BREAKING LIVE All breaking →
News

Offshore yuan rebounds on PBoC fixing

by UCapital MediaUCapital News newsroom1 min read
Offshore yuan rebounds on PBoC fixing

The offshore yuan rose to around 7.13 per dollar on Thursday, paring back significant losses from the previous session, after the People’s Bank of China set a stronger-than-expected daily reference rate.


Prior to the market opening, the central bank set the reference rate at 7.1118 per dollar, firmer than Reuters' estimate of 7.1293.


Market sentiment was further supported by signs of easing US-China trade tensions, despite US Ambassador to China David Perdue suggesting that a highly anticipated meeting between President Donald Trump and President Xi Jinping is more likely to occur next year rather than this fall.


Meanwhile, the PBoC injected CNY 600 billion into financial institutions via its one-year Medium-Term Lending Facility, reinforcing efforts to maintain adequate liquidity in the banking system.


With CNY 300 billion in MLF funds maturing this month, the operation resulted in a net liquidity injection of CNY 300 billion—marking the seventh consecutive month of net MLF expansion.

yuancny
DISCLOSURE

UCapital Asset Management LLP or group companies may have commercial relationships with the companies mentioned. This content is not financial advice.

✦ Ask the AI about this article

Sign up for free to ask the AI about this article.

Analyse the markets with UCapital’s AI agents

Multiples, financials, sentiment and risks in 60 seconds, with live data.

Open Markets →

AI use policy. UCapital AI supports the newsroom with news analysis, summaries, market reactions, translations and the generation of cards and charts. AI-generated or AI-assisted content is labelled in the byline (AI Desk, a named AI profile marked «AI», or joint byline) and is reviewed by editors before publication. News received via API feeds from third-party providers is attributed to the original source. AI can make mistakes: report any inaccuracies to the newsroom. Users’ personal data is not used to train the models.