Bloomberg has launched a new enterprise dataset in a bid to expand its investment research data solutions for quantitative research and systematic investing workflows.
Colette Garcia
The new offering – the Economic Releases and Surveys Point-in-Time (PiT) dataset – is available through Bloomberg Data License, and will provide access to more than 3,000 market-moving economic indicators and government auction events spanning an excess of 100 economies.
The dataset also spans historical, time-stamped observations from 1997 onwards, and will support macro signal creation as well as cross-asset models, to provide a foundation for analysing market responses spanning rates, FX and equities across the entire investment workflow.
“Macro strategies are fundamentally driven by expectation formation and the market’s response to new information,” said Angana Jacob, global head of investment research data at Bloomberg.
“This dataset enables clients to model that process in a point-in-time framework, capturing forecast updates, consensus evolution, and full revision histories. This provides a robust foundation for building macro signals and cross-asset models that are consistent from back testing to live trading environments.”
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Specifically, clients will be able to use to dataset to see information as it was available to market participants at the time of release, as well as draw comparisons between indicators across geographies and market themes.
In addition, the dataset spans three components, including a forward-looking calendar to help users anticipate market catalysts, actuals and surveys to capture economic values and forecasts and changes, which record intraday updates to Bloomberg’s survey of economists’ forecasts.
“Real-time and historical consistency is essential for clients building event-driven strategies,” said Colette Garcia, global head of real-time content at Bloomberg.
“By aligning our point-in-time and real-time offerings, we are providing a unified framework that supports the entire investment workflow, from initial model research to market execution.”
Recently, Bloomberg made enhancements to its existing real-time news feeds offerings in March 2026, enabling customisable capabilities to deliver machine-readable news.
By delivering these capabilities, the firm aims to reduce manual processing for its clients, by directly integrating high-quality, targeted news inputs into trading and risk workflows, spanning automated market-making, event-driven and quantitative trading.