We often hear that data is the new oil, but there’s a crucial difference—data offers limited value to your firm when it’s just sitting in a silo. In capital markets, value comes not from big data but from fast data.

Delays in processing real-time data for actionable insights can be the difference between leading the market and falling behind. Milliseconds matter, and they can translate into millions on your balance sheet.

When milliseconds are worth millions

From the Dow Jones 1,000-point flash crash in May 2010 to the infamous GameStop short squeeze, spotting and reacting to sudden market movements in real time is vital to mitigate risk and fully capitalize on opportunities.

Of course, that’s easier said than done when facing a torrent of information from myriad sources fed by constant connectivity and business digitization. Thanks to automated algorithms and high-frequency trading, today’s crowded markets also move faster than ever before—narrowing the window of opportunity further.

In this hyper-competitive environment, your quants and traders need a scalable data analytics platform ready to cope with the skyrocketing variety, volume, and velocity of data.

Read on as we explore how the right approach to real-time data analytics can help you optimize execution, boost alpha, manage risk, and ensure compliance.

The price of falling behind

With real-time analytics operating at scale, speed, and depth, your quants and traders will gain a significant edge in the market. While these advanced capabilities come at a price, they far outweigh the cost of relying on outdated or inefficient systems. Trading usually is a zero sum game and for every winner, there are many who lose out on account of slower access to data / reduced ability to act on their superior insights.

If you currently depend on a patchwork of legacy systems, don’t accept the combination of higher infrastructure costs and slower processing that causes you to miss out on opportunities or run unnecessary risks. Here are some examples.

• Missed opportunities: Delays in processing real-time data can cause you to miss critical trading signals. Let’s say you’re engaged in USD/EUR/JPY triangular arbitrage. Suddenly, an exploitable price gap emerges, but your analytics stack is running a few seconds behind live data—and the window closes
• Inefficient execution: Accurate real-time data is the backbone of effective execution before, during, and after trades. Continuing the arbitrage example above, imagine you executed just 50 milliseconds too late — leading to increased slippage, higher fees, and reduced or negated profits
• Compromised risk management: Slow analytics hinder your ability to identify risks and react fast in volatile markets. Perhaps you’re trading a small-cap cryptocurrency that suddenly collapses in price. Without real-time analytics, you’re not immediately alerted to the move and can’t take instant action to limit losses or mitigate risk
• Regulatory non-compliance: Whether it’s MiFID II in the EU or the Dodd-Frank Act in the US, an inability to ensure compliance with key industry rules around real-time trading records can come at a high price for both your bottom line and reputation

Future-proofing your stack with real-time insights

Whether it’s the opportunity to get ahead or the risk of falling behind, an optimized and scalable technology stack ready for real-time analytics has never been more important.

The ability to quickly and accurately process, integrate, and evaluate huge volumes of streaming data for insights lets quants train up-to-date models and spot emerging patterns. At the same time, traders can make the best possible decisions and execute them effectively.

Here are some recommendations for building a real-time analytics platform ready for the demands of capital markets today and tomorrow.

• Easy integration: To support ongoing innovation, look for analytics platforms that flexibly integrate with your current infrastructure. This is vital to ensure a holistic view of your data across varied functions like trading, risk management, or compliance
• Seamless scalability: Invest in a platform that can grow with your needs as trading operations and data volumes rise. Both computation and storage resources should flex with demand to prevent slowdowns and maintain performance
• Complex event processing (CEP): Look for systems that can analyze a torrent of streaming data to detect trends, patterns, or anomalies in real time. Platforms that support CEP are essential to help your teams make better decisions, execute effectively, and mitigate risk
• Optimized processing performance: Seek out platforms that support in-memory computing for faster access speeds and analysis, as well as efficient CPU usage that lowers latency and shortens your time-to-insight
• Agile visualization: Look for platforms that can visualize data instantly. With the ability to load, transform, query, and visualize massive datasets in near real-time, your quants and traders can identify, understand, and respond to market changes much more rapidly

Maximizing returns from real-time data

When managing real-time streaming data from a host of sources, gaps, duplicates, or inconsistencies should be expected. Yet, faulty data in means faulty insights out.

Data cleansing must be a vital part of your analytics lifecycle. Ensuring accurate, complete, and consistent data is central to helping quants and traders squeeze the most value from it.

Deriving the greatest value from real-time streaming data also demands more than just instantaneous processing—it requires adding historical context.

With an analytics stack that can fuse streaming market data with historical information at speed and scale, your quants and traders will gain far deeper visibility into market risks or opportunities and strengthen their ability to generate, test, and refine models.

Getting ready for real-time

The days when it was enough to derive business intelligence from static information siloes are long gone. In today’s capital markets, the ability to make faster, better‑informed decisions using rapid insights from real-time streaming data is vital to your competitive edge.

Demand for real-time analytics is rising fast, with the market projected to grow from US$27.6 billion in 2024 to US$147.5 billion by 2031, according to Persistence Market Research. This represents a compound annual growth rate (CAGR) of 26%, driven by technological advancements in AI and machine learning platforms and the increasing need for accurate, real-time data insights to support quicker decision-making and greater agility.

It’s time to ensure your analytics stack can help traders execute effectively and optimize orders on-the-fly. It’s time to drive nimble risk management for more stable operations. And it’s time to gain regulatory peace of mind with real-time surveillance.

With a scalable analytics platform that efficiently processes complex data from the past and present, your firm will have the vital insights needed to create a successful future.

Learn more by reading our ebook, ‘Supercharge your quants with real-time analytics.’

Optimize your trading strategies with kdb Insights Enterprise, which is built for real-time, high-performance analytics. Learn how real-time visibility from KX enables lightning-fast, continuous insights, improved risk management, and enhanced decision-making.