A Stress Testing Scenario Analysis for House

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Presentation transcript:

A Stress Testing Scenario Analysis for House Prices: An Application to the Greek Market Michael Doumpos Technical University of Crete Dimitrios Papastamos Eurobank Property Services S.A. Constantin Zopounidis Dimitrios Andritsos June 28 - July 1, 2017, Delft, The Netherlands

Introduction

Stress tests 3

Objectives of the study 4

Automated valuation models (AVMs) 5

Data Description: Sample The data were provided by the Eurobank Property Services S.A. Hedonic characteristics of real estate properties The sample consists of 75,991 residential properties that have been professionally evaluated in the period 2007 – 2015 240 different administrative sectors covering all areas in Greece 32 aggregated administrative areas (Index Areas)

Data Description: Geographical Distribution

Data Description: Distribution of Properties 80% of the properties are flats 11% are houses 6% maisonettes 3% of type duplex

Data Description: Initial set of Hedonic Variables Record code Value V02 Year of valuation Year V03 Month of valuation Month no. V04 Administrative sector Code value V05 Urban classification V06 Survey value Euro V07 Type of residence V08 Usable residence area Sq. m. V09 Land area V10 Year of construction V11 Distance from CBD km V12 Floor Number V13 Total number of floors V14 Existence of parking space Yes/no (1/0) V15 Type of parking V16 Type of heating Code value (0-3) V17 Quality of construction V18 Number of bedrooms V19 Touristic hotspot V20 Elevator V21 View V22 Number of bathrooms

The structure of the AVM under consideration (database) The procedure applied by EPS during the Commercial Index production, is comprised of 4 phases: 10

The structure of the AVM under consideration (valuation process) EEC: European Economic Community 11

Econometric model 12

Estimation results

Monte Carlo Simulation The methodology implemented for constructing commercial property price indices is based on “repeat valuation” of commercial properties approach:

Simulation parameters

Profit / loss distribution (baseline scenario)

Profit / loss distribution (stressed scenario)

Results by region (baseline scenario)

Conclusions and future perspectives