ASKANNALEE · LIVE PROSPECTIVE ANALYSIS

Singapore New Launch Investment Analysis

Independent, numbers-first analysis of Singapore new launches before the outcome is known. We test price, value, risk and exit so buyers can decide whether the numbers justify buying.

PRICE

What are buyers paying?
VALUE

What is it worth?
RISK

What if assumptions fail?
EXIT

Who buys it from you later?
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Every published AskAnnaLee new-launch review appears here automatically when it is assigned to the New Launch Analysis category.

HOW WE ANALYSE

Evidence → Analysis → Risk → Decision

1. Establish the Facts

Verify the project, land, location, supply and transaction evidence before forming an investment view.

2. Test the Price

Compare asking PSF and total price with meaningful comparables, land economics and a disciplined value range.

3. Stress the Exit

Test financing, rental support, future supply, buyer affordability and who may realistically buy from you later.

4. Make the Decision

Separate project quality from investment quality and conclude BUY, BUY SELECTIVELY, NEGOTIATE, WAIT or AVOID.

FROM TODAY TO HISTORY

See How the Same Framework Performs on Past Projects

Current analyses are made before the outcome is known. Our separate historical backtest library applies frozen decision rules to earlier launches so live analysis and hindsight evidence do not get mixed.

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Read Our Methodology

ASKANNALEE · NEW LAUNCH INVESTMENT ANALYSIS

Price is not value. Each report examines the project as an investment: what buyers are paying, what could go wrong, and who may buy from you later.

The Florence Residences: Two Units We Would Have Bought — and One We Would Have Missed

ASKANNALEE · HISTORICAL BACKTEST

The Florence Residences: Two Units We Would Have Bought — and One We Would Have Missed

This project gives us a useful real-world lesson. Two exact units were comfortably below our maximum price and later made good gains. Another unit was just above our limit, so we would have rejected it — yet it also performed very well.

Historical Purchases2019–2020
Main Size Tested1,270 sq ft
Maximum Price~S$1.842m
Overall ResultPASS
Historical Backtest
This is a look back using our current buying rules on old transactions. We did not recommend these units at the time. We first decide what we would have paid using the information available then, and only afterwards check what happened to the actual units.

The simple result

We found two exact 1,270 sq ft purchases below our maximum price of about S$1.842 million.

One later gained about 41.3% over 4.3 years. The other gained about 18.2% over 3.1 years.

Both comfortably passed our minimum 5% appreciation test.

HISTORICAL RESULTPASS

1. What Buyers Were Looking At

The Florence Residences is a large 1,410-unit project in the Hougang/Kovan area. Historical launch research showed indicative pricing around S$1,400 psf, with published pricing later around S$1,450 psf.

For our backtest, the important question is not whether the development was popular. It is whether individual buyers could find units at prices that gave them enough room for mistakes or a slower market.

We do not need the cheapest condo. We need a sensible price for the particular unit we are buying.

2. How Much Would We Have Paid?

For a 1,270 sq ft unit, our historical calculation put its value at about S$2.026 million.

We would not pay the full calculated value. After keeping our safety cushion, the most we would have paid was approximately:

S$1,841,675 for a 1,270 sq ft unit.

Put simply: below about S$1.842 million, we would consider buying. Above that, we would become more cautious.

3. Buyer One Paid S$1.762 Million

Unit #03-12, measuring 1,270 sq ft, was bought on 11 May 2020 for S$1.762 million. That was about S$79,700 below our maximum price.

The exact same unit later sold on 23 August 2024 for S$2.490 million.

Bought ForS$1.762m
Sold ForS$2.490m
Gain+41.3%

The owner held it for about 4.3 years, which sits comfortably inside our normal 3–5 year checking period.

4. Buyer Two Paid S$1.776 Million

Unit #10-12 was bought on 15 September 2019 for S$1.776 million. It was also below our S$1.842 million maximum.

The first sale by that original buyer was on 19 October 2022 for S$2.100 million.

Bought ForS$1.776m
Sold ForS$2.100m
Gain+18.2%

The holding period was about 3.1 years. Again, this passed our minimum 5% test.

5. So Did Our Price Limit Work?

For these two exact purchases, yes.

UnitPurchase PriceOur MaximumLater Gain
#03-12 · 1,270 sq ftS$1.762m~S$1.842m+41.3%
#10-12 · 1,270 sq ftS$1.776m~S$1.842m+18.2%

Both buyers paid below our limit, and both later made meaningful gains.

6. But We Would Have Missed a Very Good Purchase

This is where the backtest becomes more useful.

A 1,389 sq ft unit, #14-62, was bought for S$2.017 million. Our maximum price for that size was about S$2.014 million.

The buyer therefore paid only about S$2,759 more than we were prepared to pay — roughly 0.14%.

Under our rules, we would have said no.

The exact same unit later sold for S$2.668 million after about 3.6 years, giving the buyer a gain of roughly 32.3%.

We would have missed this winner.
That does not mean we should rewrite our price limit after seeing the result. It means any fixed maximum price will occasionally reject a good purchase that sits just above it. A credible backtest should show those misses as well as the successes.

7. The Same Project Also Had a Losing Unit We Would Have Rejected

The other side of the story is equally important.

An exact 667 sq ft unit was bought for S$1.371 million. Our maximum for that size was only about S$967,000, so we would not have bought it.

About four years later it sold for S$1.270 million — a loss of roughly 7.4%.

So within the same project, paying well above our limit produced a poor outcome, while paying below our limit produced two good outcomes.

8. What About Other Units We Rejected?

Not every rejected unit lost money. Two smaller units that were above our maximum later gained around 7.7% and 8.4%. Those buyers still made money, but the results were much weaker than our two qualifying 1,270 sq ft examples.

This is why the aim is not to predict every winner. The aim is to improve the odds of buying with enough room for error.

9. What We Learned

Buying below our maximum worked well in the two exact cases we found.
They returned about 18% and 41% within our normal checking period.
A fixed price limit will sometimes make us miss a winner.
The 1,389 sq ft unit was only slightly above our limit and later gained more than 32%.
Being far above our price limit can be dangerous.
One exact 667 sq ft purchase well above our maximum later lost about 7.4%.
We should never say “The Florence Residences was a BUY.”
The evidence says certain units at certain prices were attractive. Other units were not.
Do not change the rules after seeing the result.
If we move our maximum price every time a rejected unit later makes money, the backtest becomes meaningless.

10. Final Result

PASS — with an important missed winner

Two exact purchases below our historical maximum both produced gains above 5% within roughly 3–5 years.

At the same time, the model would have missed at least one excellent purchase that was only slightly above our price limit. We publish both results.

THE FLORENCE RESIDENCESPASS
Historical Backtest Disclosure
This analysis is retrospective. AskAnnaLee did not recommend these units in 2019 or 2020. Historical results are used to test our current method and do not guarantee future performance.
ASKANNALEE BACK TEST

The project name does not decide whether we buy.

The Florence Residences shows why our decision must come down to the actual unit and the actual price. Two units were cheap enough for us. One excellent winner was just outside our limit. Another expensive unit later lost money. That is the full story.

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✓ Value & risk — what deserves attention before committing capital.

✓ Financing & affordability — whether the purchase remains comfortable.

✓ Supply & exit demand — who may realistically buy from you later.

✓ Unit-type considerations — which characteristics deserve closer examination.

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