Condos Near Mrt Stations Singapore: a spotlight on Singapore condos meeting this specific criterion. Use this lens to filter the broader market down to a manageable shortlist matched to your specific buyer profile and priority weighting. The category is best understood through transacted-data verification rather than asking-price snapshots (as of 2026-Q1).
Singapore’s private residential market spans approximately 3,500 condo projects across 28 districts. Filtering to a specific spotlight category — Condos Near Mrt Stations Singapore — is the practical way to narrow the search from impossible to tractable. The category lens (commute-focused) matches buyers whose priorities align with the spotlight criterion.
The dataset to read is the URA Property Data portal for verified transacted caveats, supplemented by ShiokNest’s per-project aggregations covering price, rental, walkability, en-bloc, and investment scores. The price heatmap visualises district-level concentration; the comparison tool lets you place candidates side-by-side.
The cost-of-entry context applies to every category: SORA-pegged mortgages at ~4% effective via the MAS SORA dashboard, BSD progressive 1%–6%, ABSD by buyer profile per the IRAS ABSD schedule. The category lens doesn’t change the tax or financing framework — it changes which projects are in the shortlist.
Overview
The most affordable condominiums near MRT stations, sorted by average PSF across six major MRT lines — ideal for commuters and investors seeking transport-linked value.
- FUYONG ESTATE is the best-value MRT-linked condo at $298 psf PSF.
- MRT proximity typically commands a 5–15% price premium, but these condos show it can still be affordable.
- Properties within 500m of an MRT station enjoy stronger rental demand from commuter tenants.
Rankings
| # | Name | District | MRT Line | Avg PSF |
|---|---|---|---|---|
| 1 | FUYONG ESTATE | D23 | EWL | $298 psf |
| 2 | NORTHSHORE BUNGALOWS | D19 | NEL | $396 psf |
| 3 | NORTHSHORE BUNGALOWS | D19 | DTL | $396 psf |
| 4 | NORTHSHORE BUNGALOWS | D19 | TEL | $396 psf |
| 5 | KIARA 10 | D14 | EWL | $559 psf |
| 6 | KIARA 10 | D14 | DTL | $559 psf |
| 7 | THE WOODS | D22 | EWL | $572 psf |
| 8 | THE HILLOFT | D23 | EWL | $576 psf |
| 9 | TERESA VILLAS | D4 | CCL | $591 psf |
| 10 | CHARLTON RESIDENCES | D19 | NEL | $592 psf |
| 11 | CHARLTON RESIDENCES | D19 | DTL | $592 psf |
| 12 | CHARLTON RESIDENCES | D19 | TEL | $592 psf |
| 13 | 8 @ STRATTON | D28 | NEL | $603 psf |
| 14 | SURIN VILLAS | D19 | NEL | $622 psf |
| 15 | SURIN VILLAS | D19 | DTL | $622 psf |
Top 3 Highlights
Evaluating the Condos Near Mrt Stations Singapore category requires the following framework:
- Verified transacted data — asking prices and developer marketing materials are not the authoritative source. Pull recent caveats from URA REALIS for the projects you shortlist.
- Category-specific KPIs — walking distance to MRT (verified, not as-the-crow-flies). 500m is the standard premium threshold.
- Tenure and lease-decay considerations — freehold projects avoid the 30-year financing minimum and 60-year CPF cap path entirely. 99-year leasehold faces these constraints as the building ages.
- Capital-appreciation trajectory — cross-reference each candidate against URA Property Price Index sub-segment performance over 3–5 years to identify outperformers and underperformers within the category.
For the Condos Near Mrt Stations Singapore shortlist specifically, the buyer should run each candidate through three lenses: (a) cost via the BSD/ABSD calculator, (b) financing via the mortgage calculator at the relevant SORA-linked rate, and (c) yield via the buy-to-rent ROI calculator. The composite output is a cost-and-return picture across the shortlist.
The macro context matters even at the spotlight-category level. The current 60% foreigner ABSD plus 20% SC second-property ABSD constrains demand particularly in CCR luxury and shoebox investor stock; OCR upgrader categories and 3-bedroom family stock face less demand-side pressure. Category-level analysis should therefore consider not just the project attributes but also the buyer cohort dominating recent transactions in that segment. Use the URA segment data for cohort context.
Forward-looking dimensions: GLS-driven new-launch supply, en-bloc activity in surrounding plots, and MRT-line extensions can change the spotlight-category landscape over time. The URA GLS schedule and the LTA Land Transport Master Plan are the canonical forward references.
- First-time SC buyer: Use the spotlight category as a starting filter but verify each candidate against the standard buyer framework (BSD/ABSD, TDSR, MRT, school). The 0% ABSD on first SC purchase is your biggest advantage; deploy CPF strategically via the CPF optimizer.
- HDB upgrader: For commute-focused priorities, balance the category criterion against the upgrade-path requirement (typically 3-bedroom family stock in RCR/OCR). Some spotlight categories may include units outside your typical search range.
- Investor (yield focus): If the category is yield-aligned, the shortlist is your target pool. If not yield-aligned, verify each candidate’s gross yield separately via URA rental caveats before treating it as investor-grade.
- Investor (capital appreciation focus): Cross-reference shortlist candidates against 3–5 year transacted-price trajectory. The category criterion alone doesn’t guarantee appreciation; tenure, district trajectory, and en-bloc potential are independent factors.
- Foreign buyer (60% ABSD): At 60% ABSD, only categories with strong long-horizon owner-occupier or trophy-asset positioning justify the entry. Yield-focused categories rarely work for foreign buyers under current cooling measures. Verify FTA-eligibility (US / Swiss / Liechtenstein / Norway / Iceland) before assuming the standard rate applies.
- Verify each candidate via the URA Property Data portal for transacted caveats.
- Use the ShiokNest comparison tool to place 2–3 candidates side-by-side on price, PSF, yield, walkability, and en-bloc scores.
- Calculate upfront cost via the BSD/ABSD stamp duty calculator for each candidate at your buyer profile.
- Stress-test affordability via the mortgage calculator and the TDSR/MSR affordability calculator.
- For investor analysis, run the buy-to-rent ROI calculator at current SORA-linked rates.
- Cross-reference district-level concentration via the price heatmap and the district comparison calculator.
Bull case for the spotlight category: The category lens identifies a high-conviction shortlist matched to specific buyer priorities — far more efficient than browsing the entire market. Concentration within a verified category often produces better outcomes than breadth across mediocre matches.
Bear case for over-narrowing: Filtering too aggressively risks missing units that meet the spirit (but not exactly the letter) of the category criterion. A unit that’s 550m from MRT but offers better view and tenure may outperform a 480m unit on overall buyer value. Use the category as a starting filter, not a final gate.
Frequently Asked Questions
How much premium do MRT-linked condos command?
Which MRT line has the most affordable condos nearby?
Does MRT proximity affect rental demand?
How current is the data?
URA caveats lodge with a typical 4–6 week reporting lag from transaction date. The shortlist reflects the most recent quarter or two of verified transactions. Rental caveats carry a longer 1–2 quarter lag. For real-time market context, cross-reference active listings on 99.co or PropertyGuru, but treat those as asking, not transacted, prices.
Should I prioritise yield or capital appreciation for this category?
The honest answer depends on holding horizon and tax position. Yield-focused investors typically prefer smaller units in well-connected RCR/OCR; capital-appreciation-focused investors typically prefer larger units in freehold prime CCR/RCR. Run both scenarios through the buy-to-rent ROI calculator with realistic exit-price assumptions.
Methodology & Sources
Figures below are drawn from all available transaction periods and revised on demand.
Transaction data sourced from URA.
- Rankings require a minimum number of transactions to qualify.
- Averages are used for price and PSF metrics; yields are estimated from average rent and average sale price.
- Last updated: 18 Jul 2026.
We report medians (not means) so a single outlier transaction cannot skew district-level figures. PSF = price per square foot.