Bloomberg today announced the launch of its new Digital Asset Exposure Analytics, providing transparency into the direct and indirect exposure of a broad range of assets including spot currencies, futures, options, and equity tickers for companies with crypto activities, as well as funds holding these assets. Available via Data License for enterprise-wide use, Bloomberg’s new analytics is the first solution to automatically identify banks’ and asset managers’ exposure to crypto assets across their investments, detail the percent of allocation to crypto assets within funds, and disclose the specific crypto-related assets within a fund. 

Crypto assets are increasingly embedded in products like ETFs, which can make it difficult for asset managers to quickly understand how much or how little crypto exposure they have embedded within their portfolios. This presents challenges for asset managers who must navigate a spectrum of investor preferences—from those eager to embrace crypto to those seeking to avoid it entirely. At the same time, banks also need to maintain robust oversight of their exposure levels to prevent over-concentration, just as they would with any other asset class.

“While it seems like a simple question, ‘what is my exposure to cryptocurrencies’, the answer is surprisingly difficult to find,” said Zane Van Dusen, Global Head of Risk & Investment Analytics Products at Bloomberg. “To do this properly, you need to stitch together a diverse group of data sets ranging from foundational reference data to a company’s revenue segmentation to a fund’s holdings, which is difficult to scale without automation. Given these dynamics, we developed intuitive analytics building off our interoperable datasets so clients can quickly and confidently understand their degree of cryptocurrency exposure and adjust it to match their investment strategy.”  

How it Works

Bloomberg’s Digital Asset Exposure Analytics aggregates Bloomberg’s foundational security-level fund reference data and fundamentals data with Bloomberg’s Company Revenue Segmentation Data Solution, then applies an automated rules engine to identify securities with exposure to crypto assets. Direct exposure is defined as instruments whose value is directly derived from one or more crypto assets, whereas indirect exposure is defined as a company that discloses operations or services in crypto-related sectors. 

Utilizing Bloomberg’s Funds Data Solution, these analytics go one step further by taking the underlying fund holdings data to calculate the market value weight of the direct and indirect exposures for funds and ETFs and publishing the constituents that contribute to these exposures. Bloomberg curates constituents and as-reported holdings data for over 110,000 unique portfolios, with more than 70% of them updated more frequently than regulatory requirements, and over 1 million mapped securities. This level of granularity is important because it allows asset managers to precisely adjust their portfolios to meet their crypto exposure criteria. 

Use of these analytics can also be experienced with Bloomberg’s Investor Protection regulatory data solution, which covers virtual assets such as crypto currencies, digital tokens and other digital commodities, to help clients comply with regulations such as Hong Kong SFC circular on distribution of virtual asset funds.  

This type of automated analysis is possible given the depth, breadth and interoperability of Bloomberg’s Enterprise Data content which is built using open-source identifiers, such as the Financial Instrument Global Identifier (FIGI), proprietary Bloomberg identifiers, and detailed metadata. Bloomberg’s Digital Asset Exposure Analytics are available via Data License at data.bloomberg.com and can be delivered via SFTP, REST API or into a cloud environment.