Permutable at Eagle Alpha Alternative Data Conference New York 2026

Permutable will attend the Eagle Alpha Alternative Data Conference in New York on 10 September 2026. The article examines how institutional investors are moving from alternative data discovery towards explainable, point-in-time, production-ready intelligence, and outlines how Permutable supports macro, commodity, currencies and geopolitical research. It is aimed at hedge funds, asset managers, banks, quantitative researchers and institutional data teams globally.

We are pleased to announce that Permutable will attend the Eagle Alpha Alternative Data Conference in New York on 10 September 2026, joining institutional investors, hedge funds, asset managers, quantitative researchers and data teams assessing how alternative data is being used in investment research and production workflows.

Hosted by A-Team Group, the conference brings together data buyers and providers around the practical use of alternative data. The 2026 agenda includes macro quant strategies, forecasting intelligence, emerging risk signals, AI infrastructure, agentic financial workflows and the continued evolution of alternative datasets.

For Permutable, those themes sit directly within the problem at the centre of our work: how to turn fast-moving global information into structured, testable and explainable market intelligence.

Alternative data is moving beyond discovery

The institutional alternative data market has matured. Today, the question is no longer simply whether a new dataset is interesting but whether it is timely, point-in-time correct, historically consistent, explainable and practical to integrate.

A novel signal has limited value if a research team cannot determine what drove it, recreate the historical state visible at the time, or carry the same data structure from backtest into production. Institutional users need ways to organise fragmented information into signals that can be compared across markets, regimes and time.

This is particularly relevant in macro, commodities and geopolitical risk, where market-relevant information rarely arrives through a single channel. Inflation expectations may shift through local reporting, company commentary and policy language before confirmation in official data. Commodity risk can build through logistics, sanctions, weather, production commentary or geopolitical developments before those forces are fully reflected in price.

Alternative data becomes useful when those fragments can be structured consistently enough to test.

What Permutable provides to institutional investors

At Permutable, we convert global information flows into structured, source-linked intelligence across macroeconomics, commodities, currencies and geopolitical risk. The aim is not to replace traditional market or economic data, but to provide an additional information layer that helps investors measure how narratives, expectations and risk conditions are changing.

Our Global Macro Sentiment Indices produce hourly, point-in-time signals across more than 95 economies and 70 macro topics, with more than 11 years of historical data. The framework separates domestic and international information flows and provides directional and semantic signal layers, allowing researchers to examine not simply whether sentiment moved, but where the change came from and which economic themes contributed to it.

The same principle extends into commodities, FX and geopolitical intelligence. Rather than treating global news as an undifferentiated stream, our Intelligence Engine structures information around markets, entities, topics and drivers, with traceability to underlying sources.

For systematic teams, this can provide a feature layer, regime indicator, confirmation signal or risk overlay. For discretionary teams, it offers a way to monitor changes in market narratives at a scale difficult to replicate manually.

What makes alternative data usable in an institutional workflow?

The difference between an interesting dataset and an investable one often comes down to infrastructure and methodology. Institutional users should be able to answer a small number of basic questions:

• Was the historical observation genuinely available at that point in time?
• Can the signal be traced back to the information that produced it?
• Is the methodology consistent between historical research and live production?
• Can the data fit existing research, risk or trading infrastructure?
• Does it measure something sufficiently distinct from conventional market data to justify inclusion?

These questions become more important as investment firms incorporate machine learning, large language models and agentic systems into their workflows. Automation can increase processing speed, but it does not remove the need for lineage, reproducibility or controls around the underlying data.

For that reason, we see explainability and point-in-time integrity as core infrastructure requirements rather than optional product features.

Alternative data as an intelligence layer

At Permutable, we see the next phase of alternative data as increasingly connected to intelligence infrastructure rather than standalone datasets.

Investment teams already operate with large volumes of conventional data. However, the challenge is often understanding what is changing between formal data releases, which narratives are gaining importance, how local and international interpretations differ and whether developments in one market are beginning to transmit into another.

Structured narrative and sentiment data can provide that additional layer. Used correctly, it can help researchers identify questions worth investigating, test whether an emerging narrative has historically contained information, compare conditions across markets and monitor whether an established investment thesis is beginning to change.

The value lies in providing structure around information that would otherwise remain fragmented.

Meet Permutable at Eagle Alpha New York

Eagle Alpha’s upcoming Alternative Data Conference takes place in New York on 10 September 2026 and is designed around both data discovery and the practical deployment of alternative datasets within investment organisations.

Permutable will be attending to meet hedge funds, asset managers, banks, quantitative researchers and institutional data teams exploring new sources of macro, commodity, currencies and geopolitical intelligence.

For firms evaluating alternative data, we will be available to discuss dataset coverage, point-in-time history, API integration, source traceability, backtesting and specific research or production use cases.

If you are attending Eagle Alpha New York and would like to discuss how Permutable’s data could fit into your investment, research or risk workflow, contact our team to arrange a meeting during the conference.