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© REF! REF! – REF! REF! 1/4
REF! REF!
bulwiengesa
The 5% Study
WHERE IT STILL
PAYS OFF TO INVEST
2016
bulwiengesa
© REF! REF! – REF!
WHERE IT STILL PAYS OFF TO INVEST
page
FOREWORDS 1
CONTENT AND METHODOLOGY 2
MACROECONOMIC CONDITIONS 4
SUMMARY 6
THE 6-PERCENTERS 8
THE 5-PERCENTERS 14
THE 4-PERCENTERS 18
THE 3-PERCENTERS 28
THE RESULTS IN DETAIL 34
DEFINITIONS AND COMMENTS 40
CONTACTS 44
Contents
© bulwiengesa AG 2016
THE 5 % STUDY 2016
bulwiengesaTHE 5 % STUDY 2016
2016
The 5 % StudyWHERE IT STILL PAYS OFF TO INVEST
A study by bulwiengesa AGon behalf of
WHERE IT STILL PAYS OFF TO INVEST
© bulwiengesa AG 2016
bulwiengesa
© bulwiengesa AG 2016 page 1/44
THE 5 % STUDY 2016
WHERE IT STILL PAYS OFF TO INVEST
The publication of the first 5 % study last year met with a bigresponse on the market in light of its new approach to real es-tate market research. For the first time, markets are not (just) clustered by region anduse. Instead, the focus is on their income opportunities. An-other innovative aspect is that it includes not just a static yieldassessment, but an analysis of the internal rate of return (IRR)on the investment assumed. The study also raises questions that have already been dis-cussed a great deal but have not yet been answered defini-tively, and certainly not consistently: What are core properties?And what are non-core properties?
The meanings of these terms vary considerably, particularly inmarket phases characterised by high excess demand. Thestudy provides an analytical approach in which core propertiesare examined particularly with regard to securing ongoing in-come, and which therefore focuses on the liquidity of the indi-vidual asset classes. The responses from readers last year reaffirmed our approachof continuing in this new direction and releasing a new issue ofthe study with updated figures.
Sven Carstensen, Frankfurt am Main Branch Manager,bulwiengesa AG
Demand on the German property market is currently almost un-limited. Persistently low interest rates and the stable economicsituation are also attracting international investors to Germany.This is leading to rising prices and falling yields in the estab-lished real estate asset classes of residential, retail and officeproperty. As a result, there is a growing need to seek out in-vestments that offer more interesting income opportunities. As a lessor, portfolio holder and project developer, Aurelis hasa clear focus on production-related properties and Unterneh-mensimmobilien. For a long time, these were regarded as spe-cific, unsuitable for alternative uses and therefore not fit for thecapital market. But there is gradually growing recognition thatsignificant differences exist within this category. International in-vestors in particular recognise the strength of the Germanmanufacturing industry and are willing to invest in this area.Furthermore, the higher cash flow returns in this segment do
not necessarily go hand in hand with higher risks. Instead,these assets can be seen to hold their value in the case of de-monstrable management success and may therefore be suit-able for investment.However, availability of market data is a key factor for the suc-cess of each asset class. The 5 % study provides an objectivebasis for examining the yield opportunities on the property mar-ket – and possibly also alternative investment strategies. Weregularly support initiatives that aim to increase the transpar-ency of the real estate investment market. This gives investorsa well-founded overview of where it still pays off to invest today.
Dr Joachim Wieland, CEO Aurelis Real Estate GmbH & Co. KG
Compared with the rest of Europe, Germany is still seen as anattractive location for real estate investments in 2016. In boththe commercial and the residential property segment, A and Bcities are continuing to record significant price increases andlucrative yields – partly because the anticipated turnaround ininterest rates has not yet materialised. The key issues for theproperty market in 2016 are the influx of refugees and (as be-fore) urbanisation/rural exodus. Both of these issues areprompting growing calls for state subsidies for affordable hous-ing in urban areas and a reduction in the high legal standardsin residential construction, which contribute to the price in-creases. The German real estate market is currently characterised byhigh liquidity and a lack of attractive investment opportunities.At the same time, Germany has a developed and stable marketin a strong national economy – which means that the German
market and its yields are also of interest to foreign investors inparticular.This positive trend may well continue in the coming years, par-ticularly due to the as yet unforeseeable consequences of theBrexit vote: assuming just a moderate loss of employment inLondon, this could provide a strong boost to the real estate en-vironment in the Frankfurt/Rhine-Main region in particular.With its many years of experience, BEITEN BURKHARDT pro-vides advice on all phases of property management: from fi-nancing to the land purchase and project development throughto letting or selling the property. We implement innovative formsof property sales and trading, as well as designing German andforeign real estate funds.
Dr Detlef Koch,BEITEN BURKHARDT Rechtsanwaltsgesellschaft mbH
Forewords
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THE 5 % STUDY 2016
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Content and Methodology
ContentUsing dynamic performance measurement, the 5 % study pro-vides a new approach for describing property markets. Theyield prospects of various asset classes are presented on thebasis of an analysis of the internal rate of return on an invest-ment. In light of the recognition that a single data point can re-flect the complexity of a market only to a very limited extent,this study also highlights the range of investment profitability.
Descriptions of property markets in market reports are usuallybased on top properties that generate prime rents and are ac-cordingly traded at prime yields. However, this does not takeaccount of the high diversification of the investor landscape,where extremely security-focussed investors increasingly findthemselves alongside players seeking to identify and take ad-vantage of market opportunities. This study also offers theseplayers an overview of the market.
The subject matter analysed in this 5 % study is the perform-ance expectations in the asset classes that currently dominatethe German investment market. These include:– office– residential– shopping centres– specialist retail parks– hotels– modern logistics
as well as the new property types– micro-apartments and "Unternehmensimmobilien"
Basic conceptThe study uses a dynamic model to determine the probable in-ternal rate of return (IRR) on an investment, assuming a hold-ing period of ten years. It is assumed that the investment takesplace at typical parameters for the market in question. A cashflow approach was applied, describing the anticipated futurecash flows (purchase, rental income, property and operatingcosts, sale). The internal rate of return of these payment flowsrepresents the IRR.
No financing effectsIn addition to the success of the properties themselves, suc-cessful real estate investments are also dependent on financ-ing strategies (e.g. taking advantage of interest leveragethrough increased borrowing). There is typically a very widerange of variants on the market in this respect. To allow forclear statements regarding the property performance, these ef-fects and investor-specific adjustments were not included in themodel.
No project developmentsThis model assumes that the investment is made in buildingsthat do not require renovation or restructuring. Project develop-ments as part of asset management strategies are thereforenot included in the analysis.
ProcedureBased on the assumption that the success of the investmentmay be influenced by various different determinants such asmanagement performance and market fluctuations, a simula-tion (Monte Carlo, see glossary) of possible results was per-formed on the basis of changing parameters. To this end, therelevant characteristics affecting the success of the investmentwere assigned fluctuation ranges that were derived in advancebased on consideration and analysis of the respective market.Using Monte Carlo simulation, the probability of occurrence ofthe individual results was also calculated on the basis of 1,000draws.
Monte Carlo simulationMonte Carlo simulation is a stochastic model for the projectionof a forecast value. Put simply, this statistical method is sort ofa limited random number generator that operates within frame-work conditions and values defined by the user. To map theseparameters realistically and in line with market conditions as faras possible, a base value can also be defined in addition to avalue range. After the simulation has been performed, the userreceives a large number of results (depending on the numberof draws) taking account of the predefined conditions. Themodelling calculates probabilities of occurrence for the individ-ual results within this range. The value range itself has a prob-ability of occurrence of 100 %.For the performance of the simulation, base values and rangeswere defined – depending on the asset class under review – forthe following groups of variables: rent, vacancy rate, propertyand operating costs, fluctuation (space becoming vacant/re-let-ting). The internal rate of return on the investment resultingfrom the cash flow calculation was set as the forecast value.
Core versus non-coreCore and non-core have become established as terms for in-vestment strategies on the market, but there are no fixed defini-tions for them (at property level). Instead, there are a widerange of attempts at definitions, most of which are suggestedby the respective investors themselves.
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© bulwiengesa AG 2016
This study does not aim to add a further suggestion to thesedefinitions. The division into core and non-core investors istherefore made at a purely statistical level. In the study, the cor-ridor for core and non-core investors was delimited based onthe assumption that core investors assume less risk and acceptlower yields while non-core investors are less risk-averse buthave higher yield targets.Accordingly, the Monte Carlo results/IRRs between the 25 %quantile and the 75 % quantile (corresponding to a 50 % prob-ability) are defined as the range within which core investors op-erate. The rest of the range – starting from an attainable rate ofreturn of 6.49 % – is seen as being for non-core investors.Here, there is a probability of 25 % that internal rates of returnbeyond the core range will be achieved – but equally, non-coreinvestors may fall below the attainable rate of return for core in-vestors and in some cases may even generate negative IRRs.
Parameters and fluctuation rangesbulwiengesa's data system (RIWIS) was generally used as thesource for rental, vacancy and yield information. For Unterneh-mensimmobilien, information from the INITIATIVE UNTERNEHMENS-IMMOBILIEN was selected as the basis. The data for hotels andretail properties were also checked for plausibility using analy-ses of investment transactions and other secondary sources(e.g. data from HypZert).The cost data were calculated using primary analyses (wherepossible) and on the basis of typical market assumptions.The fluctuation ranges for costs and income were defined indi-vidually for each type of use and are based on typical marketparameters. Extreme values were excluded in this context.
The internal rate of return methodThe internal rate of return method shows the rate of return forwhich the net cash flows/the net present value is exactly zero.It thus represents the average rate of return on an investment.The internal rate of return method is not to be recommended asthe sole basis for an investment decision, since it has a numberof methodological shortcomings – the reinvestment assumptionis criticised, for example. However, calculating the internal rateof return offers the advantage that this represents the successof a certain investment period (in the case of this study, tenyears). This differentiates it from the static yield assessmentsthat are typical on the market. In addition, the internal rate ofreturn method is used by many investors and thus enjoys wide-spread acceptance.
Performance Measurement – Guidance for Readers
In view of the complex subject matter, guidance for readers isprovided below for better understanding of the results. Thisguidance relates to the right-hand column in the sections onthe 3-, 4-, 5- and 6-percenters.In general, all calculations in the study are based on propertysizes and parameters in line with the market.The Selected Model Assumptions table shows the key pa-rameters incorporated in the cash flow calculation and simula-tion.The results box in the right-hand column presents/summa-rises the results of the Monte Carlo simulation. In the diagram,the x-axis shows the projected IRRs based on the Monte Carlosimulation, while the y-axis shows the probability of occurrencefor each projected IRR. The dark blue bars represent the IRR range relevant to core in-vestors as defined by the study. This has a 50 % probability ofoccurrence and is delimited by the 25 % and 75 % quantiles. Inline with this, the dark blue field of the results box shows thecore range with values.The rest of the range – relevant to non-core investors accord-ing to the study's definition – is marked in medium blue. This isabove the core range in 25 % of cases, but may also be belowthis range. The maximum attainable IRR according to the simu-lation is specified in the medium blue field below the corerange. The internal rate of return on the investment (IRR), calculatedusing the base values in line with the cash flow method, corre-sponds to the forecast value of the simulation.
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THE 5 % STUDY 2016
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© bulwiengesa AG 2016
Sentiment remains positive
The German property market remains very lively and the gen-eral sentiment is therefore positive. However, Deutsche Hypo’sreal estate climate index – based on a survey panel of over1,000 experts – points to increasing reticence among playerson the property market. One reason for this could be the Brit-ons’ vote for Brexit and a resulting phase of uncertainty.
On the one hand, hopes of migration/relocations from Londonare growing in Frankfurt in particular, but on the other hand thepossible effects are still unclear and could be overshadowed byoutstanding consolidation in the banking industry.
Objectively speaking, the local factors of the interest rate devel-
opment, the unemployment rate and migration have a greaterimpact on the property markets than possible Brexit effects.The current phase of uncertainty could therefore slightly en-courage investments in concrete gold.
Strong momentum on the investment market
German commercial properties are in high demand, with thetransaction volume for commercial real estate in Germanyposting another significant increase in 2015. At approximately56 billion euros (commercial properties only), it reachedroughly the level of 2006. Only 2007, when a transaction vol-ume of over 67 billion euros was recorded, is still regarded asan exceptional year.The market is still driven by foreign investors, who are increas-ingly extending their focus to smaller markets are less estab-lished assets classes, too. Around 50 % of the transactions in2015 were attributable to this category of investors.Office properties were the most popular asset class again lastyear. They accounted for around 46 % of the commercial in-vestment market, while the share of retail properties was 33 %.Residential properties are not included in these statistics, butnonetheless should not be left unmentioned. Around 22 billioneuros was invested in the residential segment in the profes-sional real estate market – meaning that the total transactionvolume (commercial and residential) increased to 78 billioneuros. The development over the course of 2016 shows thatthe investment market is still lively – although it is doubtfulwhether the high figures from 2015 will be matched.
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THE 5 % STUDY 2016
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Macroeconomic Conditions
Development Deutsche Hypo Property Index by Sectors
Source: Deutsche Hypo/bulwiengesa AG
2008 2009 2010 2011 2012 2013 2014 2015 20160
50
100
150
200
250
officeretail
residentialind./logistics
New Property Investments of Institutional Investors in Commercial Property in Germany
Source: BVI, BaFin, Bundesverband Deutscher Leasing-Gesellschaften, Bankhaus Ellwanger & Geiger, Deutsche Bundesbank, analyses by Loip-finger, Scope, FERI, data is based on research and calculations by bulwiengesa AG
92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 160
15
30
45
60
75
in b
n eu
ro
property-leasing/leasing fundclosed property fundopen-end mutual fund
property special fundinsurances/pension fundslisted property companies
foreign investorsotherforecast
bulwiengesa
© bulwiengesa AG 2016
High liquidity as a driving factor on the investment market
The abundance of liquidity as described in the previous study iscontinuing to boost the equity and real estate markets. Despitecontinued positive economic fundamentals, the increase in themoney supply and economic growth are drifting further apart.
As in the previous year, two risk scenarios are theoreticallypossible as a result: inflation and a bubble.
Despite the high money supply, the risk of inflation can cur-rently be described as manageable. Consumer prices recentlyincreased compared to the previous month, mainly due to ris-ing energy prices, but this may just be a temporary effect (cf.Bundesbank monthly report for July 2016). Expectations for theyear as whole indicate only extremely low inflation rates of0.2 % to 0.4 %. There are also no signs of a bubble forming on the market as awhole at present. However, risks of regional and sectoral over-heating on the property market can be seen in a few cases –particularly in markets where rent and price increases cannotbe explained by the socio-economic variables.
Interest rates still in downward spiral
The downward spiral in interest rates has continued since theprevious study.The ECB’s key interest rate has now fallen to 0 % – for the firsttime in European history. German government bonds are evenheading into negative territory. Following a rule of thumb ac-cording to which the difference between the risk-free interestrate (i.e. that of the 10-year German government bond) and theattainable yield represents the risk premium, this is currently atan all-time high.In the Frankfurt office market, for example, it now amounts to440 basis points, whereas in the crisis year 2009 it was only203.From this perspective, there would thus seem to be scope for afurther increase in property prices.
Performance of German properties
The German Property Index (GPI) reflects the performance ofindividual property segments. Overall it shows the total return,consisting of the capital growth return and the cash flow return.
Office properties generated the highest returns in 2015, ataround 16 %. However, the other property classes also provedvery dynamic with returns of around 15 % (residential), 13 %(logistics) and roughly 11 % (retail).The driving factor is still the capital growth returns, which havebeen significantly positive since back in 2010.Positive returns are expected in the future, too, although themomentum in capital growth returns – particularly in the officeand retail sector – is likely to decrease.
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THE 5 % STUDY 2016
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Development GDP and Money Supply M3 in the Eurozone
Source: Eurostat, Deutsche Bundesbank
989900010203040506070809101112131415100125150175200225250275
GDP at market prices Money Supply M3/EZ
Overview Risk Premium of Office Property
Source: Bundesbank, EZB, bulwiengesa AG
00 02 04 06 08 10 12 14 Q1/160 %1 %2 %3 %4 %5 %6 %
Ger Gov. Bond ECB-prime rate
net initial yield FFM
Forecast Total Return in Germany
Source: bulwiengesa AG, 2016 - 2020 forecast
09 11 13 15 17 190 %
5 %
10 %
15 %
20 %
logisticsresidential
officeretail
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Summary
Core-Matrix*
For the purposes of this study, core properties are defined asproperties with a stable letting situation and sustainable loca-tion parameters. The matrix above shows the relationship be-tween the probable internal rate of return on a property invest-ment and the liquidity of the respective market. Here, market li-quidity refers to the ability to generate investment demand in-dependently of economic cycles and to offer exit opportunitieseven in years of low demand. The yield potential for core properties has decreased year-on-year in all asset classes, with a particularly marked decline foroffice properties in B markets. The low level of supply on the Amarkets is prompting institutional investors in particular to shiftto B markets, and this trend increased significantly again duringthe period under review. The consequences are an increasinglyscarce supply and relevant price increases in these markets,too. The base value for the attainable IRR in the secure corerange has therefore declined by 9.8 %. The attainable range forcore investors is currently between 2.5 % and 5.2 %. As a re-sult, investment pressure is also spilling over into the C mar-kets, where the performance of office properties has decreasedby 7.4 %. The base value for the attainable IRR for residential propertiesin A markets is below the 3 % mark. It is becoming increasinglydifficult to generate profits here. On the other hand, the attain-able cash flows are considered very secure.
One use category that still offers high yields is office propertiesin small markets. However, investments here are only recom-mended in small area sizes and in line with the market. Shopping centres offer considerably larger-volume investmentopportunities. With a yield range for core investors of between3.0 % and 3.7 %, the expected performance is increasingly lim-ited. The IRR potential of logistics properties has also de-creased again by around 6.1 % year-on-year in terms of thebase value. The secured yield range for Unternehmensimmo-bilien (UI) is between 4.7 % and 7.3 %. As this new assetclass – represented in the study with three types of Unterneh-mensimmobilien: production properties, business parks andwarehouse properties – becomes more established, this proc-ess is also reflected in falling yields. Overall, the probability of reaching the 5 % mark with securedinvestments in the conventional asset classes is becoming eversmaller. Such yields can usually be achieved only in smallermarkets or in management-intensive property classes. In thesecases, however, there is generally the problem of liquidity indeclining investment markets.
mar
ket l
iqui
dity
high
med
ium
low
5 %
mar
k
property-specific IRR
1 % 2 % 3 % 4 % 5 % 6 % 7 % 8 % 9 % 10 %
office A residential A -4.0 %shopping centres -3.8 %
modern logistics -6.1 %retail parks -7.0 %
micro-apartments A
UI light manufacturing -4.2 %
UI business park -6.2 %
office D -3.2 %
UI warehouses -5.7 %office C -7.4 %
office B -9.8 %residential B -5.3 %
hotels -7.3 %micro-apartments B -5.4 %
residential UC -2.9 %micro-apartments UC -7.2 %
* Within the categories of low, medium and high market liquidityshown in the diagram, there is no further assessment of the liquid-ity of the individual types of use.
Y-O-Y Change IRR base value
-6.3 %
-5.4 %
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Summary
Non-Core-Matrix** Within the categories of low, medium and high market liquidityshown in the diagram, there is no further assessment of the liquid-ity of the individual types of use.
Properties with an increased risk profile – and thus also higherperformance opportunities – are defined as non-core propertiesin this study. They are characterised by vacancies and are usu-ally situated outside the central locations. The matrix above only shows their market potential; extensiverestructuring or renovations are not taken into account in thisstudy. No outliers are included in the analysis either, meaningthat in some individual cases the attainable yields (and also theeconomic risks) may be considerably higher than those deter-mined in the model calculation.Residential property investments in established markets do notcurrently offer high enough yield potential for non-core inves-tors. Similarly, modern shopping centres and specialist retailcentres (without any need for restructuring/modernisation) alsoare not included in the non-core analysis. In the office markets of the A cities, non-core properties aregenerally to be found in peripheral locations. If investors suc-ceed in purchasing properties with management deficiencies(e.g. vacant space) and stabilising the rental structure, maxi-mum yields of up to 9.1 % can be generated. However, this iscountered by significantly higher economic risks. Non-core in-vestors can expect a rate of return of up to 12.5 % from smallerD office markets. However, the small size of these marketsconsiderably limits the investment volumes. As well as the typi-cal cash flow risks, there are also high liquidity risks. Good lo-
cal market knowledge is therefore a basic prerequisite for oper-ating successfully in these markets. The non-core segment for modern logistics properties is to befound primarily in regions outside the major hubs. The yield po-tential here comes to a maximum of 7.8 %. Non-core hotel investments usually relate to the purchase ofshort-term lease contracts with corresponding re-letting risks.The potential here comes to a maximum of 7.0 %. Unternehmensimmobilien (UI) continue to offer increased per-formance opportunities, amounting to up to 10.5 % for businessparks, up to 10.4 % for production properties and up to 9.3 %for warehouse space. Because this asset class is generallydominated by very regional demand, a high degree of network-ing of asset management is a key criterion for the long-termsuccess of the investment, in addition to technical expertise.Demand on the investment market is also limited after adjust-ment for economic cycles. Access to specialised sales chan-nels is therefore also important.
5 %
mar
k
4 % 5 % 6 % 7 % 8 % 9 % 10 % 11 % 12 % 13 %
high
med
ium
low
mar
ket l
iqui
dity
office Amodern logistics
office B
hotelsUI business park
UI light manufacturingUI warehouses
office C
office D
property-specific IRR
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43
5
The 6-Percenters
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As the asset class of Unternehmensimmobilien becomes in-creasingly established, this process is also reflected in thetransaction volume for production properties. In 2015, invest-ment activities thus reached a new high of approximately 450million euros. However, the ratio of the transaction volume tothe total monetary volume of production properties, which is es-timated at around 299 billion euros, clearly shows that the in-vestment potential of this asset class is far from exhausted.
The current transaction market is characterised by growing de-mand pressure combined with limited supply. Demand for thisasset group currently still comes primarily from specialisedGerman investors.The 2016 performance analysis for production propertiesshows a decrease in the attainable IRR (base value) of 0.26percentage points. The range for the internal rate of return iscurrently between 5.4 % and 7.3 % (secured range).Production properties are characterised by particular manage-ment requirements (especially in the technical field) and aretherefore to be recommended as core properties only if corre-sponding expertise is involved. Despite growing interest from investors, it is assumed that pro-duction properties may potentially lose fungibility in less pros-perous market phases. Unlike established asset classes, pro-duction properties are generally very user-specific, which re-sults in a special risk profile, particularly with regard to their ca-pacity for alternative uses. This results in yield opportunities ofup to 10.4 % at present for non-core investors.
The Market for Light Manufacturing Properties (UI)The 5.50 to 6.49-Percenters – Property-Specific IRR
Investment Volume UI Light Manufacturing
Source: INITIATIVE UNTERNEHMENSIMMOBILIEN, Market Report No. 1 to 4
H12013
H22013
H12014
H22014
H12015
H22015
050
100150200250300
in m
eur
o
IRR Range UI Light Manufacturing
Results Range
IRR base value 6.00 % Maximum2.7$%
performance expectation
5.4 - 7.3 %
Who should invest?
core-investors
5.7 - 7.5 % previous year
up to 10.4 %up to 11.2 %
non-core-investors
previous year
2.8$%
0.0$%
3.2$%3.3%
3.5%
3.6%3.8%3.9$%
Conclusion
Production properties have a particular risk profile andare consequently especially suitable for specialists.However, there are growing efforts to standardise thismarket.
Market Environmentinvestment demanddemand for space
regional up to nationalregional up to national
liquidityvolatility
lowmedium
4.1%
4.3%4.4%4.6%4.7%4.9%5.0%5.2$%
marketable size > 1 m euros (wide range) 5.4%5.5%
3 % 3.9 % 5.2 % 6.5 % 7.7 % 9.0 % 10.2 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
non-core
Selected Model Assumptionstypetypical property size
existing building10,000 sqm
net initial yieldvacancy acquisition datemarket rent acquisition dateavg. term of lease
6.2 %2,500 sqm (3 months)
4.10 euros/sqm5 years
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When analysing the office markets in D cities, the variation be-tween them must be taken into account. This means that gen-eral statements are possible to a limited extent only. Thesestructural differences are particularly clear in the analysis of therental markets. Whereas office rents in cities such as Ulm andFriedrichshafen average 10.00 euros/sqm RA-C or more, therent level in cities such as Görlitz and Halberstadt is below 5.00euros/sqm RA-C.
However, the demand pressure on the residential property mar-ket is increasingly spilling over to regional office markets, too.This is reflected in the decline in net initial yields, which havefallen from 7.2 % in 2015 to 6.8 % now. The average vacancyrate has also decreased by 30 basis points to 7.0 %. The officemarkets in Ulm, Marburg, Kassel and Pforzheim proved par-ticularly dynamic, with yields here decreasing by 2.1 % or moreyear-on-year.The performance expectations for office markets in D citieshave fallen by around 0.2 percentage points year-on-year to anIRR base value of 5.83 % in 2016. Core investors can expectan IRR of 4.3 % to 7.0 %. However, the limited investment op-portunities due to the small market sizes and the regional struc-ture of demand for space must be taken into account here. Se-curity-focussed investors should therefore concentrate on prop-erties with very good location and building characteristics (par-ticularly amounts of space in line with the market).Non-core investments are recommended only for those inves-tors with a high level of market expertise. Yields of up to 12.5 %are possible here.
Office Markets in D-CitiesThe 5.50 to 6.49-Percenters – Property-Specific IRR
Development Net Initial Yield D-Cities
2016 - 2020 forecast
06 08 10 12 14 16 18 206.0 %
6.5 %
7.0 %
7.5 %
8.0 %
IRR Range Office D-Cities
Results Range
IRR base value 5.83 % Maximum0.60$%
performance expectation
4.3 - 7.0 %
Who should invest?
core-investors
4.3 - 7.2 % previous year
up to 12.5 %up to 12.0 %
non-core-investors
previous year
0.80$%
1.00$%
1.30$%1.50$%
1.80$%
2.00$%2.30$%2.50$%
Conclusion
D cities have the highest yield prospects in the officesegment combined with very limited investment vol-umes.
Market Environmentinvestment demanddemand for space
regional up to nationalregional up to national
liquidityvolatility
lowlow
2.70$%
3.00$%3.20$%3.50$%3.70$%4.00$%4.20$%4.40$%
marketable size approx. 3 - 18 m euros 4.70$%4.90$%
0.6 % 2.5 % 4.4 % 6.4 % 8.3 % 10.3 %12.2 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
Selected Model Assumptionstypetypical property size
existing building3,900 sqm
net initial yieldmarket vacancymarket rent acquisition dateavg. term of lease
6.8 %7.0 %
7.20 euros/sqm3 years
non-core
core
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Dummyseite Logistikkarte
The Office Market in D-CitiesMaximal Obtainable Property-Specific IRR for Core-Investors
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Business parks belong to the asset class of Unternehmensim-mobilien and are characterised by mixed uses (particularly of-fice and service/warehousing). Another structural characteristicis high reversibility of the space. The attractiveness of this as-set segment is reflected in a growing transaction volume, whichtotalled around 700 million euros in 2015. However, the invest-ment market is held back by a limited supply of business parks.
As a result of falling yields, the performance for the productsegment of business parks has also declined significantly year-on-year. The IRR base value has thus fallen by 0.37 percent-age points to a current level of 5.63 %. Business parks aremanagement-intensive properties. Specialists can generate up-side potential here, particularly by purchasing properties withmanagement deficiencies that are reflected in a low rent levelor a relevant vacancy rate.For core investors, an investment in a business park is to berecommended only if specialist management expertise is in-volved. However, the yield prospects are also higher than forother asset classes at between 4.7 % and 6.6 %. The fungibilityof business parks is increasing as they become more acceptedas an investment product, but has not reached the level of es-tablished use segments.Specialised non-core investors can achieve values of up to10.5 %, particularly in properties in less prosperous regionswith higher income risks.
The Market for Business Parks (UI)The 5.50 to 6.49-Percenters – Property-Specific IRR
Investment Volume UI Business Park
Source: INITIATIVE UNTERNEHMENSIMMOBILIEN, Market Report No. 1 to 4
H12013
H22013
H12014
H22014
H12015
H22015
0
200
400
600
in m
eur
o
IRR Range UI Business Park
Results Range
IRR base value 5.63 % Maximum1.6 %
performance expectation
4.7 - 6.6 %
Who should invest?
core-investors
5.1 - 6.9 % previous year
up to 10.5 %up to 11.0 %
non-core-investors
previous year
1.80$%
2.00$%
2.10$%2.30$%
2.50$%
2.70$%2.90$%3.10$%
Conclusion
Business parks are becoming increasingly establishedon the investment market. Increased asset managementrequirements need to be taken into account.
Market Environmentinvestment demanddemand for space
regional up to internationallocal up to national
liquidityvolatility
mediummedium
3.20$%
3.40$%3.60$%3.80$%4.00$%4.20$%4.30$%4.50$%
marketable size approx. 2 - 70 m euros 4.70$%4.90$%
1.6 % 3.1 % 4.5 % 6.0 % 7.4 % 8.9 % 10.4 %
property-specific IRR
0 %1 %2 %3 %4 %5 %6 %7 %
prob
abilit
y
Selected Model Assumptionstypetypical property size
existing building12,000 sqm
office to warehouse ratio net initial yieldvacancy acquisition datemarket rent office
30 to 706.3 %
approx. 1,000 sqm8.10 euros/sqm
market rent warehouseavg. term of lease
4.00 euros/sqm2 years
core
non-core
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Warehouse properties represent another use segment in theUnternehmensimmobilien asset class. Around 245 millioneuros was invested in this type of property in 2015. This is thelowest transaction volume within the category of Unterneh-mensimmobilien. The estimated total value of approximately192 billion euros clearly shows that the investment potential inthis use segment is not yet exhausted. Owing to the simplespace and property structure, the investment market for ware-house properties is characterised by generally small-scale de-mand as compared to modern logistics properties. Access tothe regional and local economy is particularly important here.
In line with the other use segment of the Unternehmensimmo-bilien asset class, the performance expectation for warehouseproperties has declined. The current IRR base value is thus5.59 %, representing a year-on-year decrease of 0.34 percent-age points.Core investors with regional expertise achieve values of 4.9 %to 6.5 %. The professionalisation of management, as reflected in re-duced vacancies and rent adjustments, is the main factor driv-ing the profitability of warehouse properties.The yield expectations for non-core investors have also de-creased in comparison to the previous year. The yield corridorhere is up to 9.3 % for properties that are located outside themajor metropolises and are therefore characterised by very lo-cal demand.
The Market for Warehouse Properties (UI)The 5.50 to 6.49-Percenters – Property-Specific IRR
Investment Volume UI Warehouse
Source: INITIATIVE UNTERNEHMENSIMMOBILIEN, Market Report No. 1 to 4
H12013
H22013
H12014
H22014
H12015
H22015
0
50
100
150
200
in m
eur
o
IRR Range UI Warehouse
Results Range
IRR base value 5.59 % Maximum3.0 %
performance expectation
4.9 - 6.5 %
Who should invest?
core-investors
5.2 - 6.9 % previous year
up to 9.3 %up to 10.0 %
non-core-investors
previous year
3.10$%
3.30$%
3.40$%3.50$%
3.70$%
3.80$%3.90$%4.00$%
Conclusion
Warehouse properties are characterised by very re-gional demand for space. As a result, they are suitableonly for those investors with corresponding market ac-cess.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to national
liquidityvolatility
low up to mediummedium
4.20$%
4.30$%4.40$%4.60$%4.70$%4.80$%4.90$%5.10$%
marketable size approx. 1 - 10 m euro 5.20$%5.30$%
3.0 % 4.0 % 5.1 % 6.1 % 7.1 % 8.2 % 9.2 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
Selected Model Assumptionstypetypical property size
existing building10,000 sqm
net initial yieldvacancy acquisition datemarket rent acquisition dateavg. term of lease
6.1 %2,500 sqm (3 months)
3.80 euros/sqm3 years
core
non-core
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43
6
The 5-Percenters
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The cluster of C cities comprises 22 cities, meaning that thereis a wide range of structural differences. The office markets inC cities are generally in good shape. For example, the averagevacancy rate has fallen from 5.9 % in the previous year to5.7 %. While Rostock and Magdeburg saw a particularly dy-namic decrease in available space, Darmstadt and Saar-brücken posted slight increases in their vacancy rates. The av-erage rents rose from 8.60 euros/sqm RA-C in the previousyear to 8.70 euros/sqm RA-C now. Increases were recorded inall markets, with particularly strong growth in Bielefeld and Er-langen.
As a result of this positive market environment on the one handand the tense investment market on the other, initial net yieldsfell from 6.2 % to 5.7 %. The investor groups increasingly comefrom foreign countries.The significant decline in yields is also reflected in the perform-ance expectation. The IRR base value has thus fallen from5.13 % in the previous year to 4.75 % now. The attainable IRRrange for core investors is between 3.2 % and 6.0 %. Thesevalues are achieved particularly for property sizes in line withthe market in sustainable (generally central) locations. Non-core investors, particularly those who buy up vacant spaceand/or invest in non-central locations, can achieve an IRR of upto 10.6 %. It should be noted here that properties requiring re-structuring or modernisation were not included in the assess-ment. In general, regional marketing expertise is a prerequisite forsuccessful investment in C cities.
Office Markets in C-CitiesThe 4.50 to 5.49-Percenters – Property-Specific IRR
Development Net Initial Yield C-Cities
2016 - 2020 forecast
06 08 10 12 14 16 18 205 %
6 %
7 %
8 %
IRR Range Office C-Cities
Results Range
IRR base value 4.75 % Maximum.0.70$%
performance expectation
3.2 - 6.0 %
Who should invest?
core-investors
3.7 - 6.1 % previous year
up to 10.6 %up to 12.0 %
non-core-investors
previous year
.0.50$%
.0.20$%
0.00$%0.20$%
0.40$%
0.70$%0.90$%1.10$%
Conclusion
C cities are increasingly coming to the attention of inves-tors and the market here is currently in good shape. In-vestors should have regional market expertise.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to national
liquidityvolatility
lowlow
1.40$%
1.60$%1.80$%2.10$%2.30$%2.50$%2.80$%3.00$%
marketable size approx. 3 - 25 m euros 3.20$%3.40$%
-0.7 % 1.1 % 3.0 % 4.8 % 6.7 % 8.5 % 10.4 %
property-specific IRR
0 %1 %2 %3 %4 %5 %6 %7 %
prob
abilit
y
Selected Model Assumptionstypetypical property size
existing building6,100 sqm
net initial yieldmarket vacancymarket rent acquisition dateavg. term of lease
5.7 %5.7 %
8.70 euros/sqm3 years
non-core
core
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Modern logistics properties have become established as an as-set class on the investment market. The transaction volume forlogistics properties (including industry) came to around 4 billioneuros in both 2014 and 2015. Whereas just a few years agothe market was dominated by owner-occupiers and specialistsin particular, current demand comes from a wide range of na-tional and international investors. The German logistics property market can essentially be bro-ken down into 28 regions, with the main hotspots including theRhine-Main/Frankfurt, Hamburg, Hanover/Braunschweig andMunich regions. Investment demand remains at a very highlevel. Consequently, yields are displaying a downward trend.This development is also expected to continue in the mediumterm.
Investments in modern logistics properties generate a perform-ance of between 3.9 % and 5.2 %. There was a significant de-crease in the base value from 4.91 % in the previous year to4.61 %. The markets are still very diverse in this respect, withthe core range varying between 4.5 % in Munich and 5.9 % inMagdeburg.Due to the limited potential for rent increases, the rent at thetime of the acquisition is a decisive factor for a sustainable in-vestment. Increases in performance can be generated in par-ticular by purchasing (and rapidly reducing) vacant space. Non-core investors can thus achieve an IRR of up to 7.8 % for mod-ern logistics space. Logistics users have special requirementswith regard to both the structure of the property and the techni-cal management.
The Market for Modern Logistics PropertiesThe 4.50 to 5.49-Percenters – Property-Specific IRR
Development Gross Initial Yield
2016 - 2020 forecast
06 08 10 12 14 16 18 205.0 %
6.0 %
7.0 %
8.0 %
MunichFrankfurt
StuttgartHamburg
Cologne
Selected Model Assumptionstypetypical property size
existing building20,000 sqm
net initial yieldvacancy acquisition datemarket rent acquisition dateavg. term of lease
5.3 %5,000 sqm (3 months)
3.90 euros/sqm3 years
IRR Range Modern Logistics
Results Range
IRR base value 4.61 % Maximum2.3 %
performance expectation
3.9 - 5.2 %
Who should invest?
core-investors
4.2 - 5.5 % previous year
up to 7.8 %up to 7.7 %
non-core-investors
previous year
2.40$%
2.50$%
2.60$%2.70$%
2.80$%
2.90$%3.10$%3.20$%
Conclusion
Modern logistics properties represent an established as-set class and are well-suited for large-volume invest-ments.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to international
liquidityvolatility
highlow
3.30$%
3.40$%3.50$%3.60$%3.70$%3.90$%4.00$%4.10$%
marketable size > 10 m euros 4.20$%4.30$%
2.3 % 3.2 % 4.1 % 5.0 % 5.9 % 6.8 % 7.7 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
non-core
core
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Dummyseite Logistikkarte
The Market for LogisticsMaximal Obtainable Property-Specific IRR for Core-Investors
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5
3
6
The 4-Percenters
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Specialist stores and retail centres were regarded as an inex-pensive alternative to conventional investments, e.g. in shop-ping centres or office properties. There has been a substantialincrease in prices in the segment, particularly since 2013. Initialgross yields have thus fallen from 7.5 % in 2013 to 6.1 % now.Specialist stores display a very diverse tenant structure. Therental ranges largely depend on the provider groups. For exam-ple, up to 9.00 euros/sqm is paid for specialist toy stores, whilespecialist health and beauty stores usually command rents ofup to 20.00 euros/sqm. In-depth knowledge of the retail marketand the competition is therefore a prerequisite for a successfulinvestment in specialist retail centres. Anchor tenants play aparticularly important role here, since the conditions of theirrental agreements (amount of rent, term and incentives) have adecisive impact on the overall performance.
Core investors currently achieve an IRR value of between3.6 % and 4.5 %. The IRR base value has decreased by 0.23percentage points year-on-year to 4.41 %. Non-core investors can achieve up to 6.0 %. Higher yields arepossible in the case of restructuring measures, which do notform part of this model assessment. In general, it should be noted that retail concepts and the asso-ciated requirements for space are subject to regular change. Itis therefore always advisable to examine the marketability andsustainability of the existing space structures before purchasinga property.
The Market for Specialist Retail ParksThe 3.50 to 4.49-Percenters – Property-Specific IRR
Development Gross Initial Yield
06 07 08 09 10 11 12 13 14 Q15 Q2/16
5 %
6 %
7 %
8 %
9 %
IRR Rate Specialist Retail Parks
Results Range
IRR base value 4.41 % Maximum2.20$%
performance expectation
3.6 - 4.5 %
Who should invest?
core-investors
3.9 - 4.8 % previous year
max. up to 6.0 %max. up to 6.4 % previous year
2.30$%
2.40$%
2.40$%2.50$%
2.60$%
2.70$%2.80$%2.80$%
Conclusion
Despite falling yields, specialist retail centres still repre-sent a good investment alternative. Before making a pur-chase, structural and competition-related aspects shouldbe examined.
Market Environmentinvestment demanddemand for space
internationalinternational
liquidityvolatility
highmedium
2.90$%
3.00$%3.10$%3.10$%3.20$%3.30$%3.40$%3.50$%
marketable size approx. 5 - 30 m euros 3.50$%3.60$%
2.2 % 2.8 % 3.5 % 4.1 % 4.7 % 5.3 % 6.0 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
Selected Model Assumptionstypestate
existing buildinggood condition*
typical property sizenet initial yield base rent e. g. construction marketbase rent e. g. electronics store
approx. 25,000 sqm5.1 %
8.00 euros/sqm10.00 euros/sqm
base rent e. g. clothes storebase rent e. g. drugstore* no restructuring
12.00 euros/sqm 15.00 euros/sqm
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The cluster of B cities consists of 14 office markets. Thesehave established themselves alongside the traditional A mar-kets as lively user markets. The market environment is charac-terised by a high degree of stability. For example, the averagevacancy rate has decreased from 5.6 % in 2015 to 5.3 % now.The lowest vacancy rates are recorded in Duisburg, Münster,Bonn and Karlsruhe at a maximum of 3.5 %. Despite a de-crease in available space, Leipzig is still the only B market witha vacancy rate above the 10 % mark.
Average rents in the B cities increased from 9.70 to 9.80 euros/sqm RA-C. Mannheim, Bonn, Wiesbaden and Dortmund dis-play the highest rents in this category at over 10.00 euros/sqmRA-C. As investment opportunities in the major A markets be-come increasingly scarce, investment demand in B cities hasgrown substantially. In this context, yields for B markets havefallen from 5.6 % in 2015 to 5.2 % now. The highest prices areto be found in Bonn and Nuremberg, which each have a yieldlevel of well below 5.0 %. By contrast, the yield values in Bo-chum and Duisburg come to 5.8 % and 5.9 % respectively.The performance expectation for non-core investors is currentlyat an IRR of 2.5 % to 5.2 %. The base value has decreasedsignificantly by 0.44 percentage points. As such, the office mar-kets in B cities were among the asset classes with the greatestyield compression last year.Non-core investors can achieve up to 9.8 % in the B markets –particularly with properties that are outside the central locationsand have vacancies.
The Market for Office Properties in B-CitiesThe 3.50 to 4.49-Percenters – Property-Specific IRR
Development Net Initial Yield B-Cities
2016 - 2020 forecast
06 08 10 12 14 16 18 203 %
4 %
5 %
6 %
7 %
IRR Range Office B-Cities
Results Range
IRR base value 4.04 % Maximum.1.10$%
performance expectation
2.5 - 5.2 %
Who should invest?
core-investors
3.0 - 5.6 % previous year
up to 9.8 %up to 10.2 %
non-core-investors
previous year
.0.90$%
.0.70$%
.0.50$%.0.20$%
0.00$%
0.20$%0.40$%0.70$%
Conclusion
B cities represent attractive investment alternatives tothe A cities. However, the availability of assets in thecore segment is limited.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to national
liquidityvolatility
mediummedium
0.90$%
1.10$%1.30$%1.50$%1.80$%2.00$%2.20$%2.40$%
marketable size approx. 3 - 50 m euros 2.70$%2.90$%
-1.1 % 0.7 % 2.4 % 4.2 % 6.0 % 7.8 % 9.6 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
Selected Model Assumptionstypetypical property size
existing building9,300 sqm
net initial yieldmarket vacancymarket rent acquisition dateavg. term of lease
5.2 %5.3 %
9.80 euros/sqm3 years
core
non-core
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A total of 47 of the 127 markets are home to a university andhave accordingly been classified as university cities (except forA/B cities). Demand for housing has risen sharply in these cit-ies in recent years as a result of growing numbers of students.Other general effects (especially the influx of refugees) are ad-ditionally limiting the supply of housing.Investors therefore regard student cities as an attractive alter-native to the established major markets. The increased invest-ment demand resulted in a sharp rise in prices. Whereas in2012 the average multipliers of annual rent were still at around13.2, a value of 15.5 is now expected. At the level of the indi-vidual cities, they range from 10.3 in Frankfurt (Oder) to 20.7 inConstance.
The attainable IRR range for core investors is currently be-tween 3.8% and 4.4%, with a maximum of 5.2% being possi-ble. The base value has decreased by 0.12 percentage pointsto 4.02%. When analysing the performance expectations for universitycities, the significant structural differences and the associateddifferent risk structures must be taken into account. Invest-ments in thriving, structurally strong cities such as Freiburgthus represent a secure investment, but the attainable yieldshere only amount to 4.00% at most. By contrast, Frankfurt(Oder) has structural weaknesses and is experiencing popula-tion declines. However, the maximum attainable yield here is ata considerably higher level of 6.5%.
Residential Property Markets in University CitiesThe 3.50 to 4.49-Percenters – Property-Specific IRR
Multipliers Multi-Family House*, avg. University Cities
2016 - 2020 forecast, *existing properties
06 08 10 12 14 16 18 200.0
5.0
10.0
15.0
20.0
IRR Range Residential University Cities
Results Range
IRR base value 4.02 % Maximum3.00$%
performance expectation
3.8 - 4.4 %
Who should invest?
core-investors
3.9 - 4.4 % previous year
max. up to 5.2 %max. up to 5.0 % previous year
3.00$%
3.10$%
3.10$%3.10$%
3.20$%
3.20$%3.30$%3.30$%
Conclusion
University cities display significant structural differences.For this reason, investment recommendations can bemade at the level of the individual cities only.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to national
liquidityvolatility
mediumlow
3.40$%
3.40$%3.50$%3.50$%3.50$%3.60$%3.60$%3.70$%
marketable size up to approx. 50 m euros 3.70$%3.80$%
3.0 % 3.3 % 3.7 % 4.0 % 4.4 % 4.8 % 5.1 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
average
maximum
Selected Model Assumptionstypetypical property size
multi-family house, stock4,000 sqm
no. of apartment unitsnet initial yieldvacancy acquisition datemarket rent acquisition date
55 apt. units4.5 %
200 sqm (1 month)7.70 euros/sqm
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Changing working worlds and lifestyles are leading to an in-creased need for flexibility. For example, demand for secondapartments is continuously increasing due to commuting. Thisis also underscored by the growing number of single-personhouseholds. Alongside employees, students represent an im-portant group when it comes to demand for flexible housing,particularly in structurally strong, internationally focussed uni-versity cities. Micro-apartments represent a housing industryresponse to these new requirements. The product range ishighly diversified, running from simple, functional facilities toluxurious apartments with concierge services. Structurally weakmarkets can benefit from this development to a limited extentonly, as there is usually no shortage of housing here. For thepurposes of this analysis, micro-apartments are defined assmall, furnished apartments for which individual rental agree-ments are concluded. Operator solutions were not included inthe model calculation.
The IRR analysis showed a year-on-year decrease in the basevalue of 0.05 percentage points to a current level of 4.00 %. Overall, core investors can achieve an IRR of between 3.6 %and 4.5 %. A maximum of up to 5.9 % is possible. The major structural differences in university cities come tobear to a particularly strong degree in the investment analysisfor micro-apartments. The suitability of markets in structurallyweak regions should be scrutinised before making an invest-ment.
The Market for Micro-Apartments in University CitiesThe 3.50 to 4.49-Percenters – Property-Specific IRR
Range IRR Micro-Apartments UC
Results Range
IRR base value 4.00 % Maximum2.20$%
performance expectation
3.6 - 4.5 %
Who should invest?
core-investors
4.0 - 4.7 % previous year
max. up to 5.9 %max. up to 6.0 % previous year
2.30$%
2.40$%
2.50$%2.50$%
2.60$%
2.70$%2.80$%2.80$%
Conclusion
For a successful investment in micro-apartments, inves-tors should seek out particularly structurally strong loca-tions with internationally focussed universities.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to international
liquidityvolatility
mediummedium
2.90$%
3.00$%3.10$%3.10$%3.20$%3.30$%3.30$%3.40$%
marketable size up to approx. 20 m euros 3.50$%3.60$%
2.2 % 2.8 % 3.4 % 4.0 % 4.6 % 5.2 % 5.8 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
Selected Model Assumptionstypetypical property size
existing building4,000 sqm
no. of apartment unitsnet initial yieldvacancy acquisition datemarket rent acquisition date
200 apt. units4.4 %
200 sqm (1 month)14.80 euros/sqm
avg. term of lease max. 2 years
Development No. of 1-Person-Households in Univ.-Cities
Source: Federal Statistical Offices, forecast > 2015
06 10 14 18 22 26 3080
90
100
110
120
130
Inde
x (2
006
= 10
0)
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Unlike student cities, for example, B cities have a demandstructure that is increasingly also founded on commuters. Thisis also underscored by the development of single-personhouseholds, for which the forecast anticipates continuedgrowth in the future. The degree of attractiveness for micro-apartments varies significantly between the individual markets,as is also reflected in the different project development activi-ties. In this context, please refer to the above definition of themicro-apartment product category for the purposes of thisanalysis.
The expected performance for micro-apartments in B marketshas fallen by 0.22 percentage points year-on-year to a basevalue of 3.83 %. The attainable IRR range for core investors isbetween 3.4 % and 4.3 % and a maximum of 5.9% can beachieved.
The Market for Micro-Apartments in B-CitiesThe 3.50 to 4.49-Percenters – Property-Specific IRR
IRR Range Micro-Apartments B-Cities
Results Range
IRR base value 3.83 % Maximum1.90$%
performance expectation
3.4 - 4.3 %
Who should invest?
core-investors
3.7 - 4.4 % previous year
max. up to 5.9 %max. up to 5.2 % previous year
2.00$%
2.10$%
2.20$%2.20$%
2.30$%
2.40$%2.50$%2.60$%
Conclusion
Owing to their structural differences, only selected B cit-ies are suitable as investment locations for micro-apart-ments.
Market Environmentinvestment demanddemand for space
regional up to nationalregional up to national
liquidityvolatility
mediummedium
2.70$%
2.70$%2.80$%2.90$%3.00$%3.10$%3.10$%3.20$%
marketable size up to approx. 20 m euros 3.30$%3.40$%
1.9 % 2.6 % 3.2 % 3.9 % 4.5 % 5.2 % 5.8 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
Selected Model Assumptionstypetypical property size
existing buildiing4,000 sqm
no. of apartment unitsnet initial yieldvacancy acquisition datemarket rent acquisition date
200 apt. units4.3 %
200 sqm (1 month)15.30 euros/sqm
avg. term of lease max. 2 years
Development No. of 1-Person-Households in B-Cities
Source: Federal Statistical Offices, forecast > 2015
06 10 14 18 22 26 3080
90
100
110
120
130
Inde
x (2
006
= 10
0)
Definition Micro-Apartments
criteria
complexes with around 100 to 300 units, mostlyone-room apartments measuring 18 square me-tres to 35 square metres
partly or fully furnished, always with a separatekitchen unit and bathroom
in some cases, optional services such as fitnessfacilities, concierge, laundry
location with good local public transport and roadconnections and accessibility of workplaces
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A uniform description of the housing markets in Germany’s 14B cities is possible only to a limited extent, as they have devel-oped very differently in some cases. While cities such as Leip-zig, Dresden and Münster have recorded strong populationgrowth in recent years, the number of residents in Bochum andDuisburg has decreased. The key market figures for the indi-vidual cities therefore cover wide ranges.The average multipliers in relation to actual rent for existingapartment buildings are 11.3 in Duisburg and 12.1 in Bochum,the average multiplier for Münster is 19.7.
The performance expectation for residential properties in Bmarkets has fallen by 0.21 percentage points year-on-year andthe IRR base value therefore currently amounts to 3.76 %.Core investors can expect a yield (IRR) of 3.5 % to 4.1 %. Amaximum of 4.9 % can be achieved.This is based on the assumption of a stable existing property.Renovations and new buildings were not included in the analy-sis.The possibility to increase performance is limited. In many mar-kets, there is only limited potential for rent increases for exist-ing properties due to the higher regulatory requirements.As real estate transfer tax has been raised in many federalstates in recent years, reducing transaction costs by way ofshare deal design has become increasingly important.
Residential Property Markets in B-CitiesThe 3.50 to 4.49-Percenters – Property-Specific IRR
Multipliers Multi-Family House (Existing), avg. B-Cities
2016 - 2020 forecast
06 08 10 12 14 16 18 208.0
12.0
16.0
20.0
24.0
Selected Model Assumptionstypetypical property size
multi-family house, stock4,000 sqm
no. of apartment unitsnet initial yieldvacancy acquisition datemarket rent acquisition date
55 apt. units4.2 %
200 sqm (1 month)7.70 euros/sqm
IRR Range Residential B-Cities
Results Range
IRR base value 3.76 % Maximum2.60$%
performance expectation
3.5 - 4.1 %
Who should invest?
core-investors
3.8 - 4.2 % previous year
max. up to 4.9 %max. up to 4.9 % previous year
2.70$%
2.70$%
2.80$%2.80$%
2.90$%
2.90$%3.00$%3.00$%
Conclusion
For security-focussed investors, investments in structur-ally strong B markets are generally recommended.
Market Environmentinvestment demanddemand for space
regional up to nationalregional up to national
liquidityvolatility
highmedium
3.10$%
3.10$%3.20$%3.20$%3.20$%3.30$%3.30$%3.40$%
marketable size up to approx. 75 m euros 3.40$%3.50$%
2.6 % 3.0 % 3.4 % 3.8 % 4.1 % 4.5 % 4.9 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
average
maximum
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© bulwiengesa AG 2016 page 25/44
THE 5 % STUDY 2016
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2015 was an excellent year for tourism in Germany. With 166.8million arrivals and 436.2 million overnight stays, commercialaccommodation providers in Germany achieved a new record.Over the past ten years, overnight stays in Germany have risenby around 27 % and arrivals by almost as much as 39 %.
In line with this development, the asset class of hotels is be-coming increasingly important in the real estate industry andthis is also reflected in growing pressure on yields. The initialgross yield for hotel properties in Germany has thus decreasedby 1.1 percentage points over the past five years. In line withthis, there was also a high level of construction activity on theGerman hotel market and thus a corresponding supply.
In the past five years, an average of around 9,700 new hotelrooms per year have been built. Last year alone, the comple-tion volume amounted to approximately 9,730 rooms in 75 ho-tels. However, this did not quite match the peak level from2014. Two emerging development trends are on the one hand the re-purposing of existing buildings as hotels (for example as a re-sult of rising land prices) and on the other hand a decrease inmajor projects with more than 300 rooms, although the hotelsplanned by Motel One, for example, are larger on average. Throughout Germany, only one hotel with more than 300 roomswas constructed in 2015 (in Berlin), whereas in the previous
years an average of more than 1,200 new rooms a year wereattributable to large hotels.
Construction activity continues to be driven by the expansion ofchain hotel business (“multi-branding”). Around 81 % of allrooms completed in 2015 were acquired by hotel chains. Withbrands such as Aloft (Starwood/Marriott), Curio by Hilton, TulipInn Alp Style (Louvre), Super 8 (Wyndham), moxy (Marriott),Harry’s Home (Familie Ultsch) and the hotel apartment brandCapri by Fraser (Frasers Hospitality), a wide range of conceptswere launched in Germany in 2015. The centre of construction activity for new hotels in Germany isstill the city of Berlin, which exceeded the level of 30 millionovernight stays in 2015. In the past five years, around 10,000new rooms – one-fifth of the total volume throughout Germany – were built in the capital city. However, Munich moved aheadof Berlin in terms of completions last year, with 1,661 new hotelrooms. For further information on the German hotel market, please re-fer to bulwiengesa’s short study on “Hotel construction in Ger-many” (download: www.bulwiengesa.de).
The Market for Hotel PropertiesThe 3.50 to 4.49-Percenters – Property-Specific IRR
Overnight Stay* in Germany
Source: destatis; * overnighter in hotel/bed and breakfast establishm.
Abstand oben/unten: je 0,1 cm - Höhe: automatisch, Ausrichtung: oben, zentriert, Absatz/Schrift: 07a-Tabelle/Grafik ÜS weiß, Hintergrund: Füllung Tab Titel Blau1
Höhe: 5,2 cm, Hintergrund: Hintergrund Blau2 30%
Abstand oben/unten: je 0,05 cm - Höhe: automatisch, Ausrichtung: oben, Absatz/Schrift: 05-Source06 07 08 09 10 11 12 13 14 15
100
110
120
130
140
Inde
x (2
005
= 10
0)
Completions Hotel Rooms*
* facilities with a minimum size of 40 rooms
2011 2012 2013 2014 20150
3,0006,0009,000
12,00015,000
hotel chain/coop. individual hotel
Gross Initial Yield Hotel Properties
2011 2012 2013 2014 2015 Q2/164 %
5 %
6 %
7 %
8 %
Selected Model Assumptions
buildingtype of contract
stock/no restructuringlease contract
lease term
typical property size (sqm)
range of lease economy(euros/room/month)range of lease midscale(euros/room/month)
5 - 25 years
2,600 - 9,000
200 - 450
400 - 600
leasing rate upscale(euros/room/month)net initial yield
600 - 1,000
4.5 %
bulwiengesa
© bulwiengesa AG 2016
It is not just demand from users that is at a high level in allcategories of hotel properties. This asset class is also becom-ing increasingly important on the investment market. As a re-sult, prices for hotel properties have risen sharply in recentyears. Whereas in 2011 initial gross yields were still at a levelof 6.6 %, values of 5.1 % are now expected.
This is also reflected in the performance expectation for hotelproperties. In the analysis of all hotel categories (from economyto upscale), the base value has decreased by around 0.3 per-centage points and currently amounted to between 3.73 % and3.83 %, depending on the hotel category. The performance expectations for core investors are between3.4 % and 4.8 %. Here, economic success is closely tied to theterm of the lease contracts and the CapEx required as at theend of the lease term. Investments in operator-managed properties such as hotels stillpresent particular challenges, as the relationship between thecontract term and the rate of return/value regularly poses a di-lemma for investors. On the one hand, secure income can begenerated with very low administrative and maintenance costs,and on the other hand risk premiums rise as contract terms de-crease, which has a negative impact in an exit scenario.This then presents opportunities for yield-focussed experts whobuy up short-term lease contracts and thus take on the risk ofmedium-term yield losses (non-core investors). An IRR of up to7.0 % can be achieved in this case. Refurbishment and restructuring measures were not includedin the model assumptions.
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Non-Core
Core
IRR Range Economy Hotel
1.6 % 2.5 % 3.4 % 4.2 % 5.1 % 6.0 % 6.9 %
property-specific IRR
0 %1 %2 %3 %4 %5 %6 %7 %
prob
abilit
y
IRR Range Midscale Hotel
1.0 % 1.9 % 2.8 % 3.8 % 4.7 % 5.7 % 6.6 %
property-specific IRR
0 %1 %2 %3 %4 %5 %6 %7 %
prob
abilit
y
IRR Range Upscale Hotel
1.5 % 2.4 % 3.3 % 4.2 % 5.1 % 6.0 % 6.9 %
property-specific IRR
0 %1 %2 %3 %4 %5 %6 %7 %
prob
abilit
y
Results RangeIRR base value
performance expectation3.73 - 3.83 %
Who should invest?
3.4 - 4.8%
3.7 - 5.1%
up to 7.0 %
up to 7.6 %
core-investors
previous year
non-core-investors
previous year
Conclusion
For core investors, long-term lease contracts with establishedoperators at sustainable locations are recommended.
Market Environmenttype of marketinvestment demanddemand for spaceliquidity
hotels in magic citiesnational up to internationalnational up to internationalmedium
volatilitymarketable size
mediumapprox. 5 - 100 m euros
core
core
core
non-core
non-core
non-core
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© bulwiengesa AG 2016 page 27/44
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After office properties, retail properties still represent the nextmost important asset class on the German real estate invest-ment market. In 2015, retail properties worth approximately 18billion euros in total were sold, accounting for roughly a third ofthe total investment market. Shopping centres represent thelargest-volume investment opportunities in the retail segment.For several years now, they have been going through a proc-ess of qualitative upheaval. For example, all new developmentsin the past few years have been in city-centre locations. Additional challenges are arising from the growing importanceof online retail. The prevailing sector mix in shopping centreshas also evolved in this context, with periodically requiredgoods in particular becoming more important in the past fewyears.Investors in shopping centres should therefore have goodknowledge of the industry and be able to participate in marketdevelopments.
As in the other asset classes, the IRR base value decreasedyear-on-year and currently amounts to 3.50 %. Core investors achieve an IRR of 3.0 % to 3.7 % and a maxi-mum of up to 4.9 % is possible.One particularly important factor for shopping centres is theCapEx measures that need to be performed regularly as a re-sult of the structural changes described above.
The Market for Shopping CentresThe 3.50 to 4.49-Percenters – Property-Specific IRR
Development Gross Initial Yield of Shopping Centres
Q22010
Q22011
Q22012
Q22013
Q22014
Q22015
Q22016
4.0 %4.5 %5.0 %5.5 %6.0 %6.5 %7.0 %
Selected Model Assumptionstypequality
stock, three-floor*no revitalisation
property size / number of shopsnet initial yieldrange of rent (p.m.)avg. weighted rent (basement)
48,000 sqm / 754.7 %
10.00 - 60.00 euros/sqm15.30 euros/sqm
avg. weighted rent (ground floor)avg. weighted rent (first floor)*inner-city location
23.30 euros/sqm19.40 euros/sqm
IRR Range Shopping Centres
Results Range
IRR base value 3.50 % Maximum1.90$%
performance expectation
3.0 - 3.7 %
Who should invest?
core-investors
3.1 - 3.8 % previous year
max. up to 4.9 %max. up to 4.9 % previous year
2.00$%
2.00$%
2.10$%2.20$%
2.20$%
2.30$%2.30$%2.40$%
Conclusion
Shopping centres still represent a large-volume invest-ment option. The sustainability of the existing spacestructures and the competitive environment in particularshould be examined.
Market Environmentinvestment demanddemand for space
national up to internationalnational up to international
liquidityvolatility
highmedium
2.50$%
2.50$%2.60$%2.60$%2.70$%2.80$%2.80$%2.90$%
marketable size approx. 80 - 500 m euros 2.90$%3.00$%
1.9 % 2.4 % 2.9 % 3.4 % 3.8 % 4.3 % 4.8 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
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54
6
The 3-Percenters
Whereas just a few years ago the office market in A cities werecharacterised by a significant excess supply, some markets arenow showing a shortage of space. For example, the vacancyrates in Berlin, Munich and Stuttgart are currently between3.3 % and 3.4 %. Frankfurt am Main, the office location with themost active property developer market, is the only city with arate above the 10 % mark. The observable reduction in vacancies is generally attributableto two factors. Firstly, demand for office space is increasing inmost A markets, and secondly, structurally weak office proper-ties are being converted into other types of use (housing, ho-tels). In line with this development, the trend in rents is alsopositive, with the average rent for A cities rising from 17.60euros/sqm RA-C in the previous year to 17.80 euros/sqm RA-Cnow. Yields decreased again compared to the previous yearand are currently at a level of 4.1 % (net initial yield).
As a result of the yield compression, the IRR base value de-creased by 0.22 percentage points to 3.29 %. Core investorscan expect a range of 1.9 % to 4.3 %.Non-core investments are made chiefly in those properties inperipheral locations and with structural weaknesses. If existingvacancies can be reduced and these properties can be stabi-lised, an IRR of up to 9.1 % can be expected. Refurbishmentmeasures and project developments were not included in thisassessment.
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© bulwiengesa AG 2016 page 29/44
The Market for Office Properties in A-CitiesThe 2.50 to 3.49-Percenters – Property-Specific IRR
THE 5 % STUDY 2016
WHERE IT STILL PAYS OFF TO INVEST
Development Net Initial Yield A-Cities
2016 - 2020 forecast
06 08 10 12 14 16 18 202 %
3 %
4 %
5 %
6 %
Selected Model Assumptionstypetypical property size
existing building24,600 sqm
net initial yieldvacancy acquisition datemarket rent acquisition dateavg. term of lease
4.1 %5.8 %
17.80 euros/sqm3 years
IRR Range Office A-Cities
Results Range
IRR base value 3.29 % Maximum.1.70$%
performance expectation
1.9 - 4.3 %
Who should invest?
core-investors
2.3 - 4.6 % previous year
up to 9.1 %up to 9.8 %
non-core-investors
previous year
.1.50$%
.1.30$%
.1.10$%.0.90$%
.0.60$%
.0.40$%.0.20$%0.00$%
Conclusion
The office markets in the A cities are generally provingvery lively. Yield opportunities are very limited.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to international
liquidityvolatility
highhigh
0.30$%
0.50$%0.70$%0.90$%1.10$%1.40$%1.60$%1.80$%
marketable size approx. 3 - 500 m euros 2.00$%2.20$%
-1.7 % 0.0 % 1.8 % 3.6 % 5.3 % 7.1 % 8.9 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
non-core
bulwiengesa
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Whereas the micro-apartment product category still mostly rep-resents a niche in the B cities and university cities analysed, itsimportance in the A markets is growing significantly. Micro-apartments are increasingly being developed here, particularlyin international cities that are dominated by the service sectorand in which commuters play a major role (Berlin, Düsseldorf,Frankfurt, Hamburg, Munich, Cologne, Stuttgart). This is firstlydue to the fact that higher rents can be generated here than inconventional rental apartments, and secondly to the growingdemand for flexible housing.Another special feature of micro-apartments is that they offerthe possibility to react to market changes directly, as the termsof the rental agreements are usually relatively short.
The model assessment assumes an existing building with indi-vidually let apartments. Renovation properties and buildingsleased to an operator are not included in the assessment.The IRR base value is currently 3.16 %, down 0.18 percentagepoints on the previous year’s level. Core investors achieve be-tween 2.7 % and 3.7 %. Micro-apartments are not relevant tonon-core investors due to the price level. The performance ofmicro-apartments depends to a large extent on their manage-ment and on avoiding vacancy periods. The need to replacefurniture and fittings and the higher maintenance/administrativeexpenses must be taken into account.
The Market for Micro-Apartments in A-CitiesThe 2.50 to 3.49-Percenters – Property-Specific IRR
Number of 1-Person-Households in A-Cities
Source: Bundesinstitut für Bau-, Stadt- und Raumforschung
Berlin
Hambu
rgMun
ichColo
gne
Frank
furt
Stuttga
rtDüs
seldo
rf
0300600900
1,200
num
ber i
n th
ousa
nd
20062015
Selected Model Assumptionstypetypical property size
existing building4,000 sqm
no. of apartment unitsnet initial yieldvacancy acquisition datemarket rent acquisition date
200 apt. units3.6 %
200 sqm (1 month)21.80 euros/sqm
avg. term of lease max. 2 years
IRR Range Micro-Apartments A-Cities
Results Range
IRR base value 3.16 % Maximum1.20$%
performance expectation
2.7 - 3.7 %
Who should invest?
core-investors
3.0 - 3.8 % previous year
max. up to 5.0 %max. up to 5.1 % previous year
1.30$%
1.40$%
1.50$%1.60$%
1.60$%
1.70$%1.80$%1.90$%
Conclusion
The office markets in the A cities are generally provingvery lively. Yield opportunities are very limited.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to international
liquidityvolatility
highmedium
1.90$%
2.00$%2.10$%2.20$%2.30$%2.30$%2.40$%2.50$%
marketable size up to approx. 40 m euros 2.60$%2.60$%
1.2 % 1.9 % 2.5 % 3.1 % 3.7 % 4.3 % 5.0 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
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© bulwiengesa AG 2016 page 31/44
THE 5 % STUDY 2016
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Demand for housing in the major A cities is unabated and isalso being driven by additional general effects (particularly in-fluxes of refugees). The increasing project development activi-ties are able to offset this demand pressure to a limited extentonly. Owing to the limited availability of land, the product category ofresidential highrises is becoming increasingly important. Suchproperties generally command higher rents and higher pur-chase prices for owner-occupied apartments than standardhousing concepts. Not least for this reason, the increase inmarket rents and prices is set to continue. The investment market remains characterised by a combina-tion of high demand and very limited supply. In this context, themultipliers of annual rent are continuing to increase. The aver-age level for all A cities is currently at 20.7, with Munich repre-senting the most expensive market with a value of 25.3.
It is becoming increasingly difficult for core investors to gener-ate relevant yields. The model calculation shows a yield rangeof 2.6 % to 3.3 % and the IRR base value has fallen to 2.91 %.Residential properties in the A markets are thus the only assetclass below the 3 % mark.Existing properties in A markets do not offer any investment op-portunities for yield-focussed non-core investors. Such opportu-nities are to be found at most in individual renovation propertiesin peripheral areas and were not included in the model calcula-tion.
Residential Property Markets in A-CitiesThe 2.50 to 3.49-Percenters – Property-Specific IRR
Multipliers Multi-Family House (Existing), avg. A-Cities
2016 - 2020 forecast
06 08 10 12 14 16 18 2012.0
16.0
20.0
24.0
28.0
Selected Model Assumptionstypetypical property size
multi-family house, stock4,000 sqm
no. of apartment unitsnet initial yieldvacancy acquisitionmarket rent acquisition
55 apt. units3.3 %
200 sqm (1 month)10.90 euros/sqm
IRR Range Residential A-Cities
Results Range
IRR base value 2.91 % Maximum1.70$%
performance expectation
2.6 - 3.3 %
Who should invest?
core-investors
2.8 - 3.3 % previous year
max. up to 4.3 %max. up to 4.0 % previous year
1.70$%
1.80$%
1.80$%1.90$%
1.90$%
2.00$%2.00$%2.10$%
Conclusion
Very limited yield opportunities for security-focussed in-vestors.
Market Environmentinvestment demanddemand for space
regional up to internationalregional up to international
liquidityvolatility
highlow
2.20$%
2.20$%2.30$%2.30$%2.40$%2.40$%2.50$%2.50$%
marketable size up to approx. 150 m euros 2.60$%2.60$%
1.7 % 2.1 % 2.5 % 3.0 % 3.4 % 3.8 % 4.3 %
property-specific IRR
0 %
1 %
2 %
3 %
4 %
5 %
6 %
prob
abilit
y
core
average
maximum
bulwiengesa
© bulwiengesa AG 2016 page 32/44
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Dummyseite Logistikkarte
The Residential MarketMaximal Obtainable Property-Specific IRR for Core-Investors
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I. Second tenancy law amendment
After passing the “Act to Curb the Rent Increase in Tight Hous-ing Markets and to Strengthen the Purchaser Principle in RealEstate Brokerage”, also known as the rent control law, in Aprillast year, Germany’s Grand Coalition government now intendsto make improvements with the second tenancy law amend-ment, as the rent control law evidently has not had the desiredsuccess. The second tenancy law amendment is to include thefollowing regulations:
1. Rent index: extension of the period under consideration(from 4 years to x years; periods of 6, 8 and even 10 yearsare being discussed);
2. Modernisation:
– Cap for rent increases; rent must not rise by more than 50 %or a maximum of 3.00 euros/sqm within 8 years as a resultof modernisation-related rent increases;
– Reduction of the modernisation cost allocation from 11 % to8 %;
– Hardship provision in the case of modernisation-related rentincreases; a case of hardship is always to be recognised ifthe gross rent excluding heating, including modernisation-re-lated rent increases, exceeds 40 % of the tenant’s net in-come;
3. Residential space: definition of mandatory calculation meth-ods;
4. Deficiency in the case of a deviation in space of more than10 %;
5. Possibility for remedy in the case of regular termination dueto default on payments.
The above measures represent a major intervention into thedetermination of rent levels. Another factor that is increasinglyinfluencing rents is preservation statutes in the form of neigh-bourhood protection statutes, which are being used more andmore often by municipalities. Aimed at preserving the tenantstructure in individual urban districts, neighbourhood protectionstatutes govern aspects such as apartment extensions andmay also prohibit conversions into owner-occupied apartments. There is reason to fear that the drastic measures will have asignificant impact on investments in residential construction. In-stead of constantly adopting more regulations, politiciansshould make land available for construction and force federal
states and municipalities to invest in residential constructionthemselves. Increasing the supply is the only way to counterthe growing shortage of housing and the resulting rise in rentsand thus to create affordable housing.
II. Directive on residential real estate loans
The Act to Implement the Directive on Residential Real EstateLoans came into force on 21 March 2016. One significant effectof the implementation of this European directive is that the rightof revocation for newly concluded real estate loans expires nolater than one year and 14 days after the consumer loan agree-ment is concluded. As such, there is no longer a “perpetualright of revocation”. Banks now also have to take account of significant changeswhen granting real estate loans. Under the new legislation,banks must explain the content of their offers in detail. The re-quirements for credit assessments have also been raised, withthe effect that a loan cannot be granted until the bank has care-fully checked whether the applicant is solvent. If the lender fails to comply with these obligations and con-cludes a loan agreement despite a lack of creditworthiness, thecustomer can terminate the loan agreement at any time. In thiscase, the customer is not required to pay a prepayment pen-alty. Finally, tie-in deals are now also generally prohibited in thecase of real estate loans. However, the law explicitly providesfor exceptions to this prohibition under certain conditions. Firstly, we should welcome the fact that it is now clear that “un-popular” loan agreements can no longer be revoked years aftertheir conclusion due to incorrect instructions. The other provi-sions of the Directive on Residential Real Estate Loans areaimed at additional consumer protection, but this has the effectthat consumers – particularly low-income earners such as ca-reer starters, single parents and senior citizens – are hardlyable to obtain loans any more. This is counterproductive as politicians should actually supportconsumers, and in particular the groups mentioned above, withacquiring real estate. As a result of the current low interest ratephase, taking advantage of these low rates to purchase proper-ties represents the only possibility for even consumers on a lowincome to accumulate wealth and make provisions for retire-ment.
Excursus on the secondary law amendment and the directiveon residential real estate loansBy Klaus Beine, BEITEN BURKHARDT Rechtsanwaltsgesellschaft mbH
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The Results in Detail
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Städtezuordnung Büro
Office – Property-Specific IRR in Detail
A-, B-, C- and D-Cities in Detail – Property Specific IRR
type city core-i.
from
A
A
A
A
Berlin
Cologne
1.7 %
1.9 %
Düsseldorf
Frankfurt (Main)
2.0 %
1.9 %
A
A
A
Hamburg
Munich
1.8 %
1.3 %
Stuttgart 1.9 %
B
B
B
B
Bochum
Bonn
3.0 %
2.3 %
Bremen
Dortmund
2.9 %
2.6 %
to
non-core-i.
up to
type city
4.1 %
4.4 %
8.8 %
9.6 %
4.2 %
4.0 %
8.3 %
8.5 %
C Wuppertal
D
D
Albstadt
Aschaffenburg
4.1 %
3.8 %
8.6 %
9.0 %
4.4 % 8.7 %
D
D
Bamberg
Bayreuth
D
D
Bergisch Gladbach
Bottrop
5.5 %
4.7 %
9.9 %
10.1 %
5.5 %
4.9 %
12.3 %
9.4 %
D
D
Brandenburg (Hl.)
Bremerhaven
D
D
Chemnitz
Coburg
core-i.
from to
non-core-i.
up to
type
3.6 % 6.7 %
4.5 %
3.6 %
8.1 %
6.2 %
12.4 % D
D
14.5 %
11.5 %
D
D
city core-i.
from to
non-core-i.
up to
Krefeld
Landshut
3.1 %
3.4 %
Leverkusen
Lüdenscheid
3.3 %
5.1 %
5.9 %
6.0 %
10.7 %
11.1 %
5.9 %
8.0 %
11.8 %
13.8 %
3.2 %
4.3 %
6.2 %
7.0 %
4.1 %
4.4 %
6.6 %
7.2 %
11.6 %
13.5 %
D
D
11.5 %
12.9 %
D
D
3.9 %
3.3 %
7.5 %
6.7 %
5.8 %
3.7 %
8.8 %
6.5 %
12.7 %
14.0 %
D
D
15.6 %
12.8 %
D
D
Ludwigshafen
Lüneburg
3.8 %
4.3 %
Marburg
Minden
3.8 %
4.0 %
6.5 %
7.0 %
12.0 %
12.5 %
6.7 %
7.2 %
11.5 %
13.9 %
Moers
Neubrandenburg
4.4 %
6.0 %
Neumünster
Neuss
3.9 %
3.2 %
7.2 %
8.9 %
13.1 %
13.7 %
6.9 %
5.6 %
12.4 %
10.3 %
B
B
B
B
Dresden
Duisburg
2.7 %
3.0 %
Essen
Hanover
2.5 %
2.7 %
B
B
B
B
Karlsruhe
Leipzig
2.8 %
2.7 %
Mannheim
Münster
2.8 %
2.6 %
5.4 %
5.5 %
10.8 %
10.1 %
4.8 %
5.0 %
10.2 %
9.1 %
D
D
Constance
Cottbus
D
D
Dessau
Detmold
5.5 %
5.6 %
10.8 %
10.7 %
5.1 %
5.1 %
10.4 %
12.2 %
D
D
Düren
Eisenach
D
D
Flensburg
Frankfurt (Oder)
B
B
C
Nuremberg
Wiesbaden
2.2 %
2.4 %
Aachen 2.8 %
C
C
C
C
Augsburg
Bielefeld
2.8 %
3.7 %
Brunswick
Darmstadt
3.4 %
2.9 %
4.9 %
4.8 %
10.8 %
10.1 %
5.5 % 10.0 %
D
D
Friedrichshafen
Fulda
D
D
Fürth
Gelsenkirchen
5.8 %
6.7 %
11.9 %
14.5 %
6.2 %
5.3 %
13.2 %
9.5 %
D
D
Gera
Gießen
D
D
Görlitz
Göttingen
3.4 %
5.3 %
5.9 %
8.4 %
4.9 %
4.1 %
8.3 %
7.4 %
11.5 %
13.2 %
D
D
14.8 %
13.5 %
D
D
3.6 %
4.5 %
6.5 %
7.8 %
3.7 %
5.3 %
6.6 %
8.4 %
12.5 %
14.8 %
D
D
12.3 %
14.0 %
D
D
Oberhausen
Offenburg
3.2 %
3.4 %
Oldenburg
Paderborn
3.9 %
3.0 %
5.8 %
6.3 %
11.2 %
11.9 %
6.9 %
5.8 %
15.7 %
10.8 %
Passau
Pforzheim
3.1 %
3.1 %
Plauen
Ratingen
6.8 %
3.4 %
5.8 %
6.0 %
12.5 %
11.7 %
10.5 %
5.7 %
19.4 %
10.8 %
3.0 %
4.1 %
5.9 %
7.4 %
3.5 %
4.1 %
6.3 %
7.0 %
10.7 %
14.5 %
D
D
14.3 %
13.1 %
D
D
5.0 %
4.1 %
8.3 %
6.8 %
5.2 %
3.7 %
9.0 %
6.6 %
15.3 %
11.7 %
D
D
15.4 %
11.2 %
D
D
Ravensburg
Recklinghausen
4.2 %
3.6 %
Remscheid
Reutlingen
3.9 %
3.2 %
7.0 %
6.6 %
12.8 %
12.6 %
6.7 %
5.8 %
12.1 %
10.2 %
Rosenheim
Salzgitter
3.4 %
3.5 %
Schweinfurt
Schwerin
4.3 %
4.2 %
5.8 %
6.6 %
10.4 %
12.9 %
7.4 %
7.0 %
13.2 %
13.3 %
C
C
C
C
Erfurt
Erlangen
3.4 %
2.8 %
Freiburg
Heidelberg
2.9 %
2.7 %
C
C
C
C
Kiel
Lübeck
3.3 %
3.3 %
Magdeburg
Mainz
3.7 %
2.9 %
5.9 %
5.8 %
10.5 %
13.1 %
5.5 %
5.0 %
11.2 %
9.0 %
D
D
Greifswald
Gütersloh
D
D
Hagen
Halberstadt
5.8 %
6.2 %
11.2 %
12.1 %
6.3 %
5.5 %
11.5 %
10.4 %
D
D
Halle (Saale)
Hamm
D
D
Hanau
Heilbronn
C
C
C
C
Mönchengladbach
Mülheim (Ruhr)
3.4 %
3.4 %
Offenbach (Main)
Osnabrück
3.3 %
3.2 %
C
C
C
C
Potsdam
Regensburg
2.8 %
2.4 %
Rostock
Saarbrücken
3.3 %
3.6 %
5.8 %
6.1 %
10.9 %
10.6 %
5.7 %
5.9 %
11.3 %
12.9 %
D
D
Herne
Hildesheim
D
D
Ingolstadt
Jena
5.6 %
5.2 %
10.7 %
10.8 %
5.9 %
6.6 %
11.2 %
12.2 %
D
D
Kaiserslautern
Kassel
D
D
Kempten (Allgäu)
Koblenz
5.2 %
4.0 %
8.0 %
6.8 %
5.0 %
4.3 %
7.9 %
8.0 %
13.6 %
12.4 %
D
D
13.5 %
15.0 %
D
D
4.0 %
3.2 %
6.9 %
5.8 %
4.0 %
3.2 %
6.4 %
5.9 %
12.6 %
12.1 %
D
D
11.8 %
11.6 %
D
D
Siegen
Solingen
3.3 %
5.8 %
Stralsund
Suhl
4.5 %
5.7 %
6.1 %
9.2 %
11.3 %
15.3 %
7.9 %
9.1 %
14.0 %
15.8 %
Trier
Tübingen
3.7 %
3.1 %
Ulm
Villingen-Schwenn.
2.9 %
4.9 %
6.7 %
5.6 %
12.6 %
11.0 %
5.4 %
7.6 %
10.8 %
14.0 %
4.8 %
3.4 %
7.7 %
6.2 %
3.4 %
4.2 %
6.1 %
6.6 %
13.1 %
13.1 %
D
D
11.7 %
11.5 %
D
D
3.8 %
3.2 %
6.7 %
6.2 %
3.7 %
3.7 %
6.7 %
6.4 %
12.3 %
12.8 %
D
D
12.7 %
11.4 %
Weimar
Wilhelmshaven
4.7 %
5.1 %
Witten
Wolfsburg
3.4 %
3.6 %
8.1 %
8.4 %
14.1 %
15.2 %
6.2 %
6.2 %
13.3 %
11.1 %
Würzburg
Zwickau
3.9 %
6.2 %
6.4 %
9.4 %
11.9 %
16.1 %
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Städtezuordnung Büro
Residential/Micro-Apartments – Property-Specific IRR in Detail
Residential A-, B- and University Cities (UC) in Detail – Property-Specific IRR in %
type city core-i.
from
A
A
A
A
Berlin
Cologne
2.5 %
2.7 %
Düsseldorf
Frankfurt (Main)
3.0 %
2.6 %
A
A
A
B
Hamburg
Munich
2.5 %
2.2 %
Stuttgart
Bochum
2.7 %
4.4 %
B
B
B
B
Bonn
Bremen
3.2 %
3.4 %
Dortmund
Dresden
3.7 %
3.1 %
to
max.
up to
type city
3.2 %
3.3 %
4.2 %
3.9 %
3.6 %
3.2 %
4.5 %
4.1 %
UC
UC
Bamberg
Bayreuth
UC
UC
Bielefeld
Brunswick
3.0 %
3.1 %
3.8 %
4.3 %
3.4 %
4.8 %
4.4 %
5.5 %
UC
UC
Chemnitz
Constance
UC
UC
Cottbus
Darmstadt
3.6 %
4.1 %
4.4 %
5.0 %
4.2 %
3.7 %
5.0 %
4.7 %
UC
UC
Erfurt
Erlangen
UC
UC
Flensburg
Frankfurt (Oder)
core-i.
from to
max.
up to
type
3.7 %
3.6 %
4.2 %
4.1 %
3.9 %
4.3 %
4.4 %
5.1 %
5.0 %
4.7 %
UC
UC
5.2 %
6.1 %
UC
UC
city core-i.
from to
max.
up to
Kiel
Koblenz
3.7 %
3.4 %
Lübeck
Lüneburg
3.9 %
3.8 %
4.3 %
4.0 %
5.2 %
4.7 %
4.4 %
4.2 %
5.3 %
4.9 %
4.5 %
2.9 %
5.0 %
3.5 %
4.2 %
3.4 %
4.7 %
4.1 %
5.7 %
4.4 %
UC
UC
5.5 %
4.9 %
UC
UC
4.0 %
3.0 %
4.4 %
3.5 %
4.3 %
5.4 %
4.8 %
5.8 %
5.1 %
4.2 %
UC
UC
5.6 %
6.5 %
UC
UC
Magdeburg
Mainz
3.9 %
3.3 %
Marburg
Mönchengladbach
3.7 %
4.1 %
4.3 %
4.0 %
4.9 %
4.8 %
4.1 %
4.6 %
4.8 %
5.6 %
Oldenburg
Osnabrück
2.9 %
3.5 %
Paderborn
Passau
3.6 %
3.2 %
3.4 %
4.0 %
4.2 %
4.7 %
4.0 %
3.7 %
4.9 %
4.6 %
B
B
B
B
Duisburg
Essen
4.3 %
4.0 %
Hanover
Karlsruhe
3.2 %
3.2 %
B
B
B
B
Leipzig
Mannheim
3.2 %
3.7 %
Münster
Nuremberg
2.8 %
3.2 %
4.7 %
4.4 %
5.3 %
5.1 %
3.9 %
3.8 %
5.0 %
4.5 %
UC
UC
Freiburg
Gießen
UC
UC
Göttingen
Greifswald
3.9 %
4.3 %
4.9 %
5.2 %
3.4 %
3.9 %
4.2 %
4.6 %
UC
UC
Halle (Saale)
Heidelberg
UC
UC
Heilbronn
Hildesheim
B
UC
UC
Micro-Apartments A-, B- and University Cities (UC) in Detail – Property-Specific IRR in %
Wiesbaden
Aachen
3.1 %
3.1 %
Augsburg 3.0 %
type
A
A
city core-i.
from
Berlin
Cologne
2.2 %
2.9 %
3.7 %
3.8 %
4.6 %
5.0 %
3.9 % 5.0 %
UC
UC
Jena
Kaiserslautern
UC Kassel
to
max.
up to
3.3 %
3.8 %
4.9 %
5.4 %
type city
UC
UC
Bamberg
Bayreuth
2.7 %
3.9 %
3.2 %
4.6 %
3.4 %
4.9 %
4.0 %
5.4 %
4.0 %
5.5 %
UC
UC
5.0 %
6.1 %
UC
UC
4.1 %
2.7 %
4.5 %
3.4 %
3.9 %
4.0 %
4.5 %
4.4 %
5.0 %
4.3 %
UC
UC
5.4 %
5.2 %
UC
UC
Potsdam
Regensburg
2.9 %
2.9 %
Rostock
Saarbrücken
3.7 %
4.6 %
3.7 %
3.5 %
4.6 %
4.3 %
4.3 %
5.2 %
5.2 %
6.1 %
Siegen
Trier
4.4 %
3.8 %
Tübingen
Ulm
3.4 %
2.9 %
4.7 %
4.4 %
5.4 %
5.3 %
3.9 %
3.6 %
4.7 %
4.7 %
3.9 %
4.0 %
4.4 %
4.4 %
3.8 % 4.6 %
5.3 %
5.2 %
UC
UC
5.6 %
core-i.
from to
3.4 %
3.4 %
4.3 %
4.2 %
max.
up to
type
5.8 %
5.8 %
UC
UC
Wuppertal
Würzburg
4.4 %
3.1 %
4.8 %
3.7 %
5.4 %
4.4 %
city core-i.
from
Kiel
Koblenz
3.8 %
3.2 %
to
max.
up to
4.8 %
4.1 %
6.2 %
5.7 %
A
A
A
A
Düsseldorf
Frankfurt (Main)
3.1 %
2.7 %
Hamburg
Munich
2.9 %
2.2 %
A
B
B
B
Stuttgart
Bochum
2.6 %
4.0 %
Bonn
Bremen
3.2 %
3.5 %
4.0 %
3.7 %
5.3 %
5.3 %
3.7 %
3.4 %
5.2 %
5.1 %
UC
UC
Bielefeld
Braunschweig
UC
UC
Chemnitz
Constance
3.7 %
4.7 %
5.1 %
6.3 %
4.0 %
4.5 %
5.3 %
6.2 %
UC
UC
Cottbus
Darmstadt
UC
UC
Erfurt
Erlangen
B
B
B
B
Dortmund
Dresden
3.6 %
3.0 %
Duisburg
Essen
4.0 %
3.7 %
B
B
B
B
Hanover
Karlsruhe
3.1 %
3.1 %
Leipzig
Mannheim
3.1 %
3.5 %
4.4 %
4.0 %
5.8 %
5.6 %
4.7 %
4.4 %
5.9 %
5.7 %
UC
UC
Flensburg
Frankfurt (Oder)
UC
UC
Freiburg
Gießen
4.1 %
4.0 %
5.6 %
5.2 %
4.2 %
4.5 %
6.0 %
6.0 %
UC
UC
Göttingen
Greifswald
UC
UC
Halle (Saale)
Heidelberg
3.5 %
3.9 %
4.4 %
5.0 %
3.7 %
2.9 %
4.5 %
3.7 %
5.9 %
6.9 %
UC
UC
5.8 %
5.4 %
UC
UC
3.8 %
3.4 %
4.7 %
4.4 %
3.7 %
2.9 %
4.5 %
3.7 %
5.9 %
5.8 %
UC
UC
5.7 %
5.3 %
UC
UC
Lübeck
Lüneburg
3.7 %
3.7 %
Magdeburg
Mainz
3.3 %
3.4 %
4.6 %
4.4 %
6.3 %
5.5 %
4.1 %
4.4 %
5.4 %
6.2 %
Marburg
Mönchengladbach
3.7 %
3.9 %
Oldenburg
Osnabrück
2.9 %
3.2 %
4.5 %
4.8 %
5.7 %
6.3 %
3.7 %
4.1 %
4.8 %
5.5 %
4.0 %
4.6 %
4.9 %
5.4 %
2.7 %
3.9 %
3.5 %
4.9 %
6.2 %
6.6 %
UC
UC
4.6 %
6.5 %
UC
UC
3.3 %
4.5 %
4.2 %
5.4 %
3.4 %
2.7 %
4.1 %
3.7 %
5.8 %
7.2 %
UC
UC
5.3 %
5.3 %
UC
UC
Paderborn
Passau
3.0 %
2.9 %
Potsdam
Regensburg
2.9 %
2.9 %
3.8 %
3.8 %
5.2 %
5.4 %
3.8 %
3.8 %
5.2 %
5.4 %
Rostock
Saarbrücken
3.7 %
4.2 %
Siegen
Trier
4.1 %
3.6 %
4.7 %
5.0 %
6.1 %
6.6 %
4.7 %
4.6 %
6.0 %
5.9 %
B
B
B
UC
Münster
Nuremberg
2.7 %
3.0 %
Wiesbaden
Aachen
3.0 %
3.1 %
UC Augsburg 3.0 %
3.6 %
3.9 %
4.9 %
5.3 %
3.9 %
4.2 %
5.4 %
5.7 %
UC
UC
Heilbronn
Hildesheim
UC
UC
Jena
Kaiserslautern
4.1 % 5.6 % UC Kassel
3.6 %
3.5 %
4.6 %
4.3 %
3.8 %
3.5 %
4.6 %
4.2 %
6.0 %
5.7 %
UC
UC
5.7 %
5.4 %
UC
UC
3.4 % 4.5 % 6.3 %
Tübingen
Ulm
3.5 %
3.2 %
Wuppertal
Würzburg
4.2 %
2.9 %
4.3 %
4.1 %
5.5 %
5.7 %
4.9 %
3.8 %
6.2 %
5.6 %
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Logistics – Property-Specific IRR in Detail
Logistics Regions Property-Specific IRR in Detail in %
logistics region core-i.
from to
A4 Saxony
A4 Thuringia
Aachen
Augsburg
4.4 %
4.6 %
5.7 %
5.9 %
4.5 %
4.2 %
5.8 %
5.4 %
Bad Hersfeld
Berlin
Bremen and North Sea ports
Cologne
3.7 %
4.3 %
5.0 %
4.9 %
4.1 %
4.6 %
5.0 %
5.3 %
Dortmund
Düsseldorf
Halle/Leipzig
Hamburg
4.2 %
4.6 %
5.2 %
5.2 %
4.2 %
4.2 %
4.8 %
4.8 %
non-core-i.
up to
logistics region core-i.
from to
8.1 %
8.2 %
Koblenz
Lower Bavaria
8.2 %
7.6 %
Magdeburg
Munich
4.2 %
4.3 %
5.5 %
5.6 %
4.6 %
3.9 %
5.9 %
4.5 %
7.4 %
6.2 %
Münster/Osnabrück
Nuremberg
6.7 %
6.7 %
Oberrhein
Ostwestfalen-Lippe
4.2 %
4.6 %
5.4 %
5.6 %
4.1 %
4.5 %
5.3 %
5.7 %
7.0 %
6.6 %
Rhine-Main/Frankfurt
Rhine-Neckar
6.0 %
5.8 %
Rhine-Ruhr
Saarbrücken
4.1 %
4.5 %
4.7 %
5.4 %
4.4 %
4.1 %
5.3 %
5.5 %
non-core-i.
up to
7.7 %
8.0 %
9.0 %
5.7 %
7.8 %
7.3 %
7.3 %
8.0 %
6.1 %
7.2 %
7.1 %
7.7 %
Hanover/Brunswick
Kassel/Göttingen
4.1 %
4.1 %
5.1 %
5.5 %
6.7 %
7.5 %
Stuttgart
Ulm
4.1 %
4.1 %
5.1 %
5.3 %
6.9 %
7.5 %
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The Office MarketMaximal Obtainable Property-Specific IRR for Core-Investors
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Dummyseite Logistikkarte
The Market for Micro-ApartmentsMaximal Obtainable Property-Specific IRR for Core-Investors
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General Classification of Cities
Classification as A-, B-, C- and D-cities was used to categorise theGerman real estate market. This was based on the functional signifi-cance of the cities for the international, national and regional or localreal estate market:
A-cities
The most important centres in Germany with national and sometimesinternational significance. Large, well-functioning markets in all seg-ments.
B-cities
Large cities with national and regional significance.
C-cities
Major German cities with regional and limited national significance andan important impact on the surrounding region.
D-cities
Small, regionally focussed locations with a central role for their directsurroundings; lower market volume and sales.
University cities
47 cities with at least 7,000 students are classified as university citiesin this study, not including A- and B-cities since these are analysed se-parately.
Yields/Multipliers (source: gif e. V.)
Gross initial yield
The gross initial yield is a simple comparison of the contractual rent tothe purchase price, not including incidental acquisition costs. The grossinitial yield is equivalent to the reciprocal of the multiplier that is typi-cally used in the market (e.g. 12.5 times the contractual rent = 8 % p.a.gross initial yield).
Gross initial yield = contractual rent / net purchase price
Overview A-, B-, C-, D- and University-Cities (UC)
cityBerlin
categoryA
cityLübeck
CologneDüsseldorfFrankfurt (Main)Hamburg
AA
MagdeburgMainz
AA
MönchengladbachMülheim (Ruhr)
MunichStuttgart
Bochum
AA
Offenbach (Main)Osnabrück
BPotsdamRegensburg
BonnBremenDortmundDresden
BB
RostockSaarbrücken
BB
Wuppertal
categoryC/UC
cityFürth
categoryD
cityNeuss
C/UCC/UC
GelsenkirchenGera
C/UCC
Gießen Görlitz
DD
OberhausenOffenburg
D/UCD
OldenburgPaderborn
CC
Göttingen Greifswald
C/UCC/UC
Gütersloh Hagen
D/UCD/UC
PassauPforzheim
DD
PlauenRatingen
C/UCC/UC
Halberstadt Halle (Saale)
C/UC HammHanau
DD/UC
Ravensburg Recklinghausen
DD
RemscheidReutlingen
categoryDDD
D/UCD/UCD/UC
DDDDDDD
DuisburgEssenHanoverKarlsruhe
BB
AlbstadtAschaffenburg
BB
BambergBayreuth
LeipzigMannheimMünsterNuremberg
BB
Bergisch GladbachBottrop
BB
Brandenburg (Hl.)Bremerhaven
DD
HeilbronnHerne
D/UCD/UC
Hildesheim Ingolstadt
D/UCD
RosenheimSalzgitter
D/UCD
SchweinfurtSchwerin
DD
JenaKaiserslautern
DD
KasselKempten (Allgäu)
D/UCD/UC
SiegenSolingen
D/UCD
StralsundSuhl
Wiesbaden
AachenAugsburg
B ChemnitzCoburg
C/UCC/UC
ConstanceCottbus
BielefeldBrunswickDarmstadtErfurt
C/UCC/UC
DessauDetmold
C/UCC/UC
Düren Eisenach
D/UCD/UC
KoblenzKrefeld
D/UCD
LandshutLeverkusen
D/UCD
TrierTübingen
DD
UlmVillingen-Schwenn.
DD
LüdenscheidLudwigshafen
DD
Lüneburg Marburg
DD
WeimarWilhelmshaven
D/UCD/UC
WittenWolfsburg
DDDD
D/UCDDD
D/UCD/UCD/UC
DDDDD
ErlangenFreiburgHeidelbergKiel
C/UCC/UC
FlensburgFrankfurt (Oder)
C/UCC/UC
FriedrichshafenFulda
D/UCD/UC
MindenMoers
DD
NeubrandenburgNeumünster
DD
WürzburgZwickau
DD
D/UCD
Definitions and Comments
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Net initial yield
The net initial yield represents net rental income in relation to the pur-chase price plus property-specific incidental acquisition costs. For thesake of clarification, please note that other non-recurring costs andrevenue losses/risks are not deducted from the net rental income.
However, calculatory items (e.g. maintenance costs) are also takeninto account in the operating costs or in the gross purchase price. Thevaluations used for this must be in line with the market standard andmust be reported separately when stating the net initial yield. They canbe disclosed either individually for each item or for the cost block as awhole, in which case they can be referred to “operating costs” and “in-cidental acquisition costs” as a simplification (e.g. “net initial yield x.x %p.a. including y % operating costs and z % incidental acquisitioncosts”).
Net initial yield = net rental income / gross purchase price
Short Glossary for Office Property
Vacancy
Vacancy refers to vacant office space at the end of the respective year.It takes account of marketable properties only; structural vacancytherefore is not included.
The vacancy rate shows the ratio of vacancy to total space.
Take-up
Take-up is defined as an annual amount. It describes mostly officespace taken up for rent, but also includes project developments focuss-ing on owner-occupiers. The take-up date is the conclusion of the con-tract in the case of letting and the start of construction in the case ofowner-occupiers.
Rents
Office rents are reported in euros per square metre rentable area ac-cording to gif e.V. (RA-C) and apply to office space in a marketable(technical/spatial) condition with good fixtures and fittings and small tomedium-sized rental units. The reported rents are nominal values. Thenominal rent is the initial rent shown in the contract, not including in-centives, ancillary costs or local taxes.
The prime rent relates the top price segment – in relation to the respec-tive market area – with a market share of between 3 % and 5 % ofrental revenues (not including owner-occupiers) in the past twelvemonths and represents a median value. At least three concluded con-tracts should be included. It does not correspond to the absolute toprent (defined as outliers). To calculate the average rent, the individualrents for all new rental agreements concluded in the defined period areweighted according to the space rented in each case and an average iscalculated.
Short Glossary for Residential Properties/Micro-Apartments
Residential rents
Residential rents for re-letting are reported in euros per square metreof residential space and ideally apply to an apartment with three rooms,around 65 to 95 square metres of residential space and standard fix-tures and fittings. Because the fixtures and fittings and the sizes arestandardised, the degree of variation shown in the rent range is influ-enced mainly by the location and the micro-location. The reported rentsare nominal values.
The rents are stated without including ancillary costs or taking accountof other benefits. Average rents represent the average value across thewhole of the defined market.
The stated rents are average values intended to map a typical or usuallevel. They do not represent the strict arithmetic mean, the mode (mostfrequent value) or the median (central value) in a mathematical sense.
Micro-apartments
Micro-apartments or business apartments are generally found in largercomplexes with 100 to 300 units. They are offered as partly or fully fur-nished one-room apartments measuring between 18 and around 35square metres, with a small kitchen and a separate bathroom. Optionalservices often include a concierge service, fitness facilities and laundryservice. In terms of tax law, micro-apartments represent private-sectorletting rather than operator-managed properties, meaning that rentalagreements are concluded directly between the investor and the ten-ant.
Short Glossary for Retail Property
Specialist retail parks
Specialist retail park are defined as follows: They have: – gross lettable area (GLA) of 10,000 square metres or more – locations on the city outskirts with good transport connections; they
are generally easy to reach, including for the wider surroundings– ground-level floor space and extensive parking space, usually also
at ground level– simple functionality in terms of their appearance – discount retailers with aggressive price strategies that have a
crowd-pulling effect and are supplemented by retailers and serviceproviders with small amounts of space.
Shopping centres
Shopping centres are large-scale facilities that are constructed on thebasis central planning and cover short-, medium- and long-term re-quirements.
They are characterised by: – a spatial focus on retail, catering and service businesses of different
sizes – a generous supply of parking spaces– central management/administration – joint performance of certain functions by all tenants (e.g. advertis-
ing) – and generally have sales space of at least 10,000 square metres.
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Short Glossary for Unternehmensimmobilien(Source: INITIATIVE UNTERNEHMENSIMMOBILIEN)
The statements on Unternehmensimmobilien (UI) in this study arebased on the market data of the INITIATIVE UNTERNEHMENSIMMOBILIENpublished in its Market Reports No. 1 to No. 4. According to these data,UI are mixed-use commercial properties, typically with a SME-domi-nated tenant structure. The mix includes office, warehouse, production,research, service and/or wholesale space as well as open space.
Unternehmensimmobilien comprise four different property categories:– Converted properties (not included in the study due to their very
high degree of variation)– Business parks – Light manufacturing properties – Warehouse/logistics properties
All four categories are characterised by the features of capacity for al-ternative uses, use reversibility and fundamental suitability for multi-party structures. This means that the strengths of Unternehmensimmo-bilien lie in their flexibility with regard to not only the use but also theusers.
Business parks
– Usually planned and constructed specifically to be let out to compa-nies
– Consist of several individual buildings forming a complex– Management and infrastructure are organised uniformly– Have all types of space (share of office space generally between
20 % and 50 %)– Usually located on the outskirts of cities and easily accessible
Light manufacturing properties
– Predominantly individual hall properties with a moderate officeshare
– Suitable for a variety of types of production– In principle, hall space can also be used for other purposes such as
storage, research, services, wholesale and retail– Capacity for alternative uses depends primarily on the location
Warehouse properties
– Predominantly existing properties with mainly basic storage facilitiesand in some cases service space
– Within Unternehmensimmobilien, distinguished from modern logis-tics halls by a maximum size of 10,000 square metres
– Varying fit-out and quality standards– Flexible and inexpensive types of space– Generally reversible and suitable for higher-value uses (e.g. through
retrofitting of ramps and gates)
Short Glossary for Logistics Properties
The study relates to a modern logistics property with hall space of morethan 10,000 square metres.
Rents for warehouse/logistics space are reported in euros per squaremetre of hall space and apply to a heatable hall with standard fixturesand fittings, not including high-bay warehouses or similar, that are lo-cated in a conventional industrial area with good connections. The re-ported rents are nominal values.
The rents are stated without including ancillary costs or taking accountof other benefits. Maximum and average values are shown. The maxi-mum rents represent an average value for the top 3 to 5 % of the mar-ket. They do not correspond to the absolute top rent (defined as out-liers). Average rents represent the average value across the whole ofthe defined market.
The stated rents are average values intended to map a typical or usuallevel. They do not represent the strict arithmetic mean, the mode (mostfrequent value) or the median (central value) in a mathematical sense.
Short Glossary for Hotels
Magic Cities
This term refers to the city alliance Magic Cities e. V., which includesthe following cities as its members: Berlin, Cologne, Dresden, Düssel-dorf, Frankfurt am Main, Hamburg, Hanover, Leipzig, Munich, Nurem-berg and Stuttgart. These cities are characterised by above-averagetourist demand and a corresponding diverse offering for tourists(magic-cities.com).
Classification
This study is based on the following breakdown:Economy: 1 or 2 stars(Upper) midscale: 3 stars (3+ stars)(Upper) upscale: 4 stars (4+ stars)Luxury: 5 stars
The breakdown is based on the hotel classification used by DEHOGA(German Hotel and Restaurant Association), while the number of starsis taken from the online portals expedia.de and booking.com.
CompletionsThe completion figures relate to newly constructed hotels and bed-and-breakfast hotels with at least 40 rooms. Renovations and changes inthe operator are not taken into account. The bulwiengesa study Hotel-neubau in Deutschland (2016) served as a source.
List of abbreviations
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List of Abbreviations
ECB
GDP
European Central Bank
gross domestic product
gif e. V.
IRR
(non-)core-I.
RA-C
gif Gesellschaft für immobilienwirtschaftliche Forschung e. V.
internal rate of return
(non-)core-investors
rentable area according to gif
SME
sqm
UI
UC
small and medium-sized enterprises
square metres
Unternehmensimmobilien
university cities
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Comments on the Model
In general, renovations and project developments are not included. Allcalculations in the study are based on data, forecasts and analyses bybulwiengesa AG and its knowledge of the market. In addition to rentloss risk, vacancy risk is also taken into account in the cash flow calcu-lation.
Terminology
Market liquidity is defined as investment demand irrespective of eco-nomic cycles.Fluctuation refers to changes in tenants assumed at predefined dates –depending on the asset class.
Office
The study presents 127 office markets, broken down into A-, B-, C- andD-cities. A notional existing office property with average-quality spaceis assumed. The property size varies depending on the volume of theoffice market and the average take-up over the past ten years. Themodel also assumes annual fluctuation of 10 % of the property sizeand a three-year term for newly concluded rental agreements. The of-fice rents are index-linked. The market rent in the year of the respectivecontract conclusion corresponds to the company's own forecast, whilethe ageing process of the property is taken into account with a rent dis-count. The purchase yield (net initial yield) in the model corresponds tothe exit yield, so as to avoid distortions.
Residential
The study presents 68 residential markets, broken down into A-, B- and(other) university cities. The calculation is based on the assumption ofan existing apartment building with 4,000 square metres of residentialspace and 55 residential units and with average fixtures and fittings.Annual fluctuation of 200 square metres is assumed. The fluctuationcorresponds to the respective newly let space and a one-month va-cancy p.a. For existing rental agreement space, rent adjustments to themarket level every three years are assumed. The purchase yield (grossinitial yield) in the model corresponds to the exit yield, so as to avoiddistortions.
Micro-apartments
A-, B- and (other) university cities – a total of 68 cities – are analysed.The calculation is based on the assumption of a property with 4,000square metres of residential space and 200 fully furnished residentialunits of 20 square metres each. The base scenario assumes annualfluctuation of two-thirds of the total residential space, but the simulationalso includes fluctuation of 0 % and 100 %. The purchase yield (grossinitial yield) in the model corresponds to the exit yield, so as to avoiddistortions. An operator model is not assumed.
Specialist retail parks
The model is based on an ideal specialist retail centre with floor spaceof around 20,000 square metres. The user structure consists of severalretail spaces. Two anchor tenants and a use mix in line with the marketare assumed.
Shopping centres
The model is based on a three-storey shopping centre (including abasement level). It assumes one anchor tenant, a total of 78 retailspaces and sales space of 48,000 square metres.
Modern logistics properties
The model assumes an existing modern distribution/handling centre.Good divisibility and capacity for alternative uses are assumed. Thehall space totals 20,000 square metres. Office space accounts for lessthan 10 % of the hall space, meaning that it can be assumed that theamount of space for administration of the logistics hall is in line with de-mand. For reasons of simplification, office space therefore is not takeninto account separately in the model.
Business parks (Unternehmensimmobilie)
An existing business park with rental space of 12,000 square metres isassumed, with office use accounting for 30 % and warehouse use ac-counting for 70 %. All assumptions and data are based on informationfrom the INITIATIVE UNTERNEHMENSIMMOBILIEN and its Market Reports No.1 to No. 4.
Warehouses (Unternehmensimmobilie)
A simple existing warehouse with 10,000 square metres of warehousespace is assumed. In contrast to modern logistics space, there is onlylimited divisibility and capacity for alternative uses and the propertyquality is lower (including with regard to hall height, floor load capacityetc.). All assumptions and data are based on information from the INI-TIATIVE UNTERNEHMENSIMMOBILIEN and its Market Reports No. 1 to No. 4.
Light manufacturing (Unternehmensimmobilie)
A light manufacturing hall with 10,000 square metres of productionspace is assumed. In view of the high level of user specificity, longerlease terms (five years) are assumed than for the other types of de-scribed Unternehmesimmobilien. All assumptions and data are basedon information from the INITIATIVE UNTERNEHMENSIMMOBILIEN and its Mar-ket Reports No. 1 to No. 4.
Hotels
The calculations in this study relate to chain hotel businesses, definedas businesses with four or more individual hotels.
In addition, the analysis is based on fundamental assumptions that re-flect only part of the market. For example, it was assumed that a leasecontract is concluded; operator contacts and hybrid forms were not in-cluded in the analysis. Another fundamental assumption is that thecontract has a long term. The presentation of short-term contracts inthe case of yield-focussed investments with additional capex require-ments on expiry of the lease contract (generally two to three annualrents) was ensured by means of risk premiums and yield mark-ups.The model is based on city hotels with business customers and citytourists as their target groups. A high level of tourist demand is also as-sumed.
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© bulwiengesa AG 2016
ALT
Principals
Aurelis Real Estate GmbH & Co. KGBeiten Burkhardt Rechtsanwaltsgesellschaft mbH
Published bybulwiengesa AG Bettinastraße 6260325 Frankfurt am MainTelefon: +49 69 7561 467 60www.bulwiengesa.de
Published in September 2016
Conception and EditingSven Carstensen, bulwiengesa AGcarstensen@bulwiengesa.de
Silvia Beck, bulwiengesa AGbeck@bulwiengesa.de
Picture Creditswhite-studio / photocase.de
Copyright © 2016All rights reserved. Excerpts may be used when the source is provided. More extensive reproduction, publication, or dissemina-tion of content to third parties in any form is permitted only with the prior written consent of bulwiengesa AG and only if the origi-nal source is provided. The use of the study or parts of it for marketing prospectuses constitutes an exception – in such cases,prior written consent must always be obtained from bulwiengesa AG.
DisclaimerThe evaluations and calculations presented in this study and the research conducted were developed according to the best ofour knowledge and with the necessary care on the basis of existing sources or sources that were accessible when the studywas prepared. We do not provide any guarantee of the factual correctness of data and information from external sources. Theresults are interpreted and assessed in the context of bulwiengesa AG'S experience in its German and European research andconsultancy activities. The study makes no claim to be comprehensive and is made publicly available in order to encourage dis-cussion and dialogue with the relevant players.
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