The offering aims to reduce challenges associated with going to multiple data providers for the best research data and equipping investors with the data and insights they need to get a competitive edge.

“Infinite computing power, data-friendly programming languages, machine learning tools, advances in AI and easy access to financial analytics has unlocked a vast and abundant set of new data sources for investors. Managing the amount of data that is available today — and gleaning insights not already discovered by the market — has become a massive undertaking,” said Tony McManus, Global Head of Enterprise Data at Bloomberg.

He added: “By pre-ingesting, mapping and linking many different data sources together, Bloomberg allows customers to significantly reduce the time needed to generate signals or insights. There is a significant demand for fundamental, quantamental and quantitative company research, and this new point-in-time data product is just part of the long-term investment we’re making to build out a deep, interconnected suite of company research products.”

With this launch, Bloomberg is responding to customers’ need for differentiated, value-adding data with standardized company-level fundamentals, estimates and deep industry-specific metrics, alongside macro information. The Company Financials, Estimates and Pricing Point-in-Time data product empowers customers to perform deep single company as well cross-company analysis, deriving insights into the key performance drivers of a company or a sector.

“A critical component of Bloomberg’s offering is its inclusion of true, historical point-in-time data, which is essential for accurate backtesting,” said Angana Jacob, Head of Research Data, Enterprise Data. “Without historical point-in-time data, models can overestimate returns due to survivorship bias and look ahead bias. What sets Bloomberg’s new data solution apart is that it empowers quants and research analysts with the insights they need to build accurate models that allow them to forecast as precisely as possible a security’s performance, and we are thrilled to provide institutional investors with this full picture they need to derive differentiated market insights.”

Key features of the new data offering include:

Historical Point-in-Time company actuals, consensus estimates, company guidance, historical identifiers, and pricing data for 58,000 public companiesClearly marked information when company revisions and Bloomberg corrections were made to company actualsPoint-in-Time Universe that avoids survivorship or lookahead bias by including all active and inactive companiesSelection of LTM (last twelve months) and as reported fields standardized across industriesAdjusted values for relevant Actuals, Estimate and Company Guidance fieldsFinancial ratios calculated daily and adjusted as neededForward Price, Share Count and Volume Adjustment Factors to make corporate action related adjustments which impact historical Price, Volume and Actuals RatiosEarnings Date and Time stamps for each reported fiscal period and Next Period Earnings DateBloomberg proprietary comparable fields aligned with the consensus estimates and company guidance forecasts allowing for accurate earnings surprise analysisCompany Financials, Estimates and Pricing Point-in-Time is the latest Bloomberg offering tailored to Quant customers who require new, better quality data and are eager to take advantage of advances in AI technology to find an edge in their investment process.

Bloomberg’s Enterprise Data Quant Solutions also include Company Revenue Segmentation Data and Company Industry Specific Fundamental Data products, covering a broad universe of companies and providing deep actionable insights, which seamlessly integrate with other datasets including alternative data. More information on these solutions can be found here.