New searchable catalogue gives institutional researchers direct access to sample data across macroeconomic sentiment, commodities and geopolitical risk

London, LONDON, Oct. 28, 2026 (GLOBE NEWSWIRE) -- Market intelligence and data provider Permutable today announced the availability of its data discovery catalogue, enabling institutional research teams to explore macroeconomic, commodity and geopolitical datasets and download samples.

Institutional teams can explore dataset coverage and download samples via Permutable's new data catalogue

The catalogue brings dataset descriptions, coverage, historical availability, update frequencies and delivery options into one searchable resource. Banks, hedge funds, asset managers and trading desks can search by topic, ticker or sector and inspect sample records before discussing broader historical access.

“Researchers need to understand what a dataset measures, what information was available at each timestamp and whether it fits their process,” said Wilson Chan, founder and CEO of Permutable. “The catalogue lets teams review coverage and inspect samples before defining a more detailed evaluation with us.”

Permutable transforms multilingual news and public information into structured sentiment indices, market-driver signals, historical time series and source-linked intelligence for institutional research, trading and risk workflows.

The catalogue includes Permutable’s Global Macro Sentiment Indices (GMSI), covering more than 90 economies and over 70 macroeconomic topics. GMSI provides hourly updates and more than 11 years of point-in-time history, with availability varying by economy, topic and configuration.

Topics include inflation, economic growth, monetary policy, fiscal conditions, labour markets, trade and geopolitical risk. Domestic and international perspectives allow researchers to compare reporting originating within an economy with external reporting about it.

Meanwhile, Permutable's commodity datasets organise information around supply disruptions, demand, inventories, geopolitics and policy. An energy researcher can investigate whether changing oil-market sentiment reflects a supply interruption, weakening demand or competing pressures, using supporting news records to examine the underlying developments.

“The first question is whether a dataset is relevant to the desk’s actual work,” said Michael Brisley, Chief Commercial Officer at Permutable. “A systematic team may need historical observations for model testing, while a discretionary researcher may want to investigate events behind a sentiment change. The catalogue helps both establish what is available and define a focused evaluation.”

Permutable’s point-in-time architecture preserves information available at each historical timestamp, helping researchers address look-ahead bias. Source-linked records allow teams to investigate the evidence contributing to signal changes and assess the data alongside existing datasets, investment factors and market prices.

Samples allow teams to inspect fields, timestamps and structure. Broader evaluations can be scoped around specific markets, topics and historical requirements, with delivery through Permutable’s Developer Platform, REST API and Excel plugin.

Explore the catalogue and download samples at www.permutable.ai/data/. For evaluation enquiries, contact enquiries@permutable.ai.

About Permutable

Permutable is a UK-based market intelligence and data infrastructure company specialising in macroeconomic narrative analysis and asset-directed sentiment tracking. The company develops proprietary datasets and models that analyse global information flows - including geopolitics, policy developments and supply dynamics - and translate them into structured signals for financial markets. Permutable’s macro and asset-level sentiment intelligence help banks, hedge funds, asset managers and trading desks monitor how evolving narratives influence commodities, currencies and macro assets. Built on strict point-in-time data architecture, Permutable’s technology is designed to support institutional research, modelling and market monitoring across global capital markets.

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