Market & Alt Data Insight Historical, Fundamental & Index Data The latest content from across the platform
Alternative Data in Capital Markets Handbook 2026
Alternative data adoption in capital markets has moved into a more disciplined phase. Simply possessing a dataset is no longer a differentiator – the priority now is how data is sourced, synthesised and deployed, and how quickly granular, disaggregated signals can be turned into validated, decision-ready insight. The 2026 edition of the Alternative Data in…
Rethinking Alternative Data Infrastructure with Aerospike
Investment firms have never had access to more data. From corporate filings and social media to satellite imagery, transaction data and other alternative sources, the range of information that can potentially feed the investment process continues to expand. But as AI becomes embedded more deeply into research and investment workflows, the challenge is shifting. Simply…
S&P Global QnA: Adaptive Retrieval Smooths Data Access and Use
S&P Global Market Intelligence launched Adaptive Retrieval last month, promising to give clients greater flexibility in accessing and using the ratings giant’s data via their large language models (LLMs) and agents. Complementing S&P Global’s existing Deterministic Retrieval tool, which is built on the Kensho LLM-ready API, the latest innovation enables users to query and make…
Multiplying the Value of Unstructured Data
Financial institutions have spent years expanding the range of data available to investment, trading and risk teams. Increasingly, however, the challenge is not obtaining more data but making sense of what they already have. Unstructured data is estimated to account for 80-90% of the information generated withinfinancial institutions, encompassing everything from regulatory filings and earnings-call…
How ExtractAlpha Builds Trust in the Age of AI Signals
When a data provider sells raw data, the buyer can inspect what they are getting. When a provider sells a signal – a ranking, a score, a forecast of forward returns – the buyer is being asked to trust a research process they cannot necessarily see. That asymmetry sits at the centre of the systematic…
BMLL and SIGMA AI Partner to Benchmark Live Market Flow Against Historical Order Book Data
BMLL and SIGMA AI have announced a partnership combining BMLL’s historical Level 3, 2 and 1 order book data with SIGMA’s “Quant in the Cloud” streaming platform, producing an analytics layer that scores live market flow against historical benchmarks. The stated use cases are real-time anomaly detection, market regime classification and execution benchmarking, with anticipated…
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…
What Changes When 40 Years of Factor Analysis Takes Minutes?
What limits a research team when a piece of factor analysis that once consumed a morning of a quant’s time collapses into a single prompt and an answer? A recent collaboration between Axioma by SimCorp and the AI firm EDS brings the issue into focus. The answer it points to is no longer the cost…
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…
Recorded Webinar: The Data Foundation for Alpha – How fragmented data is eroding hedge fund performance
Alpha depends on more than models, talent and execution. It depends on the quality, consistency and timeliness of the data behind every investment decision. Many hedge funds still operate with fragmented datasets, inconsistent identifiers and manual reconciliation processes that slow research, distort signals and increase operational risk. As firms scale across strategies, regions and asset…