume can make sub-second improvements to transaction speed and enable real-time decision-making. Soft bundles of hardware and software which offer higher frequency and faster processing capabilities can also be built on to existing legacy infrastructures to reduce costs.
In addition to gaining speed, reducing latency is another important action item for high-frequency traders. A millisecond of trade delay may not seem important, but techniques that minimize latent periods have the potential to boost an HFT firm’s annual earnings by as much as $100 million.
Many trading houses aim to deploy infrastructure in close proximity to exchange servers or co-locate servers on the same network as exchanges. Server configurations which are right-sized for standard power capacities are optimized for easy co-location data center deployments and can help traders minimize latent periods.
Extreme computing power has not only become a key differentiator in high-frequency trading, but crucial to survival. Only financial firms that keep pace with technology and leverage data toward strategic insight will speed innovation in HFT and be able to reap greater financial returns, capitalize on data-driven decision-making and secure competitive advantage.
To learn more about the advantages of Big Data analytics, I invite you to follow me on Twitter at @sureshaswani2.