Investment Score

Investment potential score distribution

How to Read the Investment Score Insight

Key Takeaways

  • This insight is powered by live URA and HDB transaction data refreshed monthly.
  • Use the district filter above the chart to narrow results to a specific planning area.
  • Hover any data point on the chart for exact values and transaction counts.

What It Does

The Investment Potential Score ranks all 3,400+ ShiokNest-tracked developments on a 0–100 scale based on seven weighted factors: 5-year PSF price momentum, gross rental yield, transaction liquidity, MRT proximity, remaining lease, district market segment premium, and en-bloc potential. The score surfaces developments that combine multiple investment-favourable signals simultaneously — rather than being strong on one factor but weak on others. A development that scores 78 has above-aver...

Why It Matters

Most property investors in Singapore evaluate investments by a single metric — typically gross rental yield or recent capital appreciation — and miss the interplay between factors that determines the total return profile. A development with 4.8% gross yield in a district with declining transaction volume, 40 years of lease remaining, and 700m MRT walk is not a better investment than a 3.9% yield development with high liquidity, 99yr freehold, and 200m MRT walk. The yield advantage is r...

How It Works

  • Select a district from the filter or leave it blank to view Singapore-wide data.
  • Use the time-range buttons (1Y/2Y/3Y/5Y/All) to adjust the chart window.
  • Hover any point on the chart to see exact values and underlying transaction counts.
  • Review the KPI cards above the chart for headline numbers at a glance.

Examples

OCR shortlist above score 65: finding mass-market value plays

Inputs
Segment filter
OCR only
Score threshold
≥ 65
Bedroom filter
2-bedroom
Sort by
Investment Score (descending)
Results
Matching developments
~52 (from 3,400+)
Top-scoring cluster
D19 and D20 — high yield, strong MRT proximity, freehold stock
Yield range (top 10)
3.8%–4.6% gross yield
Liquidity (top 10)
18–42 transactions/year per development

How to read this: The OCR 65+ filter narrows 3,400 developments to 52 that score well across multiple investment factors simultaneously. The D19 and D20 cluster dominates because these districts combine: competitive gross yield (above-median for OCR), above-average MRT proximity (multiple NEL/CCL stations), freehold or long-remaining leasehold tenure, and enough transaction volume to support exit liquidity. An investor who previously evaluated yield in isolation might have missed that several D2x developments have stronger total return profiles than some apparently higher-yield D14 developments with thin secondary markets and depreciating lease terms.

Score vs yield discrepancy: why a high-yield unit scores low

Inputs
Development A
D5 development: 4.8% yield, score 41
Development B
D15 development: 3.9% yield, score 69
Question
Why does B score 28 points higher despite lower yield?
Results
Development A liquidity
5 transactions/year — very thin market
Development A lease
57 years remaining — accelerating decay from ~2030
Development B liquidity
31 transactions/year — deep market
Development B tenure
Freehold — no lease decay drag

How to read this: Development A's 4.8% yield is real — but it comes with 57 years of remaining lease (meaning annual lease decay of ~1.3% in value by 2030 under SLA guidelines), and only 5 transactions per year means exit liquidity is a serious concern. Development B's 3.9% yield is lower, but freehold tenure eliminates lease decay, and 31 annual transactions mean an exit can be executed within 1–2 months at market price. The score correctly identifies B as the stronger investment, even though A would win a single-metric yield comparison. This is exactly the multi-factor visibility the Investment Potential Score provides.

Tips & Pitfalls

Expert Tips

  • Compare 2–3 districts side-by-side to spot relative outliers rather than reading a single number in isolation.
  • Always check the transaction count alongside any price metric — small sample sizes can produce misleading averages.
  • Pair this insight with the related calculators and maps below for a complete decision framework.

Common Pitfalls

  • Interpreting short-term movements (under 1 year) as trends — Singapore property data is noisy and needs a longer window.
  • Ignoring the difference between median and mean — means are pulled by luxury outliers in prime districts.
  • Forgetting that new-launch prices are often subsidised by developer discounts not visible in headline data.

Frequently Asked Questions

Where does the data come from?
Data is sourced from the Urban Redevelopment Authority (URA) and Housing & Development Board (HDB) official APIs, refreshed monthly.
How often is this insight updated?
The underlying transaction data is synced monthly from URA and HDB. The charts recompute live as new data arrives.
Can I filter by district?
Yes — use the district filter above the chart. You can also share a deep link to a specific district via the URL.

Related Resources

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