{"id":39229,"date":"2024-10-16T10:48:31","date_gmt":"2024-10-16T14:48:31","guid":{"rendered":"https:\/\/www.bloomberg.com\/company\/press\/a-team-bloomberg-enhances-credit-risk-signalling-tools-that-forecast-the-barbie-party\/"},"modified":"2024-10-16T10:48:31","modified_gmt":"2024-10-16T14:48:31","slug":"a-team-bloomberg-enhances-credit-risk-signalling-tools-that-forecast-the-barbie-party","status":"publish","type":"press","link":"https:\/\/www.bloomberg.com\/company\/press\/a-team-bloomberg-enhances-credit-risk-signalling-tools-that-forecast-the-barbie-party\/","title":{"rendered":"A-Team | Bloomberg Enhances Credit Risk Signalling Tools That Forecast the Barbie Party"},"content":{"rendered":"
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This article was originally published by A-Team Data Management Insights<\/a>.<\/em><\/p>\n

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Barbie and her pals no doubt threw a huge party when the company that makes the iconic doll, Mattel, saw its debt upgraded from junk to investment grade by the three major credit rating firms earlier this year. Had they spoken with some market watchers, however, the Barbieland party could have started months \u2013 maybe years \u2013 earlier.<\/p>\n

Traders were already attuned to the corporate improvements that had spurred the California-based company\u2019s upgrade when it happened in February, even before the box-office success of the film based on the doll\u2019s adventures had elevated Mattel\u2019s prospects. By watching the company\u2019s bond prices and data on its fundamentals and a range of other indicators, they knew that the sub-investment grade rating under which it had languished for years was now out of date.<\/p>\n

Those in the know traded accordingly and cleaned up. Those who didn\u2019t have the capabilities to properly assess the company had no such luck.<\/p>\n

According to Bloomberg global head of risk and investment analytics products, Zane Van Dusen<\/strong>, the reason that more firms didn\u2019t profit was because not all traders can effectively feed the corporate-specific information to which they are privy into their firm\u2019s operational knowledge banks.<\/p>\n

\u201cIt took many months for the rating agencies to come to a consensus that Mattel belonged in the investment-grade sector,\u201d Van Dusen told\u00a0Data Management Insight<\/em>. \u201cBut if you look at market sentiment you can see from bond market activity that Mattel\u2019s yields decreased pretty significantly all the way back in 2022, giving an early signal that the back office might need to prepare for this name becoming part of their investable universe.\u201d<\/p>\n

Bridging the Gap<\/strong><\/h2>\n

This disconnect between the front and back office is potentially costing firms dearly as they try, and often fail, to forecast the market. Traders and their colleagues are privy to information through their day-to-day activities that isn\u2019t always easily transferred back to the firm\u2019s risk, research and other teams that help shape investment strategy. That gulf of information was part of the drive behind Bloomberg\u2019s recent upgrade to its market-implied probability default (MIPD) solution, a key forecasting data tool.<\/p>\n

Launched in 2021<\/a>, MIPD offers visibility into fixed-income markets by incorporating data from the company\u2019s evaluated pricing service (BVAL). MIPD provides early-warning indicators that quantifies the impact of news and events on a company and quickly reacts to changing market and issuer-level conditions. It builds par yield curves on more than 30,000 issuers to offer default probabilities and implied credit default swaps spreads, among other metrics.<\/p>\n

In the summer, MIPD was upgraded with the addition of five years of history that enables back-testing of early-warning indicators. Its functions were also enhanced to provide deeper insights into the data and to improve user friendliness with new \u201ceasy button\u201d calculations, like how an issuer\u2019s current default probability compares to its historical levels, so risk managers in the back office can quickly survey hundreds to thousands of names at once.<\/p>\n

Van Dusen explained that MIPD, when used with other Bloomberg tools, can help firms bridge the information gap between front and back offices.<\/p>\n

\u201cOn the front-office side, you are covering maybe a specific sector or even a subset of names within that sector, so you know those names really, really well and what exactly is going on with them even if it\u2019s not front-page news,\u201d he said. \u201cIf you\u2019re a second- or third-line risk manager, however, you\u2019re looking at the names everyone in the front office covers. This could be hundreds, if not thousands of companies. As a result, the back office doesn\u2019t have the capacity to do the same kind of manual analysis.\u201d<\/p>\n

Multiple Sources<\/strong><\/h2>\n

Bloomberg relies primarily on market data like bond prices to provide those signals for MIPD and converts the data into standardised risk indicators for different companies. Bond prices are regarded as a better gauge of corporate performance and sentiment because only institutions tend to trade in corporate debt and yields are less prone to the sort of irrational trading frenzies that can affect equities. Additionally, they are closely correlated to news sentiment, which is difficult to quantify.<\/p>\n

Those risk forecasts are reassessed programmatically daily in MIPD to accurately reflect changes in sentiment that the rating agencies might take longer to show in their ratings, Van Dusen said.<\/p>\n

\u201cMy goal is to convert your front-office intuition into a data feed so that you are speaking the same language as the back-office guys,\u201d he said. \u201cBecause there\u2019s knowledge there that can be converted into data. What we are doing, essentially, is our best approximation of taking that front-office perception and market sentiment and turning it into numbers.<\/p>\n<\/div>\n\n<\/div>\n\n\n<\/div>\n\n\t\t\n\t<\/div>\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"This article was originally published by A-Team Data Management Insights. Barbie and her pals no doubt threw a huge party when the company that makes the iconic doll, Mattel, saw its debt upgraded from junk to investment grade by the three major credit rating firms earlier this year. Had they spoken with some market watchers, [...]","protected":false},"featured_media":39230,"template":"","format":"standard","categories":[1469],"press_tag":[1424,2074,1347,1331,1423,1932],"class_list":["post-39229","press","type-press","status-publish","format-standard","has-post-thumbnail","hentry","category-announcements","press_tag-credit-risk","press_tag-data-license","press_tag-enterprise-data","press_tag-media-mentions","press_tag-mipd","press_tag-zane-van-dusen"],"yoast_head":"\nA-Team | Bloomberg Enhances Credit Risk Signalling Tools That Forecast the Barbie Party | Press | Bloomberg LP<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.bloomberg.com\/company\/press\/a-team-bloomberg-enhances-credit-risk-signalling-tools-that-forecast-the-barbie-party\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" 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