Koen Batsleer presents an analysis of the value evolution of office buildings in Belgium using Officenter as a case study. Officenter acquired several office buildings between 2010-2022 but saw little net increase in building value, with average annual increases of only 2.3% compared to their 4% annual investment. While acquisition prices were typically 75-80% of assessed market value, attempted sales are often only at forced sale prices of 50-60% of market value. Research on commercial real estate yields, vacancy rates, and operating expenses in Belgium is limited compared to stocks and bonds.

1. fin POWER
Introductory presentation “in research of“
by Koen Batsleer, Finpower @ Officenter
VALUE EVOLUTION OF OFFICES IN BELGIUM
November 2023

2. I. Introduction & origin of analysis
II. Available research on real estate investment return
III. Own valuation-evolution model & REIT-check
IV. Optimizing our real estate value creation
V. Conclusions
VI. Reflexions
I. INTRODUCTION

3. I. Introduction
Who is Koen Batsleer ?
• Private
– Married with Marleen
• no kids, 2 dogs
– Born in Lovendegem/Lievegem,
lives in Hasselt
– Aiming for week-ends in Knokke
• Professional
– 1986-91: Generale Bank
– 1991 – … : Finpower
• Corporate consulting partnership (5 partners)
– 1999: co-founder of BAN Vlaanderen
– 2010 - … : Officenter
• Initiator
• CFO
• Academic
– 1980-84: Commercial Engineer (E.H.L.)
– 1985-86: Maîtrise en Administration et
Gestion (U.C.L., Louvain-La-Neuve)
– 2018-19 : Master in Real Estate (U.A.M.S.)
– 2020-21 : Doctorate in Business
Administration (Real estate, Vlerick, on hold)
• Hobbies
– Football, Tennis, Golf
• The ball becomes smaller with the years
– Tennis  padel since 2018
– Studying (since 2018 ...)

4. I. Introduction
Origin of analysis : Officenter - paradigma
1. From 1992 on :
– 25 year of corporate finance consultant within Finpower
– 1992: acquisition of an apartment in Genk (2  4 people)
– 1995: sale of apartment, acquisition of a villa in Genk (4  8 people)
• Sales price excl. VAT = cost-price – VAT ‘lost’
– 1998 : Construction of villa/office-building in Genk (200 m² , 8  20 people
• 2000 : financial crisis, from 16  11 people by 2002
• !! Loss of ‘transaction and renovation costs’ between every location switch
2. 2010 : Acquisition opportunity of ‘Officenter Building in Hasselt’
– Only 60 % occupation of building – rental income 200-300 k€
– Demand=acquisition price : 3,5 Mio or 780 €/m²
– Sales price of villa : 515,000 or 2,500 €/m²

5. I. Introduction
Origin of analysis : Officenter - paradigma
3. 2010 : Acquisition of ‘Officenter Building in Hasselt’
– Acquisition of the building at 780 € x 4,800 (BVO) = 3,75 Mio €
– Renovation in 2010 : 700 k€ (150 €/m²)
– Total investment : 4,3 Mio €Investment ‘8 friends’: 0,6 Mio €
• Bank-financing: 85 % - 3,7 Mio on 15 years
– At 2,25 % interest-rate, annuities of 293 k€/yr
– Rental income ‘was’ 280-320 k€ in 2005-2010
• At ’90%-occupancy’, we expected growth to 350-400 k€ in 2011-12
 Repayment of bank financing in 15 years.
– And, the value of our building will increase the following 15 years
Financing : € 3.700.000
Intrest 2,25%
Years : 15
Annuïteit € -293.368
… so, we would become rich while sleeping…

6. • Average increase/year 2010 – 2022 : 2,3 %
– Is lower than the yearly investment we have done in our centers (4%)
– Is also lower than the inflation (2,6 %)
• !! No net ‘increase’ in value of our buildings 
Increase in value of buildings (1) ?
I. Introduction
Origin of analysis : Officenter - paradigma
Value evolution of buildings OFFICENTER 'after renovation'
Uitbreiding 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
CAGR Investeri
ng/jaar
Netto
waarde-
evolutie
Hasselt (incl. Hub) 796.000 5.300.000 5.300.000 5.300.000 5.300.000 5.300.000 5.580.000 5.580.000 5.850.000 5.850.000 5.932.000 5.932.000 6.958.000 7.006.000 1,3% -4,9% -3,6%
Turnhout 3.200.000 3.574.000 3.674.000 3.674.000 3.674.000 3.674.000 3.797.000 3.920.000 3.920.000 3.991.000 4.120.000 4.442.000 3,0% -2,0% 1,0%
A12 (incl. buurpand) 300.000 2.630.000 2.630.000 2.630.000 2.630.000 2.630.000 2.692.000 2.725.000 3.025.000 3.066.000 3.195.000 3.304.000 1,2% -4,0% -2,8%
Maastricht 4.740.000 4.740.000 4.740.000 4.928.000 5.314.000 5.700.000 5.700.000 5.700.000 5.700.000 5.700.000 2,1% -8,4% -6,3%
Leuven (incl. nieuwbouw) 4.000.000 2.812.500 2.812.500 2.812.500 2.812.500 7.654.000 7.654.000 7.574.500 8.170.000 2,6% -1,6% 1,1%
Geel 2.900.000 2.900.000 2.927.000 2.981.000 2.998.000 4.968.553 11,4% -7,2% 4,1%
Brussel 3.880.000 3.880.000 4.127.000 4.127.000 4.246.000 4.325.000 2,2% -5,2% -3,0%
Aalst 5.894.000 5.894.000 6.221.000 6.680.000 4,3% -2,5% 1,7%
Zaventem 6.789.000 7.024.000 7.295.000 3,7% -2,0% 1,7%
Beringen 1.798.000 1.750.000 -2,7%
Genk 2.312.000 2.297.000 -0,6%
Pelt 2.582.000 2.500.000 -3,2%
Sint-Truiden 1.167.000 1.271.894 9,0%
Totalen 5.300.000 8.500.000 11.504.000 16.344.000 16.344.000 19.436.500 19.624.500 27.245.500 27.787.500 39.179.000 46.134.000 55.895.500 59.709.447 CAGR
Groei vanaf 2015 (jaarlijkse waardering panden) 0,0% 4,4% 0,9% 0,0% 1,7% 1,0% 4,3% 2,0% 2,6% 0,4% 4,1% 6,8% 2,3% -4,0% 1,0%
Inflatie 3,5% 2,8% 1,1% 0,3% 0,6% 2,0% 2,1% 2,3% 0,8% 0,4% 4,8% 10,4% 2,6%

7. • Sales price are in our acquisitions < valuation
– Between 90 and 54 % - average ca. 75-80 %
• Officenter Maastricht :
– Valuation 12/2022 :
• 8 Mio € ‘market value’
• 5,7 Mio € ‘forced price’
– Actually, looking for a buyer at 5,7 Mio …
Increase in value/price of buildings (2) ?
I. Introduction
Origin of analysis : Officenter - paradigma
Price/valuation Acquisition values Officenter
Valuation
Hasselt 2010 4.800.000 3.750.000 78%
Turnhout 2011 3.200.000 2.950.000 92%
A12 2012 2.500.000 1.925.000 77%
Maastricht 2013 2.880.000 2.250.000 78%
Geel 2016 2.108.000 1.876.000 89%
Vilvoorde 2016 2.600.000 2.000.000 77%
Aalst 2017 3.475.000 2.500.000 72%
Zaventem 2020 7.618.000 4.150.000 54%
Transaction-price (50%
latente belastingen)

8. • Real estate is clearly
under-studied in
comparison to stocks and
bonds.
• How many financial
advisors do you know vs.
experts in real estate ?
I. Introduction
Importance of the real estate market
Worldwide asset
Value (in Bio)
Academic articles
on SSRN
Real Estate 280.600 5.663
Bonds 126.900 9.106
Stocks 124.400 13.149
-
2.000
4.000
6.000
8.000
10.000
12.000
14.000
-
50.000
100.000
150.000
200.000
250.000
300.000
Real Estate Bonds Stocks
Academic research on real
estate vs. stocks and bonds
Worldwide asset Value (in Bio) Academic articles on SSRN

9. • Belgian real estate > 50 %
of total Belgian assets
• Residential real estate is
dominant:
– 7 x bigger than total
commercial real estate
– Of which ‘Offices’ are the
biggest segment
• < 4 % of residential market
• >< advisors in these market.
I. Introduction
Importance of the real estate market
Key figures Belgian real estate
Number of inhabitants 11.697.557 (1/1/2023)
Number of homes : 4.503.104 Mediaanprijs 2023
wv. Open bebouwingen 1.260.869 28% 365.000
wv. Gesloten en halfopen 1.797.235 40% 259.500
wv. Appartementen 1.445.000 32% 237.000
Inhabitants pro home : 2,6
Median Value pro home : 281.820
Total estimation of home-value 1.903.597.020.240
Pro Belgian : 162.735
Pro Belgian family: 422.730
Total commercial real estate market 258.000.000.000 14% Statista 2022, EPRA
Estimation of the office-market 72.456.000.000 24.000.000 m²
28% 3.019 €/m²

10. II. Available research on this topic
II.1 Cash-flow definition
Very well documented,
quarterly updates on yields,
vacancy, …
Less documented, main topic
of my (re-)search
Potential Gross Income P.G.I.
- vacancy allowance
+ other income
- operating expenses
Net operating Income N.O.I.
- Capital Improvement expenditures
+/- value evolution of property
==> Total return of property
Total return of a property

11. II. Available research on this topic
II.2 Income/yield of corporate real estate
• Prime Rents vary according to the real
estate segment
– Mainly ‘prime yields’ – easily available,
averages much less available
– Average yield very difficult to interpret
• Prime office rents vary in time and in
location
– Net evolution is increasing
– Corrected for inflation not !
Rents are the first income of every real estate, and are
function of location, time and product.

12. II. Available research on this topic
II.2 Income/yield of corporate real estate
• Yields very transparent available –
quarterly published by a lot of brokers
– Mainly ‘prime yields’ – easy available,
but no ‘averages’
– Average yield very difficult to interpret
• Definition of ‘different’ yields
• Prime yields > intrest rate
– ?? Risk/liquidity premium
– !! Value evolutioin
Yields are the main topic if discussing the return of real estate, but
the diversity is bigger, including the ‘definition’ of yield.

13. II. Available research on this topic
II.2 Income/yield of corporate real estate
• Prime office yields evolve
generally in line with the 10
years bond rate
– From 2012 – 2022 ‘lower’
• Why ?
• Increase in bond rates from
2022 on is not fully
absorbed by an increase in
the prime office yields
– Bond-rate from 0 tot 3 %
– Prime rate increase limited to
1 % actually, from 3 to 4 %
• Why ?

14. II. Available research on this topic
II.3 Occupation rate of corporate real estate
• Vacancy rates of real estate very
different:
– A lot of markets with more demand
than offer
• Vacancy < 5 %
• Residential, warehouses, student housing, ..
– But a lot of markets where offer is
higher than demand
• Retail, offices,
• Vacancy > 10 %
– High ‘yields’ is attractive for speculative
investment/holding
• Long term office vacancy appr. 10 %
– Increases due to WFH to > 20-30 %
– !! San Francisco

15. II. Available research on this topic
II.3 Occupation rate of corporate real estate
• Vacancy rate of offices seems to be
influenced by WFH :
– Working from Home
– >< look at this statistic from the
Netherlands in 2015 !
• We can suppose that in most real
estate market, we will build up to a
level that is exceeding demand.

16. II. Available research on this topic
II.3 Operating expenses of corporate real estate
• Higher in Dutch and international
markets.
• Academic research : the bigger the
REIT, the lower the costs (nvdr)
• Belgian Office-REITS are disappearing
– Lease-invest integrated in Nextensa
– Befimmo acquired by Brookfield (Canada)
– Intervest is in the process of being acquired by TPG
• Operating costs ‘Belgian’ office-REITS appr. 20
2020 Befimmo Cofinimmo
Intervest
Offices &
Warehouses
Leaseinvest Median NSI Vastned Wereld-have
Rental income : 130.782 212.170 61.303 61.572 83.721 77.060 196.754
Other income 18.695 -441 -51 -1.724 -1.239 -257 -7.762
Technical costs 12.160 6.421 876 871 6.400 6.027 21.789
in % of rental income 9% 3% 1% 1% 2,2% 8% 8% 11%
Costs and taxes of vacancies 2.723 4.489 892 1.345 2.075 475 22.638
in % of rental income 2% 2% 1% 2% 2,1% 2% 1% 12%
Commercial costs 1.998 1.791 318 970 2.949
in % of rental income 2% 1% 1% 2% 1,2% 4%
Property mgt cost : 2.628 17.573 5.281 6.410 3.907
in % of rental income 2% 8% 9% 10% 8,4% 5%
Corporate overhead : 14.729 7.531 4.085 2.065 7.950 8.753 18.405
in % of rental income 11% 4% 7% 3% 5,1% 9% 11% 9%
Net operational income 115.239 173.924 49.800 48.187 59.201 61.548 126.160
77,1% 82,0% 81,2% 78,3% 79,7% 70,7% 79,9% 64,1%

17. II. Available research on this topic
II.1 recap ‘return’ of property
Net operating income appr. 70
% of ‘gross potential income’
– Ca. 10 % vacancy allowance
– Ca. 20 % operating expenses
What would be the effect of
the value evolution ?
Potential Gross Income P.G.I.
- vacancy allowance
+ other income
- operating expenses
Net operating Income N.O.I.
- Capital Improvement expenditures
+/- value evolution of property
==> Total return of property
Total return of a property

18. II. Available research on this topic
II.4 Value evolution of real estate
Property Life Cycle
• Bokhari and Geltner,
2014
• Short term evolution
of P (property
evolution)
decreasing
• Long term
perception of prices
is increasing

19. II. Academic research on this topic
“Depreciation of value’ of U.S. real estate
– 2 axes :
• Location : the ‘better’ the location, the lower the average decrease (from 0 to > 2 %)
• Age: newer buildings decrease faster then older (from 0 to > 2 %)
– Both effects ‘enforce each other’

20. II. Academic research on this topic
“Depreciation of value’ of U.S. real estate
– Split out of ‘land value’ and ‘property-value
– Exponential evolution :
• In contradiction with often used ‘no decrease in value the first years …’
• 3 % decrease in value of ‘structure’ value

21. III. Own ‘valuation-evolution’ research
III.1 Cost of new office-buildings
• Decomposition of ‘sales price building
Officenter Vilvoorde in 1999 :
– Estimation of direct costs of project
developer
• Land  historical acquisitions
• Building costs estimated at that time
• Direct soft costs prudently estimated.
– Sales price in 1999 at Naviga publicly
available
• 1,478 €/m² based upon a 8,80 % yield
– Resulting in a profit margin of 22 % for the
developer
• Not abnormal in 1990 – 2018  decreasing yields
• Minimal targeted/budgeted profit margin of
developers: ca. 10 %
– Vs. average profit margin building companies: 3 % !
Decomposition of sales price '3T Estate' 1997 - 2000
Decomposition of 'development cost'
Purchase of land 4.500 21 95.616
Total direct building cost 4.118 800 3.294.400
Total direct soft costs 15% 508.502 (architect, project management)
Financial costs 5% 194.926
VAT 17% 646.493
Total development cost : 1.151 4.739.938
Rental revenu 1999 21.600.000 BEF 535.450
Yield 'verkoop aan Naviga' : 8,80%
Sale to Naviga: 4.118 1.478 6.085.290 in 1998
Profit of developper : 1.345.352 22%
P.S.: Rental contract ended in 2011, not occupied from 2012 –
2015 – bought by Officenter Vilvoorde in 2015…

22. III. Own ‘valuation-evolution’ research
III.1 Cost of new office-buildings
• Estimation of investment-cost of new
office-project
– Total investment cost, thanks to data of
Expertise
– Building costs decomposition:
• Carcass (1st fixing)
• Techniques
• Soft costs (VAT, fees, margin developper)
• Estimated, thanks to the experience of Bopro
• Residual is the ‘land value’ of the
project
• Estimated for CBD in 2020
– For 3 time-frames : 2020, 2005, 1990
– For 3 ‘locations’ : CBD, decentralized and
periphery.
• !! ‘Land-value’ relatively stable over time
(surprisingly).
1990 1990 1990 2005 2005 2005 2020 2020 2020
CBD
De-
central
Peri-
pherie
CBD
De-
central
Peri-
pherie
CBD
De-
central
Peri-
pherie
Land-value/m² 1.540 481 230 2.624 1.006 446 3.174 1.143 498
Carcass-investment/m² 750 650 600 850 750 700 950 850 800
Techniques-investment/m² 200 150 100 400 300 300 700 600 500
Soft-costs/m² 760 469 370 1.126 694 554 1.426 907 702
31% 37% 40% 29% 34% 38% 30% 35% 39%
Totale investment cost/m² 3.250 1.750 1.300 5.000 2.750 2.000 6.250 3.500 2.500
==> verkoopprijs excl. BTW/RR 2.754 1.448 1.063 4.262 2.301 1.644 5.317 2.914 2.050
2020
CBD
Land-value 3.174
Carcass : 950
Techniques 700
Soft costs (incl. VAT) 1.426
Total investment cost 6.250

23. III. Own ‘valuation-evolution’ research
III.1 Cost of new office-buildings
• Own estimation of investment-cost
of new office-project
– Total investment cost, thanks to data of
Expertise
– Building costs decomposition:
• Carcass (1st fixing)
• Techniques
• Soft costs (VAT, fees, margin developper)
• Estimated, thanks to the experience of Bopro
• Residual is the ‘land value’ of the
project
• Estimated for CBD in 2020
– For 3 time-frames : 2020, 2005, 1990
– For 3 ‘locations’ : CBD, decentralized and
periphery.
• !! ‘Land-value’ relatively stable over time
(surprisingly).
• First try, looking for better input.
1990 1990 1990 2005 2005 2005 2020 2020 2020
CBD
De-
central
Peri-
pherie
CBD
De-
central
Peri-
pherie
CBD
De-
central
Peri-
pherie
Land-value/m² 1 450 459 138 2 496 809 527 2 985 1 090 488
Carcass-investment/m² 700 600 550 800 700 650 900 800 700
Techniques-investment/m² 200 150 100 300 200 200 600 500 500
Soft-costs/m² 900 541 362 1 404 791 623 1 765 1 110 812
38% 45% 46% 39% 46% 45% 39% 46% 48%
Totale investment cost/m² 3 250 1 750 1 150 5 000 2 500 2 000 6 250 3 500 2 500
==> verkoopprijs excl. BTW/RR 2 745 1 446 934 4 249 2 081 1 653 5 298 2 909 2 049

24. III. Own ‘valuation-evolution’ research
III.2 Depreciation of new office-buildings
• Value-evolution hypotheses :
– Land: increases with 1,5 x inflation rate
(can be discussed) : 1,5 x 1,50 % = 2,25%
– Carcass: 50 years (estimated maximum life
time value of office-buildings in Belgium)
– Techniques : 15 years
– Soft-cost: 10 years
• +/- 1st rental contract duration
• Gives an evolution of price/value over
a 50 years span
– Compairable to ‘Property Life Cycle’

25. III. Own ‘valuation-evolution’ research
III.2 Depreciation of new office-buildings
• Cfr. Excell-sheet
• Berekeningen overlopen.

26. III. Own ‘valuation-evolution’ research
III.2 Depreciation of new office-buildings
• Calculated
‘averages/year)
– For the past (1990 +
2005 / 2)
• From + 1,0 % to -3,5
%
– For the future (2020
basis)
• Higher then in the
past
• From +0,8 % tot -4,0
%
• Is this real ?
Offices in Belgium: historical yearly value-evolution 'calculated'
Age Location ==> Average CBD Decentral Periphery
-0,8% 0,4% -0,8% -2,0%
-2,5% -1,3% -2,6% -3,5%
-0,8% 0,4% -0,8% -1,9%
-0,2% 1,0% -0,2% -1,5%
Offices in Belgium: calculated future yearly value-evolution
Age Location ==> Average CBD Decentral Periphery
-1,2% 0,3% -1,2% -2,6%
-2,8% -1,5% -2,9% -4,0%
-1,2% 0,2% -1,2% -2,5%
-0,7% 0,8% -0,6% -2,3%
Year 21-50 :
Average
Year 1-10 :
Year 11-20 :
Year 21-50 :
Year 1-10 :
Year 11-20 :
Average

27. III. Own ‘valuation-evolution’ research
III.4 Fair-value evolution of REIT’s
• 4 ‘Office-REIT’s’ in Belgium (Befimmo,
Cofinimmo, IOW and Leasinvest)
• REIT’s must ‘revaluate’ their real-
estate every quarter
– We have calculated this yearly
‘evolution’ in % of the real-estate-
value
– See evaluation/REIT in annex 3.
• From 2004 on, we have ‘segmented’
figures of these REIT’s, so we can
differentiate this % change pro region.

28. III. Own ‘valuation-evolution’ research
III.4 Fair-value evolution of REIT’s
• Limited history due to limited lifetime of
Office-REITS from 1996 to 2022.
• Remarkable similarities/differences
– What strikes you ?
1995 - 2022
Depreciation
of assets 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Average/
year
Standard-
deviation
Cofinimmo -0,7% -0,6% 0,1% 2,1% 0,9% -2,0% -2,1% -0,9% -0,3% 0,4% -0,8% -0,2% -0,3% 0,3% 0,3% -0,2% 1,9% -0,3% 1,3% 0,0% -0,1% 1,1%
Befimmo 0,0% -1,4% -7,3% -0,4% 2,0% 3,9% -0,2% -0,7% -0,8% 0,1% 1,7% 2,1% -0,3% -4,0% -1,9% -1,0% -1,8% -0,5% 0,4% 0,5% 0,8% 0,5% -0,2% 1,4% 0,0% -5,2% -0,5% -0,2% 1,4%
Intervest 2,3% -2,2% -6,0% -1,6% 0,4% -2,4% 0,9% -0,9% -0,8% 0,4% -1,1% 0,8% 2,5% 1,5% -2,0% -0,4% -0,4% 2,2%
Leasinvest 1,5% 0,3% 0,2% -1,0% -1,1% 0,8% 2,0% 3,7% 2,4% -3,3% -2,0% -1,3% 0,2% 0,3% 0,8% 1,1% -0,1% 2,5% 0,2% 0,4% 2,4% -0,5% 0,0% 0,4% 1,8%
Inflation 2,1% 1,6% 1,0% 1,1% 2,5% 2,5% 1,6% 1,6% 2,1% 2,8% 1,8% 1,8% 4,5% -0,1% 2,2% 3,5% 2,8% 1,1% 0,3% -0,1% 2,0% 2,1% 2,3% 0,8% 0,4% 8,7% 1,9% 1,8% 1,2%
Bel20-index 32,4% 27,9% 35,7% -5,1% -3,6% -30,6% 0,8% 3,6% 31,1% 14,5% 26,9% 1,2% -54,0% 26,3% 10,6% -23,2% 17,7% 17,8% 13,0% 12,2% -0,9% 10,3% -18,5% 22,0% -8,5% -10,0% 3,6% 5,7% 21,1%

29. III. Own ‘valuation-evolution’ research
III.4 Fair-value evolution of REIT’s
• CBD had an average increase in value of
0,5 %
– Not different to ‘our’ calculated average of 0,2 %
• Decentral offices decrease with 3 %/year
in value
– Higher than our calculations
• Peripheral offices have decreased with 4 %
pro year on average from 2005 – 2020 !
– Higher the average calculated (from 3,7 % to 1,6
%)
– Partially explainable since most offices are less
then 10 to 20 years old
• Correlations ‘as expected’
– CBD en decentralized
– Decentralized en periferie
– ?? CBD en other cities
Value-evolutions
Offices/year Average
Standard-
deviation
Brussels,
CBD
Brussels,
decentraliz
ed
Brussels,
peripherie
Other
cities
Brussels, CBD 0,5% 1,8% 100,0%
Brussels, decentralized -2,9% 2,9% 47,3% 100,0%
Brussels, peripherie -4,0% 2,8% -7,0% 48,9% 100,0%
Other cities 0,2% 1,9% 74,4% 25,5% -17,2% 100,0%
-10,0%
-8,0%
-6,0%
-4,0%
-2,0%
0,0%
2,0%
4,0%
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Yearly value-evolution Belgian Offices
Brussels, CBD Brussels, decentralized Brussels, peripherie
Other cities Gemiddelde

30. III. Own ‘valuation-evolution’ research
III.5 Summary of ‘value evolutions’
• Net return on
‘properties’ more
comparaible then
we thinck
• 3 % seems to be a
market-expectation
for ‘investors in
prime offices’
Total returns on real estate are more moderate(d)
than we think.
Prime Decentral Periphery
Potential Gross Income P.G.I. 4,00% 6,00% 8,50%
- vacancy allowance -0,08% -0,48% -1,36%
+ other income
- operating expenses -1,20% -1,20% -1,20%
Net operating Income N.O.I. 2,72% 4,32% 5,94%
- Capital Improvement expenditures
+/- value evolution of property
0,30% -1,20% -2,60%
==> Total return of property 3,02% 3,12% 3,34%
Different office-locations
Total return of a property

31. IV. In search of optimization of real estate return
IV.1 recap ‘return’ of property
1. Income/yield 
‘Main/only focus of
investors’
2. Value-evolution of
property:
1. Can we evaluate that
better ?
3. Vacancy: can we
influence this ?
4. Operating expense:
can we evaluate this ?
Prime Decentral Periphery
Potential Gross Income P.G.I. 4,00% 6,00% 8,50%
no capital Improvement expenditures
+/- net value evolution of property
0,30% -1,20% -2,60%
==> local return of property 4,30% 4,80% 5,90%
- vacancy allowance -0,08% -0,48% -1,36%
==> net local return of property 4,22% 4,32% 4,54%
- operating expenses -1,20% -1,20% -1,20%
==> Total return of property 3,02% 3,12% 3,34%
Re-structuring of return of property Different office-locations

32. IV. In search of optimization of real estate return
IV.2 More income/yield : the market
• Income/yield 
• Four Quadrant Model by
DiPasquale and Wheaton
(1996)
• The different markets
(space, asset,
construction) will ensure
a long-term market
equilibrium – which will
equilibrate in the long
run the different market
segments.

33. IV. In search of optimization of real estate return
IV.2 More income/yield : the market
The change in growth of the European population from 1950 – 2020
of 1,5-2 % pro year could change fundamentally the demand for real
estate the following decades.

34. IV. In search of optimization of real estate return
IV.2 More income/yield : the market
The figures difer strongly between scenario’s and sources, but the
main tendency is obvious …

35. IV. In search of optimization of real estate return
IV.3 Valuation of our buildings
• Valuation of buildings
• A diversity of valuers in
Belgium  are the
valuations consequent ?
• > 30 valuers advised by
bank to value the
Officenter-buildings
• Only 11 advised by > 1
bank
– 2 types:
• Affiliated with brokers (6)
• Independent valuers ( 5)
Number of banks Belfius KBC BNP ING
Totaal aantal : 32 14 10 14 14
Jones Lang LaSalle BV 4 1 1 1 1
Stadim CVBA 4 1 1 1 1
Troostwijk-Roux C V B 4 1 1 1 1
Bel Square - Valuation ==> Colliers 3 1 1 1
Cushman & Wakefield 3 1 1 1
Galtier-Expertises NV 3 1 1 1
ADM Group BV 2 1 1
CBRE 2 1 1
Ceusters NV 2 1 1
De Crombrugghe & partners 2 1 1
Knight Frank 2 1 1
AGECI 1 1
Amicus Curiae 1 1
Atelier d'Architecture 1 1
Bjorn Cornelis 1 1
BNP Paribas RE Property Value 1 1
Expertisebureau Topoplan 1 1
Filip Blaton 1 1
Frank Somers 1 1
Geotec 1 1
Gudrun 1 1
Immoquest Valuations 1 1
Jef Haeverans 1 1
Lilex 1 1
Losdyck Bexi Real Estate Consultancy 1 1
M et 3i SRL 1 1
Michiels Guy 1 1
PWC 1 1
Quentin & Vincent 1 1
Sabbe 1 1
Savills 1 1
Yvan Geens 1 1

36. IV. In search of optimization of real estate return
IV.3 Valuation of Officenter buildings
• Differences ‘brokers’ vs. ‘pure valuation’-companies in line with expectations
– Brokers are in general more expensive than ‘pure’ valuers (+ 25 %, but different possibilities).
• Offers (3 – 35 pp.) 50 % more pages, report also longer (average 36 pp.)
– Small, but not relevant difference in valuation
• + 5 % for valuers, + 15% for brokers
• Diversity in ‘methods’
– Limited use of DCF and building-cost
– Rental yield and comparable nearly always used
• Diversity in valuation-results
– Investment value vs. market value (12% difference)
– Forced sale value in 50 % of cases : 70-80% of investment-value (1 x 65%)
– Land value only in 50 % of cases

37. IV. In search of optimization of real estate return
IV.3 Valuation of Officenter buildings
• Value – evolution in 75 %
of cases < 10 %
– Is smaller than the
difference between
‘market-value’ and
‘investment-value’
• Exceptional increases due
to explainable market
changes
– Mostly ‘over more years’
– But, only ‘visual’ when
changing from valuer.

38. IV. In search of optimization of real estate return
IV.3 Valuation of Officenter buildings
• Main ‘determinant’ :
Yield,
– 7,5 % average – in line with
market expctations
– Standard deviation 11 %,
limited
• Average value 1,572
€/m², standard deviation
17 %
• Rental value 116 €/m²,
with a 12 % standard
deviation
Waardering vastgoed Officenter Gebouw- B.A. Huur-
n/parking 2023 m² waarde Yield waarde Waarde Huur
Leuven 3.986 8.170.000 6,6% 540.200 2.050 136
Turnhout 2.600 4.442.000 7,0% 310.919 1.708 120
Zaventem 4.380 7.295.000 5,8% 421.000 1.666 96
A12 1.854 2.945.000 7,7% 228.190 1.588 123
Aalst 3.803 6.680.000 7,9% 525.600 1.757 138
Maastricht 3.800 6.160.000 7,3% 450.000 1.621 118
Hasselt 5.714 7.006.000 8,5% 598.580 1.226 105
Geel 3.200 4.968.553 8,0% 395.000 1.553 123
Vilvoorde 3.744 4.325.000 8,9% 384.960 1.155 103
Beringen 1.220 2.000.000 7,9% 157.915 1.640 129
Genk 1.360 2.297.000 7,9% 182.479 1.689 134
Pelt 1.394 2.500.000 6,7% 168.300 1.794 121
Sint Truiden 1.204 1.427.000 7,1% 102.000 1.185 85
TOTAAL 38.258 60.215.553 7,4% 4.465.143 1.574 1.531
Gemiddeld 2.856 4.337.129 7,6% 327.079 1.592 116
St. afwijking 1.478 2.099.780 0,8% 159.674 270 14
% st.afwijking 52% 48% 11% 49% 17% 12%
per m²

39. IV. In search of optimization of real estate return
IV.3 Valuation of Officenter buildings
• Interview with each valuer discussing
the valuation
– Methods used:
• Main reference in our ‘specific’ case :
capitalization method
– Market rents are available
– Market yields can be estimated through experience
• Sanity-checks : sales price/m²
• 2 valuers have used a discounted cash flow
method – the most expensive offers
– In 50 % of cases demand for monthly
revenues and used
– Value evolution of building
• Have no crystal boll
• Do not ‘want’ to look at that –
– Cfr. Limited increases in rental values and prices
– Analysis of sales prices/m² in Brussels

40. IV. In search of optimization of real estate return
IV.3 Occupancy-rate ?
• Is a cost of 5 tot 20 % of the
rent/value evolution
• !! : buying your ‘own’ building
avoids this net cost !!
•  is the main reason why
buying your own house is always
a good ‘financial’ investment
– But, it limits strongly your flexibility
– Given the fast-evolving world, this
disadvantage becomes more
important
Prime Decentral Periphery
Potential Gross Income P.G.I. 4,00% 6,00% 8,50%
no capital Improvement expenditures
+/- net value evolution of property
0,30% -1,20% -2,60%
==> local return of property 4,30% 4,80% 5,90%
- vacancy allowance -0,08% -0,48% -1,36%
==> net local return of property 4,22% 4,32% 4,54%
- operating expenses -1,20% -1,20% -1,20%
==> Total return of property 3,02% 3,12% 3,34%
Re-structuring of return of property Different office-locations

41. IV. In search of optimization of real estate return
IV.4 Operating expenses
• We are searching for 1 – 2 %
additional return on real estate
– Which is not easy to find.
• But we have 2 – 3 x a
management fee on these
assets which costs more than
1-2 % extra return:
– More important: avoiding
intermediation costs !
Voorbeeld
Operational real estate return 7,00% Regus
Brut real estate return 5,50%
Cofinimmo/
Intervest
Real estate investor return 4,00%
AG Insurance/
Belfius
Net real estate return for
investor
2,50% Jan met de pet
1-2 % Management-fee operator of real
estate
1 - 2 % fee of asset manager of real
estate
1 - 2 %Fee of financial advisor of investor
(bank/family office/…)

42. IV. In search of optimization of real estate return
IV.4 Operating expenses
• A return of 4 % vs. 2,5 % gives
after 30 years more than
double the return !
– Only 1/3th of loss/year but > 50
% loss on 30 year !
• This increase grows
exponentially
– ?? How many managers are you
paying with you invested funds ?

43. V. Pre-liminary conclusions
• Real estate is not researched enough, although it is our biggest asset
– It is complex to research quantitatively : we like to work with ‘correct’ figures
– We are more ‘landlords’ than ‘real estate investors’ …
• The market is working better than we think
– Although it is so difficult to comprehend/explain him
– The great number of investors guarantee a very good long term market pricing
– In the short term, high implicit and explicit transaction prices make timing very important
• So, the main advises for a passive investor remain the same
– Invest for the long run, try not to time the market (long run = 20-30 years …)
– Invest in good management and good markets, not in good ‘return of past years’
– And, for real estate – good returns of the past could be a bad sign for future evolutions…
• Finally, it is clear that more academic research seems to be necessary – to avoid
that the Anglo-Saxon investors will replace our European landlords.

44. Epilogue
Toute ma jeunesse, j'ai voulu dire: je sais
Seulement, plus je cherchais, et puis moins j'savais
Il y a soixante coups qui ont sonné à l'horloge
Je suis encore à ma fenêtre, je regarde, et j'm'interroge
Maintenant je sais
je sais qu'on ne sait jamais
La vie, l'amour, l'argent, les amis et les roses
On ne sait jamais le bruit ni la couleur des choses
C'est tout c'que j'sais ! Mais ça, j'le SAIS... !
Jean Gabin, 1974.

45. Annex 1 : residential real estate
prices
• Can the interest rate decrease further ?
• Inverse correlation of ‘land value’ and ‘interest rate’ in Belgium
– No ‘land-value’ statistics since 2015 ?
• Lower interest rates will increase the importance of ‘residual value’ in valuations.

46. Annex 2 : Belgian Office REIT’s
Evolution 1992/2007 - 2022
• Average evolution/year negative – except for Leasinvest (> Luxemburg)
– Incl. positive effect of decreasing interest rates.
• Correlations between REIT’s positive and substantial
• Negative correlation between Bel20 and inflation (Confirming the theory of Fama)
• Other correlations not obvious
1995 - 2022
Depreciation
of assets
Average/
year
Standard-
deviation
Cofin-
immo Befimmo
Inter-
vest
Leas-
invest Inflatie Bel 20
Cofinimmo -0,1% 1,1% 100,0% 36,3% 59,2% 38,9% 18,3% 28,6%
Befimmo -0,2% 1,4% 36,3% 100,0% 73,1% 60,1% -22,2% -29,0%
Intervest -0,4% 2,2% 59,2% 81,4% 100,0% 54,2% -14,9% -9,8%
Leasinvest 0,4% 1,8% 38,9% 60,1% 54,2% 100,0% -1,6% -23,6%
Inflation 1,8% 1,2% 18,3% -22,2% -14,9% -1,7% 100,0% -44,9%
Bel20-index 5,7% 21,1% 28,6% -29,0% -9,8% -23,6% -44,9% 100,0%
Correlations

47. V. Learn it from WB/CM