Key Trends
Interest Rate Cut & Monetary Policy Loosening
The Hong Kong Monetary Authority (HKMA) cut its base rate by 25 basis points to 4.50%, following the U.S. Federal Reserve’s similar move.
Reuters
Because the Hong Kong dollar is pegged to the U.S. dollar, HK’s rates are heavily influenced by Fed policy.
Reuters
Stimulus Expectations Driven by Weak Economic Data
Several economic indicators (e.g. weak retail sales, slowing home price gains, softer consumer demand) in China have fallen short of expectations. This has raised hopes that Beijing will roll out further stimulus.
Investors are anticipating more fiscal & policy support for consumption, technology, and infrastructure sectors.
Strong Mainland / Stock Connect Capital Inflows
Chinese mainland investors have been putting more money into Hong Kong via the Stock Connect
These flows are helping drive valuations in sectors preferred by mainland investors: new consumption, healthcare, and finance.
Futubull
Technology / AI Momentum
The tech sector, especially firms involved in AI, cloud, and semiconductor/AI‐infrastructure, has been outperforming. There’s renewed enthusiasm for Chinese tech/AI names after certain breakthroughs (e.g. DeepSeek) and government signals of support.
The Hang Seng Tech index has been rising, contributing significantly to overall market strength.
Valuation Pressure / Sector Rotation
Some defensive sectors (e.g. real estate, financials) have been under pressure, particularly when interest rates or Hibor (Hong Kong interbank) rates are expected to stay higher or rise due to monetary tightening or currency interventions.
There is rotation into growth / tech / AI and consumption‐related sectors, as investors seek upside, especially with rate cuts and stimulus on the radar.
South China Morning Post
The monkey believes that facts and science are the best ways to make decisions and predictions. That's why it created this website, to make different types of machine learning predictions and verify their accuracy. Although many people say that horse racing is unpredictable and random, I want to see what level of accuracy can be achieved by applying machine learning to this data.