Across the ten trading days in the Excel data (29–30 Jan and 4–6, 9–13 Feb 2026), price action looked more like sector rotation than a broad “risk-on” rally. Eighteen STI constituents gained over the window and twelve fell, with the average stock up about 1.3% (median about 0.9%). The dispersion was wide, with the best performer up about 13.8% while the weakest names fell about 4–5%, so stock selection mattered more than the index label.
This rotation happened against a backdrop of a strong Singapore tape, with the Straits Times Index pushing to record territory and crossing the 5,000 mark for the first time in early February.
A quick snapshot of the main movers (total price change from 29 Jan to 13 Feb, from the Excel data) is below.
Keppel’s move was the clearest “event-driven” burst in the Excel data, with its biggest one-day jump landing on 5 Feb (the same day it closed up about 6.1%). That lines up with headline catalysts: FY2025 results, a proposed special dividend, and board leadership changes that were widely reported locally and internationally. The fact that Keppel ended 13 Feb trading very near its 52-week high (per the Excel data) suggests the market treated the news as a re-rating moment rather than a one-day spike.
Singtel’s strength also looked catalyst-backed. The Excel data showed two sharp up-steps (notably on 4 Feb and again into 11–12 Feb), and Reuters reported that Singtel’s third-quarter underlying profit rose, helped by stronger contributions from associates like Bharti Airtel and AIS, alongside a large exceptional gain linked to trimming its Airtel stake. In simple terms, the market had both earnings momentum and a tangible capital-recycling headline to price in, which often attracts follow-through buying when sentiment is already constructive.
By contrast, the local banks collectively looked like they paused, not broke. In the Excel data, DBS drifted down steadily from 6 Feb into 13 Feb, while OCBC and UOB held up better but still ended slightly lower over the full window. That pattern matches a plausible “good news already priced / rates may be less supportive” narrative: Reuters reported DBS’ Q4 net profit missed forecasts and management flagged continuing headwinds from the interest-rate environment, with shares dipping after the results. A separate Business Times piece also highlighted the market’s tendency to compare banks versus yield assets as rate expectations shift. From a positioning angle, this looks like profit-taking and rotation into cyclicals/telcos, rather than investors abandoning the banks altogether.
Industrial and logistics REITs were the other visible soft patch. Several were not only down over the full window, but also sat below both their 50-day and 200-day average prices in the Excel data (a simple sign that their near-term trend still lacks support). Even while some commentaries were turning more constructive on S-REITs into 2026 as funding costs ease, the Excel data suggests investors still discriminated at the stock level—especially where distribution growth is harder to defend or where refinancing narratives remain sticky.
Looking forward, the Excel data alone cannot “prove” which stocks will rise in the coming weeks, but it can highlight where momentum and market attention are already clustering. Keppel and Singtel stood out because the gains were large, the moves came with unusually heavy volume on key days (Keppel’s peak volume ran about 5x its 3-month daily average; CapitaLand Investment’s peak day was even higher), and the news flow had clear valuation anchors like dividends, earnings, and capital recycling. Singapore Airlines also trended up in a steadier “grind higher” profile through February in the Excel data; one near-term watch item is that corporate funding and capital structure actions (such as its S$500 million notes issuance reported by Reuters) can signal management’s readiness to invest through the cycle, though that does not automatically translate into share price upside.
A practical way to frame a core-and-satellite approach, based on what the Excel data showed, is to treat the core as the durable franchise names that investors tend to hold through rotations, then use satellites to express shorter-cycle views. A core sleeve could centre on the three local banks (even after the pullback in DBS), plus steadier industrial/defensive exposures like ST Engineering and selected large property/platform names where liquidity stays deep; this keeps the portfolio anchored if the rotation reverses. A satellite sleeve can then tilt towards the “attention stocks” that already show strong trend and volume confirmation, such as Keppel and Singtel, and selectively towards cyclical reopen/consumption proxies like Singapore Airlines, SATS and Genting Singapore if one accepts higher volatility and event risk. The Excel data also suggests some laggards (especially certain REITs and Seatrium) screen as “valuation rebound” candidates when you compare price versus analyst target fields, but their trend weakness means they work better as smaller satellites than as portfolio anchors unless price action stabilises.
If you want to do your own analysis, you can get the data I used for the price of a cup of kopi! Here:
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