The world of high-frequency trading (HFT) is constantly changing and highly competitive, driven continuously forward by the proliferation of high-speed computing technologies and the arrival of new market entrants.
Back in the 90’s, HFT was arguably the newest and most inventive way to trade assets and increase profits on the stock market. Many traders that got in early and quickly invested in the fastest and most powerful computing systems gained a huge competitive advantage. It was once so foreign that regulators struggled with how to properly track and monitor trades that happen thousands of times per second.
Today, trading at unfathomably high speeds is much more common, so much that automated trading is estimated to account for approximately 75 percent of all financial market volume. In HFT, trades are executed in milliseconds using high-velocity financial data, electronic trading platforms, and complex algorithms that are programmed to buy and sell stocks in moments, holding them just long enough to realize a marginal profit. High performance computing (HPC) systems and low latency network connections to financial markets are absolutely essential for HFT, and speed is not only the key to competitive advantage, but the very essence of the market.
But even the wide availability of HPC tools for the financial sector doesn’t mean that today’s HFT firms can just sit back and coast while their algorithms do the heaving lifting. There are a number of disruptive technology trends that are currently affecting the HFT segment that traders must be aware of.
Everything becoming automated
The rise of computerized trading has introduced automation into other areas of finance. This means machines are now more capable of handling financial processes and decisions once dominated by humans – a fact that is serving to make employment in the securities trading sector a highly competitive environment. For example, Goldman Sachs employed approximately 600 traders in 2000 at its U.S. cash equities trading desk in New York. Today, only two equity traders remain.
Machine learning and big data analytics now the norm
Machine learning techniques and big data analytics are altering nearly every industry and business process that exists today, and the financial services sector has widely adopted these tools to make more informed investment decisions. Machine learning is a perfect fit for HFT, allowing computers to uncover hidden, non-linear relationships that could lead to greater profits that humans wouldn’t be able to observe directly.
Non-traditional data points enter the decision-making process
Traders are increasingly turning to non-traditional data sources for insight that could affect capital markets, using streams of structured and unstructured data to help them react to the market in real-time and uncover new advantages. Today’s HFT firms are enhancing decision-making using data not only from market insight and price feeds, but from a variety of different sources like social media, weather forecasts, and sentiment analytics.
Legacy IT infrastructures simply cannot offer the levels of connectivity, bandwidth, and performance that are necessary to execute lightning-quick transactions and allow traders to keep pace with these disruptive trends. HPC tools that offer high-speed processing capabilities and low latency have become a “must” for all traders, enabling them to shave milliseconds off trade times, minimize system latency, and capitalize on meaningful performance advantages.
As the world of HFT rapidly changes and new trends further disrupt the market, traders must continue to invest in HPC architectures that deliver the levels of performance and speed that are needed in order to gain a competitive advantage. Please follow me on Twitter at @Bill_Mannel to stay on top of the latest HPC trading innovations for the financial services sector.