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Why Private Markets Need Numbers They Can Defend
By Gareth Hewitt, Founder, LemonEdge. Private markets run on confidence. Performance still matters but investor trust increasingly depends on whether a general partner (GP) can defend the numbers behind it and whether a limited partner (LP) has enough transparency to test and reconcile those numbers for itself. A capital account balance, valuation movement, fee calculation…
A-Team Group Announces Capital Markets Technology APAC Awards 2026 Winners and Launches ‘State of the Market’ Report
A-Team Group today announced the highly anticipated winners of the Capital Markets Technology APAC Awards 2026. These prestigious awards celebrate the most innovative solution providers and financial institutions that are reshaping the capital markets technology landscape across the dynamic Asia Pacific region. In conjunction with the awards, A-Team Group has also launched the “State of…
How Much Hedge Fund Alpha Is Lost Before the Model Even Runs?
How often is a hedge fund’s apparent model failure actually a data failure in disguise? A model that stops working. A backtest that does not replicate. A risk number that needs explaining. How to tell one from the other – before reaching for the model first – was the recurring question of an hour-long discussion…
Are Firms Hunting Alpha Outside While Deleting It at Home?
A trading firm will pay for 15 years of price history from a market data vendor and, on a parallel housekeeping schedule, purge its own order flow, client activity and system logs after five to seven. The vendor history is treated as an asset worth a recurring licence fee. The firm’s own data – generated…
Clearstream Partners with Ares to Boost Access to Private Markets
Clearstream, the post-trade business of Deutsche Börse Group, has partnered with alternative investment manager Ares Management Corporation to add Ares’ private market strategies to its fund platform. The collaboration aims to simplify the investment process for fund distributors, allowing them to access private market investments with the same operational efficiency as traditional mutual funds. For…
MCPs in Data Management: Bringing New Order to Private Markets
Financial institutions have begun deploying Model Context Protocols (MCPs) as they have expanded the use of artificial intelligence applications and agents. The technology developed by Anthropic is an open-source contextual layer that helps coordinate models and data, enabling AI applications to connect with a multitude of other platforms and processes. In the first of a…
Direct Lending Practitioners Target Large Tech Budget Growth on Data
An overwhelming majority of private credit market practitioners are planning to substantially increase their technology budgets as they seek to address risks that are contributing to concerns about the direct lending sector. The Compass 2026 survey conducted for Oxane Partners – a technology provider for credit and other private markets – found that almost four-fifths…
Is the Real Value of Intraday Alternative Data in Risk, Not Alpha?
Intraday alternative data has long been the preserve of high-frequency and systematic desks, where speed provides an edge. But ask practitioners what decision it actually changes for a discretionary book, and the answer is rarely about generating a new trade, it is more about testing the one already on. Sizing, conviction and the risk sitting…
When Correlation Breaks: Why Crowding, Not Macro, Is Testing Quant Models
In February 2025, Goldman Sachs told clients the US equity market had become a stock-picker’s market: 74% of the typical S&P 500 stock’s return was being driven by company-specific factors rather than macro forces, against a 20-year average of 58%, and the bank expected that micro-driven environment to persist. Within weeks, sweeping tariff announcements had…
Where is the Edge When Everyone Has the Same Alt Data?
Has the institutional alternative data market reached a phase in which the easy sources of edge have closed? Datasets that once generated standalone alpha are widely distributed, the AI tooling layered on top of them is increasingly commoditised, and the differentiator has migrated to a less glamorous middle ground: validation, transformation, kill criteria, and the…