Housing as a commodity? Operative behavior of German publicly listed housing organizations Presenter: Prof. Dr. Stefan Kofner, MCIH Tirana, 05.

Transcription

1 Housing as a commodity? Operative behavior of German publicly listed housing organizations Presenter: Prof. Dr. Stefan Kofner, MCIH Tirana, 05. September, 2017

2 1. Publicly listed housing organizations and their owners 2. Value drivers overview 3. Selected value drivers Rents Vacancies BPR Stock investment Portfolio strategies 4. Conclusion 2

3 Political background of the privatizations Public budgets: Austerity measures Pioneering role of federal holdings: Post, Rail, GAGFAH States and some communities followed, eg Dresden, Kiel and Berlin Special framework conditions for factoryrelated housing stock 3

4 Listed housing organizations at a glance Company Vonovia Deutsche Wohnen LEG TAG Grand City Adler Buwog Dtld Conwert Dtld Akelius Dtld Summe Based on a total stock of million rented apartments, this represents a share of 3.8 percent 5

5 Consolidation via takeovers Year Transaction 2010 Takeover of Colonia Real Estate AG by TAG Immobilien AG 2012 Takeover of KWG Kommunale Wohnen AG by Conwert Immobilien Invest SE 2013 Takeover of GSW Immobilien AG by Deutsche Wohnen AG 2014 Takeover of Gagfah S.A. by Deutsche Annington Immobilien SE (renamed in Vonovia SE) 02/2015 Attempted takeover of Conwert Immobilien Invest SE by Deutsche Wohnen AG (failed) 02/2015 Takeover of Westgrund AG by Adler Real Estate AG 09/2015 Attempted takeover of LEG Immobilien AG by Deutsche Wohnen AG (failed) 10/2015 Attempted takeover of Deutsche Wohnen AG by Vonovia SE für (failed) 03/2017 Takeover of Conwert Immobilien Invest SE by Vonovia SE The largest company now controls almost half of all housing units in the sector (less than ¼ at the end of 2013). The two largest providers together account for nearly two thirds of the housing stock (2013: 42 percent). 6

6 The owners Control conditions: Before the IPOs, owner-controlled AGs Today predominantly publicly owned AGs without controlling shareholders much more entrepreneurial freedom Limitations of freedom of action Stock trading, share price development Highly transparent environment (reporting requirements, ratings) Sanctioning of performance problems by the market for company control 7

7 Shares of investor groups in total market capitalization

8 Investment and portfolio strategies of selected shareholders Shareholder Investor type Regulation intensity Risk appetite Risk spread Time horizon Share of equity Sun Life Insurer high low high long 4 % Asset Value Investment company medium medium medium medium 100 % Norges Bank Sovereign low medium high long 60 % wealth fund Wellcome Trust Charity low high medium long 50 % Lansdowne Hedge fund low high gering short high 9

9 Business improvement Revenues Costs Business processes Housing stock Portfolio Rent increases: Mietspiegel Collective agreements Degree of centralization Allocation of capex funds Core and Non-core Rent increases: Fluctuation Assignment of tasks acc. To qualification Standardization Maintenance intensity Positioning Rent increases: Modernization Tax optimization Supply chain Management: Global and Single sourcing Modernization of buildings Spatial distribution Rents of newly built dwellings Vertical integration: Make or buy Modernization of dwellings Tenant privatization Vacancy reduction BPR Densification / Top-ups External growth Share of new development 10

10 Rental policy in ongoing leases Rent increases modernization-related fluctuation-related 11

11 Rental policy Company Vonovia 4,71 4,81 4,93 5,01 5,06 5,13 5,23 5,32 5,48 5,75 6,02 Dt. Annington 4,67 4,78 4,91 5,00 5,06 5,15 5,30 5,40 5,60 5,78 GAGFAH 4,76 4,85 4,95 5,02 5,07 5,36 5,15 5,21 5,35 5,55 Deutsche Wohnen 5,29 5,38 5,57 5,49 5,62 5,69 5,89 6,10 GSW 4,55 4,67 4,81 4,90 5,08 5,22 5,44 5,59 5,86 6,07 LEG 4,39 4,43 4,52 4,63 4,79 4,86 4,96 5,07 5,21 5,28 TAG 5,03 5,04 4,97 5,00 4,97 5,04 5,11 Grand City 4,86 4,90 5,20 5,30 5,40 Adler 5,14 5,02 4,93 5,00 Buwog Dtld. 5,70 5,34 5,51 5,68 Conwert Dtld. 5,31 5,53 5,73 Akelius Dtld. 7,19 7,52 7,71 7,77 8,13 8,56 GdW 4,51 4,55 4,62 4,75 4,86 4,96 5,04 5,15 5,27 5,36 5,51 Table: Development of average NCR in per m 2 and month Sources: business reports 12

12 Rental policy CPI plus 6,9 % Rent index plus 6,7 % Unternehmen Vonovia 0,99 1,36 1,91 1,69 2,92 4,70 13,64 Deutsche Annington 1,19 1,75 2,83 1,85 3,57 3,11 14,23 GAGFAH 0,99 5,41-4,08 1,15 2,62 3,60 9,47 Deutsche Wohnen 1,67 3,41-1,46 2,31 1,23 3,40 9,48 GSW 1,84 3,54 2,68 4,04 2,68 4,61 19,59 LEG 2,38 3,34 1,44 2,02 2,17 2,69 12,53 TAG 0,20-1,41 0,60-0,60 1,39 0,20 Grand City 0,82 5,77 1,89 Adler -2,39-1,83 Buwog Dtld. -6,74 3,09 Conwert 3,98 3,49 Akelius Dtld. 4,39 2,46 0,77 4,43 GdW 2,26 2,02 1,59 2,14 2,28 1,68 10,29 Table: Development of average NCR % YoY Sources: business reports 13

13 Rental policy City NCR 2006 NCR 2014 Percentage growth over the entire period Average annual growth in percent Berlin 4,38 5,28 20,5 2,6 Dresden 4,36 5,06 16,1 2,0 Hamburg 5,08 6,00 18,1 2,3 Köln 6,02 6,83 13,5 1,7 Bielefeld 4,20 4,84 15,2 1,9 Duisburg 4,32 5,03 16,4 2,1 Essen 5,11 5,25 2,7 0,3 Leverkusen 5,29 5,64 6,6 0,8 Dortmund 4,64 4,76 2,6 0,3 Table: Development of average NCR at selected Gagfah locations Sources: business reports 14

14 Regional perspective on price policy NCR growth rates of selected municipal and listed housing companies in Berlin, Hamburg and Dortmund no big differences between the two groups Berlin: the 6 municipal companies have increased their rents more since 2007 than the three large listed housing companies, but no major differences in the rental price level reached Hamburg: scarcely any differences in the level and adjustment of the rents between Gagfah and SAGA GWG, but relative restraint of the municipal company Dortmund: rent enhancing effect of the extensive modernizations of Deutsche Annington 15

15 Berlin Company Increase in average NCR % GAGFAH 25,4 Deutsche Wohnen 24,2 Deutsche Annington 22,3 Gesobau 30,3 STADT UND LAND 27,2 Gewobag 26,8 degewo 24,3 WBM 23,5 HOWOGE 22,2 Table: Growth rate of average NCR of different listed and state-owned housing companies in Berlin Sources: business reports, holdings reports of Senatsverwaltung für Finanzen 16

16 Vacancy rates Vacancies as an important success factor Since 2010 the trend of vacancy rates is downward Most companies are claiming to be able to significantly reduce vacancies in recently acquired portfolios. Largest strategic role at GCP Division of labor: Different portfolio strategies Grand City, TAG and Adler buy buildings with high vacancy rates. Deutsche Annington or Gagfah sell such stock. 17

17 Vacancy rates Company Vonovia 6,4 5,6 4,3 3,9 5,5 5,1 4,6 4,4 3,8 3,4 2,7 2,4 Dt. Annington 6,3 5,7 4,2 3,9 5,9 5,1 4,3 3,9 3,5 3,5 k.a. k.a. GAGFAH 6,4 5,5 4,4 3,9 4,9 5,2 5,1 5,0 4,1 3,4 k.a. k.a. Deutsche Wohnen 4,2 3,3 2,4 2,5 2,4 2,2 1,8 1,8 GSW 6,7 5,3 4,5 3,7 3,4 2,7 2,2 2,4 2,3 2,1 LEG 2,2 2,2 k.a. 3,9 3,6 3,6 3,1 2,9 2,7 2,5 2,9 TAG 10,3 6,5 11,6 9,9 8,8 8,1 7,5 6,1 Grand City 13,8 12,7 10,8 7,8 Adler 10,2 12,8 11,2 10,1 Buwog Dtld. 2,4 3,6 2,7 2,1 Conwert Dtld. 6,9 8,6 7,2 5,4 3,2 Akelius Germany, real Table: Vacancy rates in per cent Sources: business reports 0,4 0,9 1,6 2,0 1,1 18

18 MANAGEMENT TRACK RECORD TURNAROUND 19

19 Business process reengineering (BPR) Weak point Organization too decentralized Too much diversity and individualization in processes and components medium zur Beseitigung Centralization Standardization Too many / too expensive procurement sources, orders too small Supply Chain Management (Global and Single sourcing) Low degree of vertical integration Multiple weaknesses Insourcing BPR 20

20 Maintenance Company Vonovia 9,28 9,26 8,48 8,58 9,80 10,12 11,64 10,99 14,88 15,92 Deutsche Annington 9,83 9,73 10,00 10,35 10,81 9,93 12,21 11,26 k.a. k.a. GAGFAH 8,62 8,72 6,61 6,36 8,47 10,23 10,84 10,60 k.a. k.a. Deutsche Wohnen 9,85 9,63 9,81 9,68 10,36 9,59 9,45 9,63 GSW 7,64 6,74 6,07 5,87 6,25 8,83 10,15 LEG 9,06 12,78 6,78 5,94 6,84 7,08 7,84 8,77 TAG 6,39 5,21 5,73 5,11 Grand City 4,40 5,50 5,50 5,40 5,30 Adler 9,39 6,94 9,21 Buwog total 8,40 10,60 9,70 10,30 k.a. Conwert total 7,79 6,83 4,26 3,11 2,83 Akelius Dtld. 9,91 7,13 7,99 6,41 6,99 Table: Maintenance costs in per m 2 and year Sources: business reports 21

21 Modernization Company Vonovia 4,93 5,22 2,06 2,31 3,06 4,58 5,95 12,03 18,16 20,26 Deutsche Annington 0,75 5,50 2,65 3,82 5,29 7,70 8,22 15,55 GAGFAH 9,91 4,88 1,35 0,40 0,10 0,45 3,00 6,99 Deutsche Wohnen 4,35 6,02 8,19 9,26 4,67 6,92 10,53 15,29 GSW 5,44 6,27 7,93 9,23 8,97 7,20 14,17 LEG 3,74 1,09 6,92 6,96 7,16 6,73 8,26 9,45 TAG 11,54 10,41 11,05 4,67 8,16 9,42 10,30 Grand City 6,50 8,20 8,30 8,70 11,10 Adler 6,18 4,93 5,66 Buwog total 4,50 2,60 5,00 5,10 Conwert total 11,61 10,40 8,43 10,85 4,36 Akelius Dtld. 46,60 56,25 51,19 57,36 74,95 Table: Modernization cost in per m 2 and year Sources: business reports 22

22 Maintenance and modernization Company Vonovia 14,21 14,48 10,54 10,89 12,86 14,70 17,59 23,02 33,04 36,18 Deutsche Annington 10,58 15,23 12,65 14,17 16,10 17,63 20,43 26,81 k.a. k.a. GAGFAH 18,53 13,60 7,96 6,76 8,57 10,68 13,84 17,59 k.a. k.a. Deutsche Wohnen 14,20 15,65 18,00 18,94 15,03 16,51 19,98 24,92 GSW 13,08 13,01 14,00 15,10 15,22 16,03 24,32 LEG 25,54 19,54 12,80 13,87 13,70 12,90 14,00 13,81 16,10 18,22 TAG 11,54 10,41 11,05 11,06 13,37 15,15 15,41 Grand City 10,90 13,70 13,80 14,10 16,40 Adler 15,57 11,87 14,87 Buwog total 12,90 13,20 14,70 15,40 k.a. Conwert total 19,40 17,23 12,69 13,96 7,19 Akelius Dtld. 56,51 63,38 59,18 63,76 81,94 Table: Maintenance and modernization costs in per m 2 and year Sources: business reports 23

23 Rent increases after modernization Figure: Rent increases after modernization and heating cost savings: 20 case examples from Dortmund 24

24 Stock investment as compared with municipal housing companies Comparison with municipal housing Apart from Akelius and Vonovia, the expenditure of the listed housing companies maintenance and modernization remains well below the benchmark value for municipal companies (about / m 2 in 2015). Except for Vonovia, the listed companies also spend much less on maintenance than the municipal housing sector (around / m 2 in 2015). Different expenditure mix: Municipal: 60% maintenance and repair Listed: focus on the modernization Reason: The listed companies put a different weight to the different effects of maintenance and modernization on annual result and cash flow. 25

25 Portfolio management at Deutsche Wohnen Macro scoring model to rate the housing market Key scoring parameters Historic real estate data Change in households Change in-place rent Population growth Prognostic real estate data Population and household prognoses Macro economic data Unemployment rate Change in unemployment rate Purchase power per capita Change in purchase power Infrastructure data Students per inhabitants Change students per inhabitants High qualified employees per inhabitants Core+ ( growth ) Regions with increasing housing needs and a dynamic economic environment. Most markets with strong rental growth can be found here. Core ( yield ) Regions with a stable economic environment and a constant number of households. Here you can find markets with moderately rising rents. Non Core ( risk ) Regions with a stagnating economic environment or a negative trend, with the result that stocks are available for sale in these regions. 26

26 Micro scoring structure to rate the specific asset Performance Weighting 40% Score 2.9 Fair value EUR / sqm Tenant turnover return 1) Rental growth p. a. 1) Maintenance EUR / sqm 1) Rent potential In-place rent EUR / sqm Vacancy rate Micro score Score 3.1 Condition Weighting 30% Score 3.2 Building envelope Building services Property-on-property base Identify risks & opportunities Using scoring system Location Weighting 30% Score 3.1 Infrastructure Surrounding General attractiveness Traceable and consistent classification Based on periodically analyzed key performance indicators Using in-house information systems Scalable ranking of properties / quarters / portfolios Benchmark for sales and acquisitions Strategy-cluster The operate" strategy (approximately 82% of the portfolio) is used in housing estates with a good or excellent condition, where the focus is on re-letting and realizing rent potentials by eliminating the gap between existing and market rents without or with only a few investment. The "develop" strategy (approximately 11 percent of the portfolio) is applied to residential units at attractive locations but with a below average state and therefore should be revaluated by investments (31 percent expected rental growth potential). The disposal" strategy (approximately 7% of the portfolio) is applied to all residential units in the non-core regions as well as to about 5% of the core + and core regions, where privatization and block sales should create opportunistic value. 27

27 Spatial portfolio strategies Company Balanced Selected metropolises Individual state City categories Densely populated areas Cardinal direction Vonovia X Deutsche Wohnen X X LEG X TAG X Grand City X Adler X Buwog X Conwert Akelius X Table: Spatial portfolio strategies 28

28 Do they behave differently? Try to achieve tangible and sustainable cost reductions by using different value drivers Scale effects of large housing portfolios Significant reductions in personnel costs via consistent process optimization and after takeovers Catch up against the market rent / LRR Modernization related rent increases Reduction of vacancy rates (Grand City!) Pursue defined spatial portfolio strategies Fixation of organizations to KPIs The financial perspective seems to be dominant 29

29 Stakeholder interests Tenants Exploitation of margins for raising rents within the limits of rental price laws (catch up against market rent / LRR) Allocation of the costs for so called "energetic envelope modernizations" In the event of a functioning competition, rent reducing effects of continual efficiency increases, ceteris paribus Less individuality of care Computability of landlord behavior increases, e.g. by unification of information technology. 30