greek real estate challenges - tegova · 2016-03-31 · greek real estate challenges: an integrated...
TRANSCRIPT
Page 1
Regulated by RICS
Dimitris Andritsos
MSc MRICS
Chief Executive Officer
Eurobank Property Services
October 2015
Greek Real Estate challenges: An integrated approach on property valuations amidst
turbulent times
Page 2
I. Real Estate Market Overview
II. New Challenges in the Role of Valuers
III. The Contribution of the Greek Banking System
IV. Advanced Tools
V. Case Study: Valuations v/s Actual Transactions
VI. Conclusion
VII. APPENDIX
Table of Contents
Page 3
I. Real estate market overview
Note: Impact on recent developments (i.e. Capital Controls, MOU III) not yet factored in.
Source: ELSTAT
Inherent Problems:
Lack of Transparency
Tax Regime (Varying tax laws with high tax factors)
Urban Planning Complications
Overall Bureaucracy
Negative pressure attributed to:
Current Economic Climate
Political Instability and Uncertainty
Unfavorable Macroeconomic Forecasts
Resulted in:
Deferral or Cancellation of Investment Initiatives
Decrease in Development Activity
Precarious Forecasts
Requirement for Higher Yields
Page 4
I. Real Estate Market Overview
Sources: The World Bank, Bank of Greece, Eurobank Property Services Research
Page 5
I. Real Estate Market Overview
Structural Changes of Institutional Framework
A series of structural reforms in legislation have been
introduced to attract investments. These are:
Deregulation of commercial leases (Negotiable
duration minimum 3 years instead of 12 years)
(4242/2014)
Significant decrease in property transfer tax to 3%
(4223/2013)
Composite Touristic Investments (e.g. Hotels and
housing in the same development) (2012)
Special Plan of Spatial Development of Public Estate
(ΕΣΧΑΔΑ 3986/2011)
Special Plan of Spatial Development of Strategic
Investments (ΕΣΧΑΣΕ 4146/2013)
Recapitalization of the Banking System. Source: European Commission (May 2015), ELSTAT (September 2015)
Page 6
28th
5th
Emerging Trends in Real Estate
(ULI & PWC Report)
Investment Trends
Traditionally safe investment
destinations are oversaturated
(London, Zurich, Paris etc.)
Investors seeking returns are
more willing to assume
additional risk (German Stalwart
Cities, European Recovery
Plays’ etc.)
Investments & Infrastructure
Announcements (Indicatively)
Athens Metro and Tram
extensions
Faliron Seafront Regeneration
Pedestrianization of
Panepistimiou Avenue
Exploitation of former Hellinikon
airport (Lamda Development &
Foreign Investors)
Completion of Iconio-Thriasio
Rail line (logistics)
I. Real Estate Market Overview:
A light at the end of the tunnel?
2013 2014
Source: Emerging Trends Europe survey 2014 Source: Emerging Trends Europe survey 2015
Page 7
“Market value” definition by International Valuation Standards:
“The estimated amount for which an asset or liability should exchange on the
valuation date between a willing buyer and a willing seller in an arm’s length
transaction after proper marketing and wherein parties had each acted knowledgeably,
prudently and without compulsion ”.
II. New Challenges in the Role of Valuers
Prerequisites for reliable valuations:
In-depth Knowledge of Valuation Methodologies and
Practices:
High Academic and Professional Credentials of
Valuers
Continuous Professional Development
Market Intelligence
Access to Reliable Market Data
Monitoring of Market Trends & Changes
Quality Control: Effective Reviewing Mechanisms
Critical Question
How can this be applied in a
Market which is:
Intransparent
Stagnating (reduced
transaction volume)
Distressed
Page 8 II. New Challenges in the Role of Valuers
Number of accredited valuers by TEGOVA 2011-2015,
Source: AVAG
Sophistication of Appraisal Practices
Progress on an institutional level: Increasing
demand for high level of professional and academic
credentials
Specialized institutions’ presence (e.g. TEGOVA,
AVAG, HVI, RICS, ULI, ICSC) in the Greek market
Supported by senior property professionals
Organization of training events (Life-long
learning programs through seminars,
workshops)
Increase in headcount of officially certified valuers
TEGOVA: 29 members in 2009; 504 in 2014
New categories of accreditations have been
added: (e.g. Valuer specializing in Plant and
Equipment)
RICS: 27 members in 2003; 151 in 2015
Page 9 III. The Contribution of the Greek Banking System
Banking system is the major stakeholder in
Greek Real Estate, controlled and supervised by
European organizations such as European
Central Bank, and national supervision
authorities (Bank of Greece)
Wide network of accredited valuers on a
national level with in depth knowledge of local
sub-markets
Valuers are qualified professionals, certified
by international organizations with high
professional recommendations and having
undergone special training
Assessment of valuers per case and on an annual basis
0
50
100
150
200
250
300
Consumerloans
Residentialloans
Bussinessloans
Total NPLs
Vo
lum
e i
n €
bn
Total Volume of Outstanding Loans
Source: Bank of Greece (BoG)
Page 10
Appraisal 1st
Review 2nd
Review Sample
Checking
Multiple steps of reviewing process
“4-eye” principal (or 6- or 8-eye for complex cases),
Centralised character of reviewing on a senior level according to predetermined control criteria,
Red flag check,
Sample checking of valuations by external independent valuers.
Specialized Software development (REAL II, WAVE etc.),
Software developments along with the requirements of Internal Control result in high level risk
audit.
Development and exploitation of sophisticated tools
III. The Contribution of the Greek Banking System:
Quality Control
Page 11
Advanced tools used for valuation assessment and effective risk management:
1. Regularly Updated Market Reports
2. Residential & Commercial Indices which help monitoring Market Trends & Changes
3. Forecasts
4. Sophisticated Statistical Tools which provide Current Market Price Estimations &
monitor Risk (e.g. Automated Reviewing Mechanism (ARM))
IV. Advanced Tools
Page 12
A wide range of reports covering all major property markets are updated regularly,
estimating the sale price and rent ranges per property type for each geographical area,
early identifying changes in market trends
Market Reports
Property Age (residential properties)
Up to 10 years
11-20
21-30
31-40
>40 years
Location
Expensive
Medium
Economic
Annual Nation-wide reports on local commercial
property markets (offices – retail) in their entirety as
well as their sub-segments.
Periodical Prefecture level reports on all major
markets (residential – offices – retail). For the
prefectures of Attica and Thessaloniki we publish the
respective reports for each of their municipalities. The
number of total reports updated semi-annually is 233.
Specialized market reports as well as major
market sub-segment reports (e.g. Offices on
Syngrou Avenue) or specific area reports (e.g. island
of Rhodes hotel market) etc.
IV. Advanced Tools:
Market Intelligence
Structure of Residential Market Reports
Page 13 IV. Advanced Tools:
Residential and Commercial Indices
Residential Indices
15 Indices in Attica
24 Indices in Thessaloniki & Rest of Greece
1 Index for Greece
Year of Construction
2 Indices for Greece (Old &
New Apartments)
2 Indices for Athens (Old &
New Apartments)
Commercial Indices
Office Retail
Valuations are collected on a quarterly basis.
Page 14 IV. Advanced Tools:
Residential and Commercial Indices
0
20
40
60
80
100
120
2007 2008 2009 2010 2011 2012 2013 2014 2015
Residential Index Comparison: BoG - EPS - PropIndex
BoG EPS PropIndex
0
20
40
60
80
100
120
Quarter
EPS Commercial Index
All Office Retail
Residential: 40% decrease since 2007
Commercial: 50% decrease since 2007
Page 15
Residential Index Forecasts are based on:
– World leading quality macro economic data and forecasts at local
level
– Exhaustive collection of local level planning and building activity
data
– Outcome of advanced econometric modelling, consistent with
latest theoretical scientific literature, fully integrated with relevant
macroeconomic variable forecasts (Inflation, Interest Rates,
Household Disposable Income etc.)
– Covering from short term to long term (over 4 years) horizon, with
quarterly predictions.
IV. Advanced Tools:
Forecasts
Page 16
Automated Reviewing Mechanisms (ARM)s are testing
instruments based on the structure of Automated Valuation
Models (AVMs).
ARMs use the same tools and information with the AVMs.
The uniformity and performance of ARM’s database has been
carried out according to the Standards on Automated Valuation
Models (AVMs), approved by the IAAO* and ANEVAR.
ARMs enable quick and effective monitoring of valuations.
ARMs work as an ALERT system that point toward the cases with
abnormal deviations.
AVM
Extensive Database &
Updated Market Reports
Forecasting & Questionnaires
Hedonic Regression
Model
Four-phased procedure: An efficient and transparent process of continuous
monitoring
IV. Advanced Tools:
Automated Reviewing Mechanism (ARM)
*International
Association of
Assessing
Officers
Real Time
ARM Filter Valuation
1st Review
Phase 3 Phase 4
2nd Review
Phase 2 Phase 1
Initial Certified Valuation
of portfolio or single
property
1st review from
specialized experts
(market researchers
and reviewers)
Usage of ARM checker
for identification of
large deviations
2nd Review for cases
with deviations
over 20%
Page 17 IV. Automated Reviewing Mechanism:
Performance Procedures
Average deviation 1.30%
12.80% Mean Absolute
Deviation at National Level
54.22% of appraisals with
deviation less than 10%
About 80.60% of appraisals
with deviation
less than 20%
The quality of the data is
checked daily under a four-
phase procedure.
Page 18 V. Case Study “Valuations v/s Actual Transactions”:
Data Collection
1. Collection of transactions’ data from multiple
sources:
i. Eurobank Property Services’ Database
ii. Local Real Estate Agents
2. Type of Transactions
i. Commercial
Office
Retail
ii. Residential
Apartments (90% of Sample)
Semi-detached houses
Detached houses
Transactions
Residential (focused on apartments - total sample: 200)
Commercial (Limited # of transactions - total sample: 34)
Research focused on Attica due to the high concentration of transactions.
Source (images): kasrawy.deviantart.com,
www.rightmove.co.uk
Page 19 V. Case Study “Valuations v/s Actual Transactions”:
Limitations
No study goes without limitations:
Grammy Award Winning Artist Phil Hansen once said:
“Embrace your LIMITATIONS and watch yourself
become LIMITLESS”
In this case study, the following limitations, regarding
transaction data were faced:
1. Insufficient address data (e.g. The street name was
known but not the exact location – street number etc.) Source: Image - http://dfwhailrepair.com/ on 23/9/2015
2. Subjective evaluation of property characteristics amongst agents (e.g. condition of
maintenance, view etc.),
3. Exact Transaction Date (Indexation purposes – e.g. 2nd Semester of 2014 was expressed
as 15/9/2014),
4. Insufficient property characteristics (e.g. floor number, condition of maintenance etc.) for a
small number of transactions.
Page 20
Three (3) sets of values were created to be compared to transactions:
Statistically Estimated Value (produced by ARM)
Certified Valuation (desktop)
Market Range
For a transaction to be considered special (non-ordinary), the criterion was to FAIL all three sets
of values. An ordinary transaction only needed to pass one test.
1st check – Statistically Estimated Value
Checks the deviation between the value created by the mathematical model and the transaction.
2nd check – Certified Valuation
Checks the deviation between the value created by the network and the transaction.
3rd check – Market Range
Checks whether the transaction lies between the range of the reports or the extended range +/-20% (loose criterion).
“SPECIAL
TRANSACTION”
V. Case Study “Valuations v/s Actual Transactions”:
Procedure
Page 21
Results: Ordinary Transactions (68%)
Special
Transactions (32%)
Ordinary
Transactions (68%)
Summary
Transaction
/Desktop
Transaction
/ARM
Market
Report
Ranges
Mean
Deviation -5.6% -6.1% Within
Range
Mean
Absolute
Deviation
12.9% 14.2% Within
Range
V. Case Study “Valuations v/s Actual Transactions”:
Residential Results
Page 22
Results: Non-Ordinary Transactions (32%)
The results indicate that those transactions were special (non-
ordinary). The sale prices are not close to any of the values
and additionally do not fall within the market report ranges,
leading to extremely large deviations. The results imply that
transactions have occurred in a different level of prices due to:
Tax Motives (not arm’s length)
Special Circumstances (e.g. rumors for haircuts on bank
accounts, capital controls etc.)
Forced Sales (distressed sales)
Other
V. Case Study “Valuations v/s Actual Transactions”:
Residential Results
Page 23
Results: All Transactions (Non-ordinary & Ordinary)
Special Transactions
(12%)
Ordinary
Transactions (88%)
V. Case Study “Valuations v/s Actual Transactions”:
Commercial Results
Page 24
Results: Commercial Ordinary Transactions (88%)
V. Case Study “Valuations v/s Actual Transactions”:
Commercial Results
Page 25
Results: Commercial Non-Ordinary Transactions (12%)
V. Case Study “Valuations v/s Actual Transactions”:
Commercial Results
Page 26 V. Case Study “Valuations v/s Actual Transactions”:
Summary of Results (Cumulative Charts)
Page 27
VI. Conclusion
An integrated approach was adopted to improve reliability of valuations in
turbulent times:
1. Improved Qualifications of Valuers (training, continuous professional
development, certifications etc.)
2. Development of Sophisticated Systems (Review Mechanisms, Software –
REAL, WAVE etc.)
3. Utilization of Tools (indices, market reports to capture market trends, ARM,
forecasts).
This approach resulted in a success rate of valuations between deviation
ranges [-20%,20%] of 80% for both residential and commercial properties.
Page 28
VII. APPENDIX
APPENDIX
Page 29
VII. Legislative aspects of an AVM
Internationally (UK):
The Financial Service Authority provides general guidance in its Prudential
sourcebook for Banks, Building Societies and Investment Firms (known as
BIPRU). Rule 3.4.66 sets out the method for monitoring property values,
noting that it allows ‘statistical methods to be used to monitor the value of
the property and to identify property that needs revaluation’.
AVM is bound to limitations in usage in line with international practice
Explicit terms and conditions are provided on the EPS website
Page 30
VII. Development of EPS AVM
The overall construction and assessment of the EPS AVM has been established
according to ANEVAR’s guidelines. EPS followed the hereinafter stages:
Stage 1: Sampling Procedures
Stage 2: Sample Size
Stage 3: Data Management and Data Quality Analysis
Stage 4: Stratification
Stage 5: Determining Model Specifications
Stage 6: Model Calibration
Stage 7: Model Testing for Quality
Stage 8: Model Validation
Stage 9: Model Application
Stage 10: Periodic Check of Model Accuracy
Page 31
Hedonic Regression Model:
is in the heart of ARM and Index developments
Ln(V6li/V8li) = Σb1ljVji + Σb2jLji + Σb3jaji + eli
provides the optimum coefficients for each
property characteristic, useful in developing a
successful mathematical process based on:
– Market forecasting
Indices are based on historical data and
therefore reflect both the present and the past)
– Market Reports
Cover multiple areas.
Present the current sale price and rent ranges for
each geographical area.
– Specialized Questionnaires filled in by Market
Experts
AVM
Extensive Database &
Updated Market Reports
Forecasting & Questionnaires
Hedonic Regression
Model
VII. Advanced Tools:
Automated Valuation Model (AVM)
Page 32
Ratio Study Performance Standards
Area Characteristics COD* PRD*
Newer, more
homogeneous areas 10.0 or less 0.98-1.03
Older, heterogeneous
areas 15.0 or less 0.98-1.03
Rural residential and
seasonal 20.0 or less 0.98-1.03
VII. Advanced Tools:
Uniformity and Performance of Database
The uniformity and performance of ARM’s database has
been carried out according to the Standards on
Automated Valuation Models (AVMs), approved by the
International Association of Assessing Officers.
Greek Real Estate has shown a more heterogeneous performance with COD less than 15 (12.8) and an automatic
reviewer model that shows a very good performance both to low valued and high valued properties (PRD close to 1).
*ARM: Automated Reviewing Mechanism
*COD: Coefficient of Dispersion
*PRD: Price Related Differential