SimCorp Enhances Axioma Risk With AI-Powered Stress Testing

SimCorp has launched a new AI-powered capability within its Axioma Risk platform designed to automate the configuration of portfolio stress tests. By using natural language processing, the enhancement allows investment and risk managers to move from manual, multi-step workflows to AI-assisted setups. This shift reduces the time required to configure complex scenarios from hours to seconds, enabling teams to respond to market events in real time rather than being delayed by technical administration.

The tool enables users to describe macroeconomic or geopolitical concerns in plain English, which the system then translates into specific financial shocks and relevant market data. Beyond merely generating scenarios, the AI assists in identifying historical precedents and assessing the statistical plausibility of a test to ensure results are realistic. This helps managers gain deeper insights into tail risks associated with inflation, interest rate shifts, and global geopolitical instability without the need for spreadsheets or manual data exports.

Crucially, the update maintains rigorous calculation governance to meet increasing regulatory demands for transparency. While AI simplifies the initial design and iteration of stress tests, the analytical foundation remains fully auditable with human-in-the-loop approvals. This ensures that all decisions and analytics are explainable, allowing investment professionals to focus their specialized expertise on interpreting risk and making informed portfolio decisions.

BMLL Historical Data Launches on Databricks Marketplace

BMLL, the independent provider of historical market data and analytics, has made its datasets available via the Databricks platform. This move is part of the firm’s broader strategy to offer flexible delivery mechanisms, complementing its existing API, SFTP, and S3 options. The collaboration was driven by customer demand and guidance from the BMLL Client Product Advisory Board, with initial adoption already seen among major global investment management firms.

The integration allows market participants to access granular data across equities, ETFs, futures, and options directly within their existing Databricks workflows. To facilitate ease of use, BMLL has provided a series of marketplace notebooks designed by quantitative analysts. These tools enable users to evaluate the product suite with minimal integration effort and lower data storage costs, accelerating the transition from raw data to actionable insights.

The platform supports various financial functions, including execution analysis, backtesting, and market surveillance. By providing granular, normalised historical data on a scalable platform, BMLL aims to help firms perform more efficient analysis. The initiative reflects a commitment to meeting the growing industry demand for sophisticated data engineering while providing flexibility in how large-scale datasets are discovered and evaluated.

Bloomberg Introduces MYQ to Centralise Foreign Exchange Price Discovery

Bloomberg has launched MYQ, a price monitoring tool designed to aggregate and display foreign exchange (FX) quotes identified by Natural Language Processing (NLP) within Instant Bloomberg (IB) chats. The solution addresses the “swivel chair” challenge by consolidating fragmented pricing data from multiple chat rooms into a single, centralised FX curve-style format. By grouping quotes by currency pairs, tenors, and bid/offer levels, the tool provides traders with a clear overview of available liquidity and market interest prior to execution.

The tool aims to reduce operational friction and the risk of missed opportunities in fast-moving markets. Key features include a history tab for chronological price tracking and a “click-to-navigate” function that allows users to jump directly to the specific chat line where a quote originated. Advanced filters further enable participants to customise their view by currency or counterparty, streamlining the pre-trade workflow and helping users secure competitive pricing more efficiently before executing trades on platforms like FXGO.

Avelacom Launches Lowest Latency Hybrid Route Between Amsterdam and Tokyo

Avelacom, a global provider of low-latency network solutions, has launched a new hybrid fibre and microwave route connecting Amsterdam and Tokyo. The route achieves a round-trip latency of less than 127 milliseconds, establishing a new benchmark for connectivity between Europe and Asian digital asset markets. This expansion complements the company’s existing ultra-low latency infrastructure linking London and Frankfurt to major hubs such as Shanghai and Hong Kong.

The route is specifically designed to support institutional digital asset trading, where execution speed directly influences profitability. Amsterdam has emerged as a significant hub for this activity, hosting venues like BtcTurk and a growing concentration of blockchain validator nodes. Connecting this ecosystem to Tokyo provides traders with high-speed access to global liquidity centres and price discovery on platforms such as Binance.

To achieve these speeds, Avelacom has integrated additional microwave segments into its proprietary hybrid architecture, leveraging its existing Points of Presence. By combining fibre and microwave technologies, the network minimises delays across long-distance paths. This infrastructure investment reflects the increasing demand for high-performance connectivity as Amsterdam evolves into a critical gateway for decentralised networks and global electronic trading.

TS Imagine Launches Automation 2.0 as Assets Under Service Reach $19.5 Trillion

TS Imagine has unveiled Automation 2.0, an event-driven trading platform designed to help institutional desks manage sophisticated, rule-based workflows across multiple asset classes. The launch coincides with a significant growth milestone for the firm, which now manages over $19.5 trillion in assets under service, a substantial increase from the $5.3 trillion reported in 2023. This expansion reflects the increasing demand for scalable solutions in a high-speed market environment where manual order routing often leads to operational inefficiencies.

The new platform addresses the limitations of traditional automation tools, which frequently struggle with nuanced logic and complex compliance requirements. Automation 2.0 introduces a robust rule-building environment that incorporates cost intelligence, liquidity awareness, and market calendars. By utilizing two core components – the Rule Manager for workflow design and a stateful Workflow Engine for real-time execution – the system ensures consistent, reliable handling of orders without the need for manual intervention when market conditions shift.

Furthermore, Automation 2.0 establishes the architecture for the “Execution Agent,” the next phase in the evolution of Execution Management Systems (EMS). This foundation enables the transition from predefined rule-following to autonomous, agent-driven execution. By combining real-time event processing with structured logic, the platform allows trading systems to reason and adapt across the entire order lifecycle, providing institutional desks with greater control and sophisticated fallback capabilities during execution.

Arcesium Partners with Feynman Point Asset Management to Unified Multi-Asset Infrastructure

Arcesium, the financial technology provider, has formed a partnership with Feynman Point Asset Management (FPAM) to provide a unified infrastructure for digital and traditional assets. FPAM, an investment firm focused on digital asset markets and frontier technologies, will utilise Arcesium’s reconciliation solutions to manage its expanding investment landscape within a single ecosystem.

The partnership enables FPAM to support enhanced settlement cycles and scale its operations as the business grows. By implementing Arcesium’s Reconciliation platform, the firm gains real-time transparency and automated exception management. This allows for the rapid identification of data discrepancies and operational risks across varied asset classes, streamlining workflows and strengthening overall risk management, according to the company.

Exegy Enhances nxAccess Trading Engine with 71% Latency Reduction

Exegy, provider of capital markets trading technology, has announced a major update to its FPGA-based trading engine, nxAccess. The release introduces a 71% reduction in execution-stack latency, measured from start-of-packet to start-of-packet on the switch. This performance boost is designed to provide deterministic execution for firms operating in highly volatile environments where traditional hardware constraints can lead to “latency leakage” and missed pricing opportunities.

The update features a new Session Override capability, allowing firms to monitor session performance in real-time. This tool enables trading algorithms to bypass static configurations and pivot to the fastest available session or network link at the moment of execution. By turning connectivity into a dynamic asset, firms can adapt to fluctuating exchange latencies throughout the trading day without requiring complex hardware re-coding.

In addition to speed improvements, the latest version of nxAccess expands connectivity options to include UDP-based multicast and raw Ethernet frame transmission. These additions allow for immediate integration with ultra-low latency wireless and private links. As an off-the-shelf FPGA platform, the enhanced nxAccess aims to provide firms with the speed of custom hardware logic while maintaining the deployment flexibility and shorter development cycles of software-led solutions.

TS Imagine Launches Real-Time Integrated Swap Management Module

TS Imagine has introduced a new module to its cross-asset platform, offering a fully integrated system for managing swap economics and risk. Designed for synthetic prime brokerage desks and asset managers, the solution replaces traditional end-of-day reconciliation with a unified, real-time intraday view. By consolidating swap positions and corresponding cash equity hedges within a single system, the module eliminates manual processes and significantly reduces operational overhead.

The module is available across TS Imagine’s existing suite, including SwapSmart, RiskSmart+, and TradeSmart. It provides users with immediate visibility into risk and hedge discrepancies while offering native P&L attribution. This architecture supports a broad range of instruments, such as total return swaps (TRS), basket swaps, and CFDs, and has already been validated by large institutional synthetic prime brokerage clients.

To assist with regulatory demands, the solution features embedded P&L attribution that automates Volcker Rule reporting. By providing full VO2 to VO11 decomposition, the system removes the need for manual overlays and streamlines compliance. This modular approach ensures that regardless of their role in the investment lifecycle, users can manage complex swap portfolios with greater accuracy and fewer reconciliation breaks.

CME Group to Launch Avalanche and Sui Futures

CME Group is expanding its cryptocurrency product suite with the introduction of Avalanche (AVAX) and Sui (SUI) futures. Scheduled for launch on 4^th May subject to regulatory approval, these new contracts aim to provide market participants with increased flexibility and capital efficiency. The offering includes both standard and micro-sized contracts to cater to a broad range of investors, with AVAX units set at 5,000 and 500 tokens, and SUI units at 50,000 and 5,000 tokens respectively.

The expansion comes amid significant growth in CME Group’s digital asset markets, which saw March average daily volumes rise by 19% year-on-year, reaching approximately $8 billion in daily notional value. Industry leaders from Volatility Shares and Plus500US have welcomed the move, noting that it addresses the rising institutional demand for regulated, sound products in the high-growth crypto sector.

These new contracts join a growing list of recently added derivatives, including Cardano, Chainlink, and Stellar. Furthermore, CME Group has confirmed that starting 29 May, its cryptocurrency futures and options will transition to 24/7 trading. This shift is designed to enhance market accessibility and allow global customers to manage risk more effectively across evolving digital asset markets.

Bloomberg Expands MAC3 Risk Models for Enhanced Portfolio and Risk Forecasting Across Public and Private Investments

Bloomberg has expanded its MAC3 multi-asset risk models to cover private markets, extending the platform’s portfolio and risk forecasting capabilities beyond traditional public asset classes into private equity, private credit, real estate, infrastructure, hedge funds and liquid alternatives. The update reflects growing demand among institutional investors for more consistent measurement of risk across portfolios spanning both public and private investments. Bloomberg presents the expansion as a way to bring those exposures into a broader portfolio risk framework.

“Institutional investors are increasingly allocating across both public and private markets, yet risk is often measured in silos,” said Jose Menchero, Head of Portfolio Analytics Research at Bloomberg. “With these new models, MAC3 delivers a consistent, cross-asset factor framework that enables Bloomberg clients to understand and manage risk seamlessly across their entire portfolio in an increasingly complex investment landscape.”

Bloomberg MAC3 is a multi-asset class risk factor model that combines quantitative research techniques with Bloomberg security data to provide institutional investors with a unified view of risk across the portfolio. The platform currently includes more than 3,000 individual risk factors and supports risk forecasting, risk attribution, performance attribution, stress testing and optimization. The model also offers six time horizons, ranging from a responsive daily model to a stable long-term model, giving firms flexibility to align risk forecasts with different investment decision-making processes.

The new private markets capability adds MAC3 models for private asset funds, hedge funds and liquid alternative funds, allowing investors to forecast and decompose risk more consistently across public and private markets and support a total portfolio view across asset types. Bloomberg says the private fund model is constructed using dedicated private-asset factors and data on approximately 50,000 private funds covering private equity, private credit, real estate and infrastructure strategies, alongside hedge funds and liquid alternatives.

Across the alternatives fund suite, the models capture exposures across strategies, regions, sectors, styles and key macro sensitivities including rates, commodities, volatility and FX. Bloomberg says this can help investors identify shared risk drivers across managers and strategies, supporting portfolio construction, risk budgeting and governance at total portfolio level. Bloomberg’s MAC3 risk models are available to Terminal subscribers, who can use them to explore portfolio risk across public and private assets. Bloomberg PORT Enterprise customers can also license the underlying risk data, including risk factor exposures, volatilities, correlations and historical returns, with programmatic access available via API.

More broadly, Bloomberg positions MAC3 and PORT Enterprise as part of its wider buyside solutions suite, spanning research management, order and execution management, portfolio and risk analytics, trade compliance and operations. In that sense, the private markets expansion extends Bloomberg’s effort to support cross-asset investment workflows through a common data and analytics foundation.