CCR vs RCR vs OCR

Market segment price trends over time

How to Read the Market Segments 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 Market Segments insight plots median PSF over time for Singapore's three official residential property segments — CCR (Core Central Region: D9, D10, D11, D1, D2, D6), RCR (Rest of Central Region: D3–D8, D12–D15), and OCR (Outside Central Region: D16–D28) — on a single dual-axis chart, allowing direct segment comparison. A secondary chart shows the CCR-to-OCR PSF ratio over time (the "segment premium"), which tracks whether CCR is becoming more or less expensive relative to ma...

Why It Matters

The relative performance of CCR versus OCR is the most important cycle indicator in Singapore property. During bull markets, CCR outperforms OCR significantly — foreign buyers and high-net-worth investors bid up prime district properties faster than mass-market supply. The CCR-to-OCR PSF ratio expanded from approximately 1.8× in 2009 to 2.4× by 2012, reflecting the intense overseas interest in Singapore prime property at that time. During corrections and cooling-measure periods, CCR ty...

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

CCR/OCR ratio at 1.65×: reading relative value in 2019

Inputs
Metric
CCR median PSF ÷ OCR median PSF (segment premium ratio)
Time point
Q3 2019
Context
Post-2018 cooling measure environment, ABSD at 25%/30%/35%
Results
CCR median PSF Q3 2019
~$2,420
OCR median PSF Q3 2019
~$1,460
CCR/OCR ratio Q3 2019
1.66× (near 10-year low)
Historical ratio average
~2.0× (2012–2024 average)

How to read this: In Q3 2019, the CCR/OCR ratio was 1.66× — 17% below its long-run average of 2.0×. This reflected the disproportionate impact of 2018 cooling measures on the CCR segment, which relies more heavily on foreign buying (ABSD 20–25%) and investor demand. An investor entering CCR in Q3 2019 at this compressed ratio was effectively buying CCR at an unusually low premium to OCR. By Q1 2022, the ratio had reverted toward 1.9×, delivering outperformance of approximately 15% relative to OCR from the same starting investment. The segment ratio chart identifies these relative value windows historically — and makes the current ratio visible for comparison.

RCR defensive performance in 2019–2020: segment rotation signal

Inputs
Metric
YoY PSF change by segment (CCR, RCR, OCR)
Time range
2018–2020
Context
ABSD cooling, COVID lockdown period
Results
CCR YoY change 2018–2020
−2.1% cumulative (underperformed)
OCR YoY change 2018–2020
+1.4% cumulative (marginal)
RCR YoY change 2018–2020
+5.8% cumulative (outperformed)
Interpretation
RCR held and grew while CCR declined

How to read this: During 2018–2020, RCR was the only segment to post consistent positive PSF performance while CCR corrected and OCR stalled. This reflects RCR's defensive characteristics: genuine domestic-buyer demand from local upgraders moving into Queenstown, Marine Parade, and Katong; limited new supply; and lower ABSD sensitivity versus CCR. An investor who read the segment premium chart in late 2018 and noted RCR's historical tendency to hold up during CCR corrections could have shifted allocation from CCR to RCR — a trade that would have delivered meaningfully better risk-adjusted returns over the 2018–2021 period.

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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