Softer U.S. inflation lowers expectations for another Fed rate hike
publishers 17articles 17first reported 27 Sep, 19:55 UTCdeveloping since 28 Sep · 4 editions
A softer-than-expected U.S. inflation reading reduced market expectations that the Federal Reserve would raise interest rates again in October, after the central bank increased rates earlier in September for the first time since 2023.
The personal consumption expenditures price index rose 3.4% in August from a year earlier, below the 3.7% forecast by economists polled by Reuters, according to a Commerce Department report cited by The Guardian. Traders subsequently put the probability of an October rate increase at about 35%, down from roughly 45%, based on LSEG data.
Separate figures showed solid second-quarter U.S. economic growth, supported by consumer spending and business investment associated with artificial-intelligence infrastructure. Payroll processor ADP reported that private employers added 90,000 jobs in September, up from 36,000 in August and above expectations.
U.S. stock indexes initially rose Wednesday, although the S&P 500 closed 0.25% lower and the Dow declined 0.86%. The Nasdaq gained 0.24%. The 10-year Treasury yield held at 5.246%, one day after reaching its highest level since June 2007.
Investors were awaiting the Labor Department’s monthly employment report, expected to show that the economy added 84,000 jobs in September, compared with 162,000 the previous month.
HOW THIS STORY WAS MADE
Written from 8 articles, headlines and summaries only; 8 independent newsrooms once syndicated copies count as one; this version written 24 h after the record first saw the story; the editor kept it as written.
- Publishers
- 17
- Source articles
- 17
- Given to the writer
- 8, headlines and summaries only
- Independent newsrooms
- 8
- This version written
- 24 h after the record first saw the story
- Second model (editor)
- kept as written
- Publication gate
- passed
- Human review
- none
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 →