BridgeWise Utilises X Data in New Wealth-Focused Sentiment Analysis Tool

Wealth management financial technology specialist BridgeWise has collaborated with X to integrate data from the social media platform into its intelligence engine to provide social sentiment analysis for thousands of securities.

The system utilises an API-driven connector and a proprietary framework to convert unstructured data into structured signals for financial institutions. The resultant SentimentWise is a solution intended to allow users to monitor shifts in investor mood and identify trends through the analysis of both fundamental and alternative data. The offering builds on BridgeWise’s acquisition of Context Analytics.

BridgeWise co-founder and chief executive Gaby Diamant said the arrangement turns global conversations into a quantifiable tool to assist investors with decision-making.

“Markets move on more than just numbers; they move on what people are saying, thinking, and feeling in the moment,” Diamant said. “By plugging X’s data stream into our engine alongside our deep fundamental and technical analysis, we’re helping our clients cut through the noise to see what actually matters.”

Sentiment analysis uses algorithms to evaluate public opinion and social media activity to gauge potential market movements.

Fitch Builds Fitch Nexus MCP Connector to Ratings Data

Fitch Solutions has launched a Model Context Protocol (MCP) connector, Fitch Nexus, that enables clients to access Fitch Ratings content through internal AI applications and large language models.

The connector provides credit research, historical ratings data and financial forecasts through a single integration.

“Fitch Nexus is designed to deliver faster, more actionable insights with greater efficiency and immediacy,” said Fitch Solutions chief commercial officer Christopher Sparke. “It reduces the distance between question and answer, enabling our clients to access the signals, commentary, and data they need to inform investment and risk management decisions.”

Future updates will include additional capabilities from CreditSights, BMI, and Sustainable Fitch to expand the available dataset. MCP is an open standard that enables AI assistants to connect with data sources and tools across different platforms.

ExtractAlpha Relaunches AlphaClub Research Workspace with Expanded Signal Coverage

ExtractAlpha has relaunched AlphaClub, its research workspace for investment professionals evaluating the firm’s quantitative stock selection signals and alternative datasets. The update introduces a redesigned interface, broader international coverage, and a workflow-oriented structure aimed at making signal discovery and evaluation more efficient.

The platform is positioned as an environment where hedge fund analysts, portfolio managers, quant teams, and research professionals can explore ExtractAlpha’s offerings, examine how individual signals are constructed, and assess where they might fit within an existing investment process. Updates include faster navigation, cleaner layouts, longer signal histories, and expanded global context across the firm’s datasets.

“AlphaClub is not a data terminal,” says Vinesh Jha, CEO at ExtractAlpha. “It’s a practical research workspace that helps investors understand what our signals are, how they behave, and where they may add value.” This framing is a notable positioning point in a market where evaluation tooling for alternative data signals has tended to lag the sophistication of the signals themselves.

AlphaClub is available via free membership for qualified investment professionals.

73 Strings Unifies Data Operating System for Private Markets Participants

Private markets valuation and portfolio intelligence platform 73 Strings has launched a unified global operating model, which the company said “brings together the platform, people, and clients into one ecosystem”.

This transition aligns global teams to support clients across private equity, private credit, venture capital and infrastructure, it said.

“Private markets are entering a new era, defined by data, AI and the need to operate at scale,” said Yann Magnan, chief executive and co-founder of 73 Strings. “Our global operating model… allows us to innovate faster and help our clients stay ahead, while maintaining the rigour and trust that underpin investment decisions.”

The firm has appointed Jazmin Hogan as global head of client operations to lead the client organisation from New York. Hogan previously held leadership roles at Apollo Global Management, Blackstone and Kohlberg & Company.

73 Strings’ integrated platform combines valuation, portfolio monitoring and data extraction to replace fragmented spreadsheet-based processes.

BMLL Integrates SpiderRock Options Analytics into Data Lab Environment

BMLL has expanded its cross-asset research capabilities by making SpiderRock’s Options Print Set data available through the BMLL Data Lab. This integration allows institutional clients to analyse the relationship between options markets and underlying cash equity behaviour within a single, unified framework. By combining SpiderRock’s print-level analytics with BMLL’s historical data, users can better evaluate how dealer positioning and hedging flows influence intraday price formation.

The partnership provides access to SpiderRock’s implied volatility and Greeks data alongside BMLL’s existing datasets for equities, futures, and options. This data suite is designed to support quantitative research and strategy development, offering insights into how options hedging affects spot liquidity and market microstructure. The collaboration aims to help market participants understand the dependencies between different asset classes to improve trading and market intelligence.

The addition of SpiderRock data aligns with BMLL’s broader strategy of consolidating high-value partner datasets with its own historical analytics. This move is intended to streamline the research process for clients, enabling them to gain a more comprehensive view of market interdependencies and risk.

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.

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.

SEC Approves Cost-Saving Measures for the Consolidated Audit Trail

The Securities and Exchange Commission (SEC) has approved an amendment to the National Market System Plan to implement various cost-saving measures for the Consolidated Audit Trail (CAT). This decision includes exemptive relief from specific requirements of the Securities Exchange Act of 1934, aiming to reduce the financial burden of the CAT while maintaining its core regulatory functions. The amendment builds upon previous efforts from 2025 to streamline the system’s budget and operational efficiency.

Key changes under the new amendment include the deletion of CAT data older than three years, the relaxation of certain data processing deadlines, and the implementation of a spending cap for future modifications. Furthermore, the plan participants will cease creating interim lifecycle linkages unless requested and will stop reporting rejected messages. These technical adjustments are designed to simplify the infrastructure and reduce the volume of data managed by the system.

The SEC estimates that these measures will result in annual cost savings of between $50 million and $70 million compared to the 2025 CAT budget. When measured against the savings from the 2025 exemptive relief, the new amendment is expected to provide an additional $19.4 million to $24.1 million in incremental reductions. SEC Chairman Paul S. Atkins noted that while this represents significant progress, a comprehensive review of the CAT’s long-term sustainability remains ongoing.

Bite Investments Acquires Portfolio Intelligence Platform Untap

Bite Investments, a technology provider for the alternative investments sector, has announced the acquisition of Untap, a portfolio management and fund-intelligence platform. This move integrates Untap’s data capabilities into Bite Stream, Bite Investments’ flagship software, to enhance portfolio analytics and ESG reporting. The acquisition follows a period of strategic growth for the company, supported by recent investments from NewSpring Capital, Proof Point Capital, and Osage Venture Capital.

The integration of Untap allows Bite Stream to offer private-market managers a more comprehensive suite of tools, including AI-driven fund intelligence and KPI tracking. Untap’s flexible data model facilitates the collection of financial, operational, and qualitative information within a single environment. This assists managers in meeting the growing demand for transparency regarding return generation and fund performance, while also streamlining investor onboarding and communications.

Moving forward, the combined platform aims to bridge the gap between investor engagement and underlying portfolio data. While both platforms will continue to support their existing clients, the development roadmap focuses on unifying the user experience and strengthening data infrastructure. Legal and financial advice for the transaction was provided to Untap by Hart Brown, PwC, and Kitra Advisory.