Higher Yields Pressure Stocks as Bond-Market Concerns Spread
publishers 47articles 75first reported 23 Sep, 23:47 UTCdeveloping since 23 Sep · 40 editions
A selloff in U.S. and European government bonds deepened, pushing yields higher and contributing to a losing session for stocks. U.S. stock futures were little changed afterward as investors assessed how much further yields could rise and how higher borrowing costs might affect equities.
Signs of strain also appeared in lower-rated corporate debt. Bloomberg Law reported that CCC-rated debt entered distressed territory for the first time since the 2023 crisis, while reports from Finimize and Tech Times highlighted investor concern about increased corporate borrowing and growing exposure to securities viewed as bankruptcy risks. Deutsche Bank Wealth Management, however, described credit spreads as quietly resilient.
The pressure from rates comes after a third quarter in which market leadership shifted. According to CNBC, the iShares Expanded Tech-Software Sector ETF gained 17%, while the iShares Semiconductor ETF fell 11%. Salesforce rose 46%, Microsoft gained 37%, Workday climbed 55% and Veeva advanced 60% as fears that artificial intelligence would disrupt software companies eased. CNBC’s Jim Cramer said his main concern entering the new quarter was the effect of higher interest rates on stocks, particularly rate-sensitive companies.
HOW THIS STORY WAS MADE
Written from 8 articles, 1 with the publisher's own text; 7 independent newsrooms once syndicated copies count as one; this version written 48 h after the record first saw the story; the editor kept it as written.
- Publishers
- 47
- Source articles
- 75
- Given to the writer
- 8, 1 with the article's own text
- Independent newsrooms
- 7
- This version written
- 48 h after the record first saw the story
- Second model (editor)
- kept as written
- Publication gate
- passed
- Human review
- none
WHAT THE EDITOR DID
The second model checked the writer's draft against the same sources and published it as written.
Written by a language model from the sources above, then checked by a second model that may only cut, attribute or correct. How it works →