KX

Over the past few years, many teams have seen signal half-lives shorten as regimes shift more frequently, implementation effects carry more weight, and learning windows compress. This session looks at: 🔸Why signal decay is accelerating 🔸Where it creates operational pressure 🔸 The analytical capabilities that support faster learning cycles 📊 Signal Decay: Why Alpha Half-Lives Are Shrinking Feb 05 2026, 4:00 PM GMT | 11:00AM EST 🎙️ Scott Rich & Paul Geis Register here 👉 kx.com/resources/webi…

🚀 Get ready to build, compete, and win big. The KDB-X 5-Day Code Challenge kicks off Monday, January 26th, 2026 — with thousands of dollars in prizes up for grabs. 🗓 5 fast-paced days 💻 A brand-new challenge drops every day ⏱ 24 hours to build and submit 🔥 Crush a day → get entered to win that day’s prize 🏆 Finish all five → unlock your shot at the grand prize 🎁Prizes: Day 1: Smart Watch Day 2: DJI Mini 4k Drone Day 3: Noise Cancelling Headphones Day 4: Tablet Day 5: GoPro Camera Grand Prize: MacBook Air All challenges are released on KX Academy, with real-time collaboration and hype in the Code Challenge Slack channel. Proudly sponsored by Data Intellect 👉 Register here: academy.kx.com/courses/kdb-x-…

Alpha decays as markets evolve. Structure changes, participants adapt, and execution frictions shift. In this session, we look at how hedge funds are responding to signal decay under faster market conditions, and why learning velocity increasingly shapes outcomes. Webinar title: Signal Decay: Why Alpha Half-Lives Are Shrinking and How Leading Funds Respond 📅 February 5, 11:00 am EST | 4:00 pm GMT Register here: brighttalk.com/webcast/19020/…{{Recipient.ID}}&utm_source=KX&utm_medium=linkedin&utm_campaign=660715

🏝️ Your research vessel hit a storm. You’re stranded on a remote island. The only thing that survived the wreckage? A laptop running the Community Edition of KDB-X and some mysterious data links. On Monday, January 26th, 2026, the KDB-X 5-Day Code Challenge kicks off — five days of hands-on building, learning, and competition. How it works 🔸 A new coding challenge drops each day on KX Academy 🔸 You have 24 hours to complete each challenge 🔸 Complete a day → entered to win that day’s prize 🔸 Complete all five → entered to win the grand prize All participants are invited to join the Code Challenge Slack channel to ask questions, share progress, and build together throughout the week. 🚀 Registration is open now: academy.kx.com/courses/kdb-x-…

In 1968, Apollo 7 launched only after thousands of simulations eliminated uncertainty long before ignition. 🔎 Systematic trading works the same way. 🚀 Alpha is determined before capital is deployed. Today’s quants are operating against faster signal decay, higher data volumes, and backtesting stacks that struggle to scale. When full-fidelity simulations take hours or days, opportunity cost compounds quickly. This piece examines why backtesting speed, realism, and deployment continuity now shape time-to-alpha, and how leading hedge funds are rethinking their research infrastructure to keep pace. Read the full blog 👇 kx.com/blog/outrunnin…

Laura Kerr has published a practical walkthrough on how to seamlessly query Parquet datasets in KDB-X, unlocking faster analytics and easier interoperability with tools like Spark, Pandas, and Arrow. The tutorial shows how to: 🔸 Run q queries directly on Parquet files 🔸 Combine on-disk and in-memory tables in hybrid workloads 🔸 Use virtual tables to analyse large historical datasets efficiently 🔸 Perform high-volume time-series calculations at scale If you work with large columnar datasets or time-series analytics, this is a great hands-on guide to getting more out of Parquet within KDB-X ➡️ kx.com/blog/tutorial-…

As we wrap up another exciting year, we extend our sincere thanks to our clients, KX Community, and partners for their continued trust and collaboration. From all of us at KX, we wish you a joyful holiday season and a successful year ahead.

If you work with time series data and want faster iteration without adding infrastructure overhead, check out @Laura Kerr’s new KDB-X SQL tutorial. The tutorial shows how you can: 🔸 query q tables using familiar SQL 🔸 turn exploratory queries into reusable functions 🔸 combine SQL with q to handle more complex analytics like pivots 🔸 keep workflows fast across environments These patterns align with what high-performing capital markets teams need: shorter research cycles, less duplication between environments, and clearer paths from idea to production. Read the full tutorial: kx.com/blog/tutorial-…

🎉 Meet our two newest members of the #KXperts Community Advocacy Program! ⭐ James — 13+ years building kdb+ solutions for trading analysis across Montreal, NYC & London. ⭐ Fabio — Data Engineer with an MSc in AI, bringing deep experience across finance, telecom & energy. He applies data-driven solutions to complex capital markets + quant challenges. You’ll find James and Fabio actively engaging in our Slack Community: kx.com/slack 👉 Learn more about the KXperts Program: kx.com/developers/kxp…

kdb/q is often described as a database, but that label barely scratches the surface. It’s an array programming language that lets developers build almost anything they can imagine, and as Alexander Unterrainer explains in his latest DefconQ blog, its real power is how it reshapes the way you think and approach problem-solving: defconq.tech/docs/language/…

Agentic AI is accelerating operations in capital markets. ​ ​In @NVIDIA’s latest blog, they highlight how @rbccm is using the NVIDIA NeMo Agent Toolkit and NeMo Retriever with KX to power document processing, research capabilities, and banking services. ​ We’re proud to support RBC’s vision as it scales agentic AI across capital markets with NVIDIA AI Enterprise. Read the full NVIDIA blog: nvidia.com/en-us/customer…

Traditional workflows move data to centralized environments, but in the real-time economy, that’s too slow. In episode 4 of Data in the AI Era, our CEO explains why market leaders are flipping the model and bringing compute to the data. ​ Full episode + key takeaways: kx.com/resources/podc…

One week to go until our webinar exploring KDB-X – the next generation of kdb+.​ The KDB-X launch brought time-series, vector, and AI workloads together in one platform. Now see what that means in practice.​ Join us for a hands-on walkthrough of KDB-X and learn how to:​ 🔷 Install and query data in minutes using q, Python, or SQL​ 🔷 Run live analytics and AI workflows side by side​ 🔷 Extend the platform with open modules and formats​ 🔷 Explore what’s next in the roadmap​ Register here: linkedin.com/events/7397633…

We’re proud to share that KX has won the @RegTechInsight Award for Best Transaction Cost Analysis Solution in the Best Execution category! Thank you to the judges and thank you to our community for your votes and support. Congratulations to all the winners and finalists!

KDB-X brings time-series, vector, and AI data together in one high-performance platform, helping firms accelerate research, trading, and risk analytics.​ Read how this platform shift is transforming data and AI workflows: kx.com/blog/kdb-x-now…

We’re live at @QuantMinds this week! Meet the team at stand QM14 to see what’s new with KDB-X and learn how leading quant groups are scaling real-time analytics and AI workloads with KX.​ #QuantMinds #QuantFinance #KX #KDBX #CapitalMarkets

The KDB-X Community Edition is live, giving every developer free access to our high-performance, AI-ready unified data and analytics engine!​ Shaped by developer feedback, the Community Edition brings an open, modular framework with enhanced libraries for high-volume time series and market data. Since it’s been in public preview, developers have already used it to build real-time IoT monitoring systems, predictive maintenance platforms and trade execution strategies!​ Join the 1,300+ developers already exploring KDB-X at no cost. Learn more: kx.com/news-room/kx-d…

KDB-X continues to demonstrate exceptional efficiency on real-time and time-series workloads.​ In a new TSBS DevOps benchmark, KDB-X delivered fast, consistent performance across all query types, even while using only a small fraction of the available system resources.​ Read the full analysis for a closer look at the results and why efficiency critical for real-world time-series applications at scale:​ kx.com/blog/benchmark…

KDB-X is now GA​ ​ The next generation of kdb+ unifies time-series, vector, and AI data in one high-performance platform.​ ​Built-in AI libs and support for Python, SQL, and q.​ Learn more in Ryan Siegler’s blog: kx.com/blog/kdb-x-ga-…

Great to see KX Nano powering new performance benchmarks from @GoogleCloud and @AMD at #STACSummit NYC. Using our open-source tool for kdb+ performance testing, the new H4D VMs (powered by 5th Gen AMD EPYC processors) delivered an average ~34% uplift over the previous generation, out of the box and with no system tuning.​ A strong result for the next generation of high-performance, low-latency financial workloads. Read more: cloud.google.com/blog/topics/hp… @stacresearch